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2023(1):1-10, DOI: 10.19781/j.issn.1673?9140.2023.01.001
Abstract:
Aiming at the problem that the wind storage system's power fluctuation suppression effect is unsatisfactory, the wind storage system's operation is optimized. Considering the time series coupling characteristics of wind storage system operation and the influence of future wind power fluctuation on the energy storage system (ESS), an optimization strategy based on stabilizing target optimization method and model predictive control (MPC) is proposed. Firstly, the expected grid?connected power is calculated according to the predicted wind power and the constraints of ESS, and the local prediction accuracy is introduced to correct it. Then, combined with the current state of charge (SOC) of ESS, the optimal stabilization target is obtained by fuzzy control; Lastly, the MPC with particle swarm optimization (MPC?PSO) strategy is used to optimize the ESS power, so as to minimize the difference between the grid?connected power of next time and the optimal target power and minimize the ESS power. The simulation results show that the strategy proposed in this paper has a better wind power fluctuation smoothing effect and can effectively reduce the operation cost of energy storage.
Aiming at the problem that the wind storage system's power fluctuation suppression effect is unsatisfactory, the wind storage system's operation is optimized. Considering the time series coupling characteristics of wind storage system operation and the influence of future wind power fluctuation on the energy storage system (ESS), an optimization strategy based on stabilizing target optimization method and model predictive control (MPC) is proposed. Firstly, the expected grid?connected power is calculated according to the predicted wind power and the constraints of ESS, and the local prediction accuracy is introduced to correct it. Then, combined with the current state of charge (SOC) of ESS, the optimal stabilization target is obtained by fuzzy control; Lastly, the MPC with particle swarm optimization (MPC?PSO) strategy is used to optimize the ESS power, so as to minimize the difference between the grid?connected power of next time and the optimal target power and minimize the ESS power. The simulation results show that the strategy proposed in this paper has a better wind power fluctuation smoothing effect and can effectively reduce the operation cost of energy storage.
2023(1):11-17, DOI: 10.19781/j.issn.1673?9140.2023.01.002
Abstract:
The application of energy storage optimization configuration and demand?side response in the integrated energy system can decouple the constraints of "heating to determine power" in the operation of combined heat and power (CHP) units, and improve energy utilization efficiency. Therefore, taking the performance of power generation, heating, electricity consumption and heat consumption on both sides of the source and charge into account, installing the electricity?heat energy storage equipment on the source side to realize the thermoelectric decoupling of CHP, and fully utilizing the dispatching value of the electricity?heat integrated demand response (IDR) resources on the load side, an optimal configuration model for electric and thermal energy storage capacity of regional integrated energy systems considering the integrated demand responses is established. The model considers the constraints of electricity storage and heat storage, power balance constraints, etc., and aims to minimize the total annual cost of the regional comprehensive energy system to solve the problem of optimal economic allocation of electricity and thermal energy storage. The results of case study show that coordinated operation of multiple energy storage and load side can reduce operating cost, and considering the integrated demand response reduces the configuration capacity of energy storage. The energy storage configuration on the source side and the integrated demand response on the load side promote wind power consumption, and improve the economy, precision and flexibility of the integrated energy system operation.
The application of energy storage optimization configuration and demand?side response in the integrated energy system can decouple the constraints of "heating to determine power" in the operation of combined heat and power (CHP) units, and improve energy utilization efficiency. Therefore, taking the performance of power generation, heating, electricity consumption and heat consumption on both sides of the source and charge into account, installing the electricity?heat energy storage equipment on the source side to realize the thermoelectric decoupling of CHP, and fully utilizing the dispatching value of the electricity?heat integrated demand response (IDR) resources on the load side, an optimal configuration model for electric and thermal energy storage capacity of regional integrated energy systems considering the integrated demand responses is established. The model considers the constraints of electricity storage and heat storage, power balance constraints, etc., and aims to minimize the total annual cost of the regional comprehensive energy system to solve the problem of optimal economic allocation of electricity and thermal energy storage. The results of case study show that coordinated operation of multiple energy storage and load side can reduce operating cost, and considering the integrated demand response reduces the configuration capacity of energy storage. The energy storage configuration on the source side and the integrated demand response on the load side promote wind power consumption, and improve the economy, precision and flexibility of the integrated energy system operation.
2023(1):18-26, DOI: 10.19781/j.issn.1673?9140.2023.01.003
Abstract:
The increasing charging load of electric vehicles will have an impact on the economy operation and reliability of the power system. Power system production simulation is an important analysis method of cost and reliability , and it is necessary to consider such charging loads. Firstly, based on the impact of the temperature, the charging load prediction model of electric vehicles is established by the Monte Carlo sampling method. Then, in a continuous load model for electric vehicles to pursuit the lowest annual production and operation cost of the system. The factors such as maintenance plan, start and stop cost, and operation cost constraints of each generator are incorporated, an optimization model of mid/long?term power system production is built. Finally, the CPLEX is used to solve this optimization model to realize the simulation of power system productions, which can modeling the factors like production and operation parameters of each generator, maintenance scheme, total system power generation and total system operation cost. Based on the modified IEEE?RTS 79 test system, a case study is presented to verify the feasibility of the proposed method, and the influence of electric vehicle charging load on power systems is also analyzed.
The increasing charging load of electric vehicles will have an impact on the economy operation and reliability of the power system. Power system production simulation is an important analysis method of cost and reliability , and it is necessary to consider such charging loads. Firstly, based on the impact of the temperature, the charging load prediction model of electric vehicles is established by the Monte Carlo sampling method. Then, in a continuous load model for electric vehicles to pursuit the lowest annual production and operation cost of the system. The factors such as maintenance plan, start and stop cost, and operation cost constraints of each generator are incorporated, an optimization model of mid/long?term power system production is built. Finally, the CPLEX is used to solve this optimization model to realize the simulation of power system productions, which can modeling the factors like production and operation parameters of each generator, maintenance scheme, total system power generation and total system operation cost. Based on the modified IEEE?RTS 79 test system, a case study is presented to verify the feasibility of the proposed method, and the influence of electric vehicle charging load on power systems is also analyzed.
2023(1):27-34, DOI: 10.19781/j.issn.1673?9140.2023.01.004
Abstract:
The proportion of renewable energy in the supply side of the electricity market is gradually expanding, whilst its supply uncertainty increases the risk of electricity market trading. Under the background, an integrated trading strategy is proposed considering the day?ahead electricity price and supply uncertainty. Firstly, renewable energy aggregators utilize the demand response to deal with the uncertainty of electricity production. Then, they make a contract with demand response operators by comprehensively considering the contractual settlement price and activation charge of demand response. After that, the power is transferred according to demand. The cost of demand response switching to different times is decided by the contracted power, no need to consider when and where they will be used. Secondly, the operator participates in day?ahead market transactions through non?contractual demand response and further increases its revenue. Finally, the conditional value?at?risk (CVaR) by assessing expected cost volatility. Thereby, the risk aversion is incorporated into the decision model to avoid overly conservative trading scenarios. In the end, the proposed decision method is evaluated in a test system to validate the effectiveness of the method. It is shown that the proposed method can increase the expected returns of different market participants while reducing the associated risks.
The proportion of renewable energy in the supply side of the electricity market is gradually expanding, whilst its supply uncertainty increases the risk of electricity market trading. Under the background, an integrated trading strategy is proposed considering the day?ahead electricity price and supply uncertainty. Firstly, renewable energy aggregators utilize the demand response to deal with the uncertainty of electricity production. Then, they make a contract with demand response operators by comprehensively considering the contractual settlement price and activation charge of demand response. After that, the power is transferred according to demand. The cost of demand response switching to different times is decided by the contracted power, no need to consider when and where they will be used. Secondly, the operator participates in day?ahead market transactions through non?contractual demand response and further increases its revenue. Finally, the conditional value?at?risk (CVaR) by assessing expected cost volatility. Thereby, the risk aversion is incorporated into the decision model to avoid overly conservative trading scenarios. In the end, the proposed decision method is evaluated in a test system to validate the effectiveness of the method. It is shown that the proposed method can increase the expected returns of different market participants while reducing the associated risks.
2023(1):35-42, DOI: 10.19781/j.issn.1673?9140.2023.01.005
Abstract:
After the receiving?end AC fault occurs in the multi?infeed HVDC system, it is easy to cause simultaneous commutation failure of multiple DCs, resulting in a large quantity of power shortage and active power fluctuation. In order to achieve effective suppression of grid power fluctuation after the receiving?end AC faults in the multi?infeed HVDC transmission system, from the perspective of AC/DC interaction strength and the critical nodes and lines of active power, a siting method of the energy storage system is proposed for suppressing power fluctuation of the AC system after commutation failure is proposed. Firstly, the candidate areas are determined according to the multi?infeed interaction factor(MIIF), and then the candidate sites are determined by the multi?infeed effective short circuit ratio(MIESCR). Finally, the specific location of the energy storage system is determined by the active power fluctuation rate of the whole network(APFRWN). The simulation results are verified in PSCAD based on the modified IEEE?39 bus system. The location method of the energy storage system proposed in this paper can effectively reduce the power fluctuation caused by DC commutation failure caused by AC fault at the receiving end and improve the stability of the AC system.
After the receiving?end AC fault occurs in the multi?infeed HVDC system, it is easy to cause simultaneous commutation failure of multiple DCs, resulting in a large quantity of power shortage and active power fluctuation. In order to achieve effective suppression of grid power fluctuation after the receiving?end AC faults in the multi?infeed HVDC transmission system, from the perspective of AC/DC interaction strength and the critical nodes and lines of active power, a siting method of the energy storage system is proposed for suppressing power fluctuation of the AC system after commutation failure is proposed. Firstly, the candidate areas are determined according to the multi?infeed interaction factor(MIIF), and then the candidate sites are determined by the multi?infeed effective short circuit ratio(MIESCR). Finally, the specific location of the energy storage system is determined by the active power fluctuation rate of the whole network(APFRWN). The simulation results are verified in PSCAD based on the modified IEEE?39 bus system. The location method of the energy storage system proposed in this paper can effectively reduce the power fluctuation caused by DC commutation failure caused by AC fault at the receiving end and improve the stability of the AC system.
2023(1):43-54, DOI: 10.19781/j.issn.1673?9140.2023.01.006
Abstract:
This paper proposes an optimal siting and sizing method for distributed energy storage in distribution networks considering islanding duration uncertainty. The uncertainty of the islanding duration is described based on robust optimization, which improves the ability of islanding operation and guarantees the un interrupted power supply of important loads. The planning model aims to minimize the sum of the annual investment cost of energy storage, the annual power purchase cost of the distribution network, and the operation and maintenance cost of energy storage, the configuration and operation constraints of distributed energy storage, photovoltaic output constraints, distribution network flow constraints, grid operation safety constraints, power purchase constraints and load power supply constraints and the uncertainty of islanding duration is considered in the planning model. The column?and?constraint generation algorithm (C&CG) is adopted to solve the mixed?integer second?order cone robust programming model. The planning model is carried out under an actual distribution network. The results show that the established model can optimize the planning solution of distributed energy storage while guarantee the power supply of important loads considering the islanding duration uncertainty, and improves the ability of distribution network islanding operation and economy
This paper proposes an optimal siting and sizing method for distributed energy storage in distribution networks considering islanding duration uncertainty. The uncertainty of the islanding duration is described based on robust optimization, which improves the ability of islanding operation and guarantees the un interrupted power supply of important loads. The planning model aims to minimize the sum of the annual investment cost of energy storage, the annual power purchase cost of the distribution network, and the operation and maintenance cost of energy storage, the configuration and operation constraints of distributed energy storage, photovoltaic output constraints, distribution network flow constraints, grid operation safety constraints, power purchase constraints and load power supply constraints and the uncertainty of islanding duration is considered in the planning model. The column?and?constraint generation algorithm (C&CG) is adopted to solve the mixed?integer second?order cone robust programming model. The planning model is carried out under an actual distribution network. The results show that the established model can optimize the planning solution of distributed energy storage while guarantee the power supply of important loads considering the islanding duration uncertainty, and improves the ability of distribution network islanding operation and economy
2023(1):55-65, DOI: 10.19781/j.issn.1673?9140.2023.01.007
Abstract:
With the strategic goal of developing "double carbon", it is required to further promote the large?scale integration of wind and solar power as the main source of clean energy. In order to improve the wind power consumption capability and reduce the wind power curtailment, a interactive optimization operation model of regenerative electric heating and wind power considering user satisfaction is proposed. Firstly, the operation principle of regenerative electric heating equipment participating with wind power is analyzed; then, a multi?objective optimization model for the combined operation of regenerative electric heating and wind power is established considering wind power consumption, economical property and user satisfaction. A grey relational analysis based improved chaotic particle swarm optimization algorithm is adopted for solving the proposed model; finally, an operation scheme which satisfying all the operation requirements is proposed based on the simulation data of a real grid. The simulation results show that the model can effectively increase the wind power consumption capability, reduce the operating cost, satisfy the user's thermal comfortable level, and provide decision support for future development for the regenerative electric heating and wind power.
With the strategic goal of developing "double carbon", it is required to further promote the large?scale integration of wind and solar power as the main source of clean energy. In order to improve the wind power consumption capability and reduce the wind power curtailment, a interactive optimization operation model of regenerative electric heating and wind power considering user satisfaction is proposed. Firstly, the operation principle of regenerative electric heating equipment participating with wind power is analyzed; then, a multi?objective optimization model for the combined operation of regenerative electric heating and wind power is established considering wind power consumption, economical property and user satisfaction. A grey relational analysis based improved chaotic particle swarm optimization algorithm is adopted for solving the proposed model; finally, an operation scheme which satisfying all the operation requirements is proposed based on the simulation data of a real grid. The simulation results show that the model can effectively increase the wind power consumption capability, reduce the operating cost, satisfy the user's thermal comfortable level, and provide decision support for future development for the regenerative electric heating and wind power.
2023(1):66-76, DOI: 10.19781/j.issn.1673?9140.2023.01.008
Abstract:
The planning of electric vehicle charging stations needs to consider not only the cost of connecting to the power grid but also the convenience of electric vehicle users, as well as the impact of traffic congestion on user travel. Based on the spatial and temporal distribution characteristics of electric vehicles, an electric vehicle spatial?temporal distribution model is established. The impact of traffic congestion on the travel characteristics of electric vehicle users and the selection of charging stations is fully considered, and the electric vehicle entry capacity is calculated at different times. A mixed?integer second?order cone programming model is established to minimize the total investment cost, total operating cost, and total user travel cost, taking into account the impact of traffic congestion on electric vehicle charging station planning. The effectiveness and feasibility of the proposed method for planning electric vehicle charging stations considering traffic congestion are verified through hypothetical planning areas.
The planning of electric vehicle charging stations needs to consider not only the cost of connecting to the power grid but also the convenience of electric vehicle users, as well as the impact of traffic congestion on user travel. Based on the spatial and temporal distribution characteristics of electric vehicles, an electric vehicle spatial?temporal distribution model is established. The impact of traffic congestion on the travel characteristics of electric vehicle users and the selection of charging stations is fully considered, and the electric vehicle entry capacity is calculated at different times. A mixed?integer second?order cone programming model is established to minimize the total investment cost, total operating cost, and total user travel cost, taking into account the impact of traffic congestion on electric vehicle charging station planning. The effectiveness and feasibility of the proposed method for planning electric vehicle charging stations considering traffic congestion are verified through hypothetical planning areas.
2023(1):77-87, DOI: 10.19781/j.issn.1673?9140.2023.01.009
Abstract:
As a high?quality demand response resource, electric heating load groups can improve the operation of distribution network through optimization dispatch. In order to achieve reasonable dispatching of electric heating loads, an optimal strategy for electric heating load groups that takes into account user behavior difference and distribution network flow is proposed. At first, the prediction mechanism of the controllable capacity of electric heating load is analyzed. Secondly, according to the influencing factors of user demand response behavior, the users are integrated into multiple electric heating load aggregates, and the thermal comfort design and controllable capacity solution of each group are carried out. Considering the power flow constraints of the distribution network, an optimal dispatch model for electric heating load groups with the goal of minimizing load fluctuations is established. The example analysis shows that the optimal scheduling model can improve the accuracy of electric heating load response prediction, improve the effect of peak?cutting and valley filling in the distribution network, and is conducive to the economic and safe operation of the system.
As a high?quality demand response resource, electric heating load groups can improve the operation of distribution network through optimization dispatch. In order to achieve reasonable dispatching of electric heating loads, an optimal strategy for electric heating load groups that takes into account user behavior difference and distribution network flow is proposed. At first, the prediction mechanism of the controllable capacity of electric heating load is analyzed. Secondly, according to the influencing factors of user demand response behavior, the users are integrated into multiple electric heating load aggregates, and the thermal comfort design and controllable capacity solution of each group are carried out. Considering the power flow constraints of the distribution network, an optimal dispatch model for electric heating load groups with the goal of minimizing load fluctuations is established. The example analysis shows that the optimal scheduling model can improve the accuracy of electric heating load response prediction, improve the effect of peak?cutting and valley filling in the distribution network, and is conducive to the economic and safe operation of the system.
2023(1):88-96, DOI: 10.19781/j.issn.1673?9140.2023.01.010
Abstract:
The characteristics of AC/DC hybrid system faults are different from those of AC systems, which will affect the reaction of traditional AC protections. For the power frequency variation distance protection, firstly, the variation range of equivalent impedance angle of protection back system is analyzed from the perspective of quadrants, and then its action characteristics are further assessed. The results show that the protection range of power frequency variation distance protection in AC/DC hybrid system will be reduced, the anti?transition resistance capacity will be weakened, and the protection range may be completely lost in some extreme cases. To solve this, the reliability coefficient is diminished, the cosine value of phase difference of zero sequence current on both sides is used to avoid misoperation outside the area, and thus an improved measure of power frequency variation distance protection based on zero sequence current phase compensation can be proposed. An case study platform is built on PSCAD/EMTDC to verify the correctness of the theoretical analysis, and the effectiveness of the proposed improvement measures.
The characteristics of AC/DC hybrid system faults are different from those of AC systems, which will affect the reaction of traditional AC protections. For the power frequency variation distance protection, firstly, the variation range of equivalent impedance angle of protection back system is analyzed from the perspective of quadrants, and then its action characteristics are further assessed. The results show that the protection range of power frequency variation distance protection in AC/DC hybrid system will be reduced, the anti?transition resistance capacity will be weakened, and the protection range may be completely lost in some extreme cases. To solve this, the reliability coefficient is diminished, the cosine value of phase difference of zero sequence current on both sides is used to avoid misoperation outside the area, and thus an improved measure of power frequency variation distance protection based on zero sequence current phase compensation can be proposed. An case study platform is built on PSCAD/EMTDC to verify the correctness of the theoretical analysis, and the effectiveness of the proposed improvement measures.
2023(1):97-107, DOI: 10.19781/j.issn.1673?9140.2020.01.011
Abstract:
With the grid connection of large scale distributed generations, the regulation and control of distribution network becomes more diversified. Under the circumstance, the key influence factors of the decoupling optimization and coordinated optimization of active and reactive power is investigated. Firstly, an analysis method considering the influence of the changing of power source, network, and load on the power optimization of distribution network is proposed for problem of the power optimization for distribution network containing distributed generation. Then, based on the two power optimization models, the interaction mechanisms between power optimization and grid price, network parameters and load are analyzed. And the mathematical expressions of line impedance ratio and load power factor to transmission power are given. In addition, the boundary conditions of two optimization modes are given qualitatively. At last, an improved IEEE?33 bus system is included to verify the impact of core influence factors for two power optimization modes on the total power generation cost and calculation time, including the feed?in tariff, the impedance rate and length of transmission line, the power factors and load.
With the grid connection of large scale distributed generations, the regulation and control of distribution network becomes more diversified. Under the circumstance, the key influence factors of the decoupling optimization and coordinated optimization of active and reactive power is investigated. Firstly, an analysis method considering the influence of the changing of power source, network, and load on the power optimization of distribution network is proposed for problem of the power optimization for distribution network containing distributed generation. Then, based on the two power optimization models, the interaction mechanisms between power optimization and grid price, network parameters and load are analyzed. And the mathematical expressions of line impedance ratio and load power factor to transmission power are given. In addition, the boundary conditions of two optimization modes are given qualitatively. At last, an improved IEEE?33 bus system is included to verify the impact of core influence factors for two power optimization modes on the total power generation cost and calculation time, including the feed?in tariff, the impedance rate and length of transmission line, the power factors and load.
2023(1):108-113, DOI: 10.19781/j.issn.1673?9140.2023.01.012
Abstract:
A reasonable comprehensive evaluation of distribution network resilience can reflect the ability of distribution network to restore power supplies when random faults occur, which is also helpful to diagnose the performances of different countermeasures for a higher resilience and lower losses. According to the mutual impacts by network nodes under different random faults, one comprehensive evaluation method for the resilience of active distribution networks (ADN) is presented to handle such an uncertainty. Firstly, three resilience indexes: fault recovery time, outrage time and energy loss percentage is established to comprehensively evaluate the resilience of node. Aiming at quantitatively rating the interactive influences of nodes caused by the network connectivity and distribution energy resource (DER) location in a fault event, this paper retains the data information characteristics of multiple random fault resilience, and proposes a node weight calculation method, to comprehensively evaluate the overall resilience of ADN. In a case study, IEEE 33 bus model is taken as an example medium voltage distribution network, and Monte Carlo simulation is used to simulate random faults in that system. From the results, the proposed method can reflect the improvement of resilience after the implementation of different countermeasures, thus the effectiveness of this method can be verified.
A reasonable comprehensive evaluation of distribution network resilience can reflect the ability of distribution network to restore power supplies when random faults occur, which is also helpful to diagnose the performances of different countermeasures for a higher resilience and lower losses. According to the mutual impacts by network nodes under different random faults, one comprehensive evaluation method for the resilience of active distribution networks (ADN) is presented to handle such an uncertainty. Firstly, three resilience indexes: fault recovery time, outrage time and energy loss percentage is established to comprehensively evaluate the resilience of node. Aiming at quantitatively rating the interactive influences of nodes caused by the network connectivity and distribution energy resource (DER) location in a fault event, this paper retains the data information characteristics of multiple random fault resilience, and proposes a node weight calculation method, to comprehensively evaluate the overall resilience of ADN. In a case study, IEEE 33 bus model is taken as an example medium voltage distribution network, and Monte Carlo simulation is used to simulate random faults in that system. From the results, the proposed method can reflect the improvement of resilience after the implementation of different countermeasures, thus the effectiveness of this method can be verified.
2023(1):114-121, DOI: 10.19781/j.issn.1673?9140.2023.01.013
Abstract:
Due to bus bar function of single?ended injection for 10 kV main line, the end?terminal is prone to suffering low voltage problems. Transforming the main line voltage drop constraint into the outlet load constraint can provide great convenience for the safe operation and planning of power grid. Therefore, an estimation method of the first?end load security region boundary is proposed in this paper. Aiming at the numerous station loads along the line, a torque method for rapid estimation of the voltage drop across the main line basing on segmented voltage drop characteristics is proposed. Then the actual station load distribution is equivalent to the characteristic form of balanced distribution along the line with several heavy load points, which is more consistent with the actual situation. Based on the moment method, the relationship between the load at the head end of the line and the voltage drop is obtained, and finally the linearized equation of the safety zone boundary of the head load is obtained. The results of the calculation examples show that the voltage drop analysis and safety zone boundary analysis of the moment method satisfy the engineering accuracy requirements. Based on the boundary of the first?end load safety zone, the load margin of the 10 kV line can be obtained, which is convenient for load controlling and rolling distribution network planning, and has good engineering application value.
Due to bus bar function of single?ended injection for 10 kV main line, the end?terminal is prone to suffering low voltage problems. Transforming the main line voltage drop constraint into the outlet load constraint can provide great convenience for the safe operation and planning of power grid. Therefore, an estimation method of the first?end load security region boundary is proposed in this paper. Aiming at the numerous station loads along the line, a torque method for rapid estimation of the voltage drop across the main line basing on segmented voltage drop characteristics is proposed. Then the actual station load distribution is equivalent to the characteristic form of balanced distribution along the line with several heavy load points, which is more consistent with the actual situation. Based on the moment method, the relationship between the load at the head end of the line and the voltage drop is obtained, and finally the linearized equation of the safety zone boundary of the head load is obtained. The results of the calculation examples show that the voltage drop analysis and safety zone boundary analysis of the moment method satisfy the engineering accuracy requirements. Based on the boundary of the first?end load safety zone, the load margin of the 10 kV line can be obtained, which is convenient for load controlling and rolling distribution network planning, and has good engineering application value.
2023(1):122-129, DOI: 10.19781/j.issn.1673?9140.2023.01.014
Abstract:
The clock?inaccuracy at the load measuring point on the 10 kV line leads to an abnormal line loss rate, while the existing manual methods have the problems of low efficiency and low intelligence. Therefore, based on the fluctuation characteristics of line loss rate curve, a new method for identifying the load types of clock?inaccuracy metering points is proposed to fit the mapping relationship between load type and the clock?inaccuracy line loss rate by Bayesian network (BN). In order to solve the problem of lack of clock?inaccuracy samples, the metering clock deviation modules are respectively set for the load metering points to generate a sample set of clock?inaccuracy line loss rate in the simulation model based on the actual operation data of the line. The fuzzy C?means clustering is then introduced to classify the load according to the shape similarity of the load curve, and the data dimensionality reduction is realized in scenarios with heavy load. Relying on research data from the synchronous line loss management system, the calculation example verifies the feasibility and accuracy of the proposed method. It is shown that the method can realize load type identification of clock?inaccuracy, and provide a reference for quickly locating the abnormal energy meters.
The clock?inaccuracy at the load measuring point on the 10 kV line leads to an abnormal line loss rate, while the existing manual methods have the problems of low efficiency and low intelligence. Therefore, based on the fluctuation characteristics of line loss rate curve, a new method for identifying the load types of clock?inaccuracy metering points is proposed to fit the mapping relationship between load type and the clock?inaccuracy line loss rate by Bayesian network (BN). In order to solve the problem of lack of clock?inaccuracy samples, the metering clock deviation modules are respectively set for the load metering points to generate a sample set of clock?inaccuracy line loss rate in the simulation model based on the actual operation data of the line. The fuzzy C?means clustering is then introduced to classify the load according to the shape similarity of the load curve, and the data dimensionality reduction is realized in scenarios with heavy load. Relying on research data from the synchronous line loss management system, the calculation example verifies the feasibility and accuracy of the proposed method. It is shown that the method can realize load type identification of clock?inaccuracy, and provide a reference for quickly locating the abnormal energy meters.
2023(1):130-137, DOI: 10.19781/j.issn.1673?9140.2023.01.015
Abstract:
Load node classification based on daily load curve is an important part of load modeling. The detailed and appropriate classification results retain the internal characteristics of load nodes and can improve the efficiency of power system simulation calculation. At present, the node clustering method based on artificial intelligence has made rapid progress. However, the overall adaptability to data deep feature extraction is still insufficient. This paper presents the daily load curve clustering method based on the improved deep embedded algorithm, which uses the ability of neural network to effectively extract the deep features of the data. Then, an improved method of increasing the dimension first and then clustering is proposed. Through the comparative analysis of numerical examples, the feasibility of the proposed algorithm and the correctness of the improved dimension reconstruction clustering method are verified.
Load node classification based on daily load curve is an important part of load modeling. The detailed and appropriate classification results retain the internal characteristics of load nodes and can improve the efficiency of power system simulation calculation. At present, the node clustering method based on artificial intelligence has made rapid progress. However, the overall adaptability to data deep feature extraction is still insufficient. This paper presents the daily load curve clustering method based on the improved deep embedded algorithm, which uses the ability of neural network to effectively extract the deep features of the data. Then, an improved method of increasing the dimension first and then clustering is proposed. Through the comparative analysis of numerical examples, the feasibility of the proposed algorithm and the correctness of the improved dimension reconstruction clustering method are verified.
2023(1):138-145, DOI: 10.19781/j.issn.1673?9140.2023.01.016
Abstract:
Load identification is an important part of power system simulation. In order to obtain accurate load identification dynamic parameters, scholars at home and abroad have done a lot of in-depth research on the reasonable construction of identification models. Firstly, on the basis of the traditional load model, two real-time dynamic parameter identification load models based on ambient noise are deduced, which realizes the decoupling of the input data sequence of the measurement and identification data in the calculation of the identification model. At the same time, it avoids the negative impact of the identification of the initial physical quantity redundancy and the iterative amplification of the identification quantity error on the parameter power response capability. Then, the data power response capability of the two measurement and identification models is verified and analyzed from the ambient noise simulation data and the actual measurement data. The results show that the load dynamic parameters measured and identified are applicable to the current power simulation system, indicating that the research can provide a new direction for further research on the identification model and provide a data basis for load controllability.
Load identification is an important part of power system simulation. In order to obtain accurate load identification dynamic parameters, scholars at home and abroad have done a lot of in-depth research on the reasonable construction of identification models. Firstly, on the basis of the traditional load model, two real-time dynamic parameter identification load models based on ambient noise are deduced, which realizes the decoupling of the input data sequence of the measurement and identification data in the calculation of the identification model. At the same time, it avoids the negative impact of the identification of the initial physical quantity redundancy and the iterative amplification of the identification quantity error on the parameter power response capability. Then, the data power response capability of the two measurement and identification models is verified and analyzed from the ambient noise simulation data and the actual measurement data. The results show that the load dynamic parameters measured and identified are applicable to the current power simulation system, indicating that the research can provide a new direction for further research on the identification model and provide a data basis for load controllability.
2023(1):146-153, DOI: 10.19781/j.issn.1673?9140.2023.01.017
Abstract:
Non?intrusive load disaggregation technology can effectively mine the appliance information of customers, which is the basis to carry out interactive customer load response by the grid company. The conventional non?intrusive load disaggregation technology has several drawbacks, such as limited scope of application and low accuracy. In this paper, a non?intrusive load disaggregation model with multiple optimization selection of appliance characteristics is proposed. First, an adaptive sliding data window is designed for appliance operation characteristics to obtain a more complete power segment and to adjust the network input and output dimensions. Second, the appliance features can be extracted and deepened by fusing shallow convolutional neural networks (CNN) with two?layer nested long and short?term memory networks (NLSTM), which is further fed into an improved attention mechanism to obtain the optimum appliance feature sequence by adjusting the feature weights. Finally, experimental analysis on the REDD dataset shows that the multiple selection, deepening and reusing of appliance features can significantly improve the accuracy of load decomposition while reducing training time.
Non?intrusive load disaggregation technology can effectively mine the appliance information of customers, which is the basis to carry out interactive customer load response by the grid company. The conventional non?intrusive load disaggregation technology has several drawbacks, such as limited scope of application and low accuracy. In this paper, a non?intrusive load disaggregation model with multiple optimization selection of appliance characteristics is proposed. First, an adaptive sliding data window is designed for appliance operation characteristics to obtain a more complete power segment and to adjust the network input and output dimensions. Second, the appliance features can be extracted and deepened by fusing shallow convolutional neural networks (CNN) with two?layer nested long and short?term memory networks (NLSTM), which is further fed into an improved attention mechanism to obtain the optimum appliance feature sequence by adjusting the feature weights. Finally, experimental analysis on the REDD dataset shows that the multiple selection, deepening and reusing of appliance features can significantly improve the accuracy of load decomposition while reducing training time.
2023(1):154-163, DOI: 10.19781/j.issn.1673?9140.2023.01.018
Abstract:
In modern DC microgrids, distributed power sources are connected to the common DC bus through power electronic converters. Although the control loop of the converter has good stability margin, the interconnection of multiple converters may affect the microgrid dynamic performance and stability. Therefore, in order to ensure the required dynamic performance of the multi?converter system, a DC bus impedance peak estimation method based on the phase margin of the voltage loop is proposed in this paper. On this basis, an optimized control scheme for the DC bus impedance is further proposed. And through experiments to verify the effectiveness of the proposed control method. First, derive the expression of DC bus impedance based on the voltage control loop gain of the source?side converter; then, through reasonable assumptions, the DC bus impedance peak value is estimated based on the phase margin of the voltage control loop; finally, through the voltage control A sinusoidal signal is injected into the loop to continuously monitor the peak value of the bus impedance. By optimizing the control parameters of the voltage regulator, the peak value of the DC bus impedance is effectively reduced. The experimental results show that the proposed monitoring scheme could reduce the measurement and the calculation burden, and the optimized control scheme improves the stability and dynamic performance of the DC microgrid.
In modern DC microgrids, distributed power sources are connected to the common DC bus through power electronic converters. Although the control loop of the converter has good stability margin, the interconnection of multiple converters may affect the microgrid dynamic performance and stability. Therefore, in order to ensure the required dynamic performance of the multi?converter system, a DC bus impedance peak estimation method based on the phase margin of the voltage loop is proposed in this paper. On this basis, an optimized control scheme for the DC bus impedance is further proposed. And through experiments to verify the effectiveness of the proposed control method. First, derive the expression of DC bus impedance based on the voltage control loop gain of the source?side converter; then, through reasonable assumptions, the DC bus impedance peak value is estimated based on the phase margin of the voltage control loop; finally, through the voltage control A sinusoidal signal is injected into the loop to continuously monitor the peak value of the bus impedance. By optimizing the control parameters of the voltage regulator, the peak value of the DC bus impedance is effectively reduced. The experimental results show that the proposed monitoring scheme could reduce the measurement and the calculation burden, and the optimized control scheme improves the stability and dynamic performance of the DC microgrid.
2023(1):164-170, DOI: 10.19781/j.issn.1673?9140.2023.01.019
Abstract:
To deal with the power fluctuation and the consumption of photovoltaic power generation with the premise of the demand of power supply and heating in northwest China, this paper studies the collaborative control of multi?types of energy storage based on fluctuation parameters by taking the electric?thermal joint micro?network composed of photovoltaic, heat pump and hybrid energy storage as the research object. Firstly, the characteristics and energy conversion mode of electro?thermal joint microgrid are analyzed. Then, a two?layer collaborative control strategy of multi?type energy storage based on fluctuation parameters is designed for the electro?thermal joint micro?grid. In the upper layer, a strategy of multi?type energy storage collaborative power fluctuation suppression is proposed based on the time?scale of power fluctuation and the low?pass filtering method with variable parameters. In the lower layer, an adaptive control strategy for energy transfer of hybrid energy storage is proposed based on the requirement of the power fluctuation suppression and the mechanism of voltage and frequency in microgrid. Finally, the proposed algorithm is verified by simulation. The simulation results show the proposed method can suppress the power fluctuation of renewable energy and can extend the battery life on the premise of reducing the investment cost of electric energy storage effectively.
To deal with the power fluctuation and the consumption of photovoltaic power generation with the premise of the demand of power supply and heating in northwest China, this paper studies the collaborative control of multi?types of energy storage based on fluctuation parameters by taking the electric?thermal joint micro?network composed of photovoltaic, heat pump and hybrid energy storage as the research object. Firstly, the characteristics and energy conversion mode of electro?thermal joint microgrid are analyzed. Then, a two?layer collaborative control strategy of multi?type energy storage based on fluctuation parameters is designed for the electro?thermal joint micro?grid. In the upper layer, a strategy of multi?type energy storage collaborative power fluctuation suppression is proposed based on the time?scale of power fluctuation and the low?pass filtering method with variable parameters. In the lower layer, an adaptive control strategy for energy transfer of hybrid energy storage is proposed based on the requirement of the power fluctuation suppression and the mechanism of voltage and frequency in microgrid. Finally, the proposed algorithm is verified by simulation. The simulation results show the proposed method can suppress the power fluctuation of renewable energy and can extend the battery life on the premise of reducing the investment cost of electric energy storage effectively.
2023(1):171-177, DOI: 10.19781/j.issn.1673?9140.2023.01.020
Abstract:
Aiming at the problem that the recognition accuracy of multiple disturbances is not high under noise interference, a new classification method of power quality disturbances based on deep belief network is proposed. Firstly, the stationary wavelet multi?scale transformation is performed on the power quality disturbance signal, and then the soft threshold function is used to process the estimated wavelet coefficients to reconstruct the original signal, thereby realizing the denoising of the power quality disturbance signal. Moreover, it is further proposed to use the deep belief network to classify and identify the reconstructed single disturbance signal and multiple disturbance signals. The calculation example shows that even under the interference of 20 dB noise, the classification accuracy rate is as high as 93%. The results show that the recognition accuracy of the method is high for 7 kinds of single disturbance and 13 kinds of multiple disturbance signals, which verifies that the method has strong anti?noise interference ability.
Aiming at the problem that the recognition accuracy of multiple disturbances is not high under noise interference, a new classification method of power quality disturbances based on deep belief network is proposed. Firstly, the stationary wavelet multi?scale transformation is performed on the power quality disturbance signal, and then the soft threshold function is used to process the estimated wavelet coefficients to reconstruct the original signal, thereby realizing the denoising of the power quality disturbance signal. Moreover, it is further proposed to use the deep belief network to classify and identify the reconstructed single disturbance signal and multiple disturbance signals. The calculation example shows that even under the interference of 20 dB noise, the classification accuracy rate is as high as 93%. The results show that the recognition accuracy of the method is high for 7 kinds of single disturbance and 13 kinds of multiple disturbance signals, which verifies that the method has strong anti?noise interference ability.
2023(1):178-190, DOI: 10.19781/j.issn.1673?9140.2023.01.021
Abstract:
One of the advantages of the phasor measurement unit (PMU) is to provide synchronous phase angle data. However, due to factors such as abnormal time synchronization, device failures and other factors, some of the measured PMU phase angle data are abnormal, which could affect the PMU application. This paper proposes a method for correcting the time?varying deviation of PMU phase angle difference (PAD) at both ends of the line based on line reactive power loss. Firstly, based on the measured value and estimated value of the line reactive power loss, a single?time PAD deviation estimation model is constructed; Secondly, aiming at the problem that the single?time estimation model is greatly affected by noise, based on the relationship between the voltage PAD and the line parameter, the time?varying deviation estimation model by single?snapshot data is transformed into a constant line parameter estimation model by multi?snapshots data; after estimating the line parameters through the golden section search algorithm, the PAD deviation can be calculated by the PMU amplitude and power data, the estimation and correction of the time?varying PAD deviation at multiple times are realized. The test results of simulated and measured PMU data from a province show that the method could accurately estimate the PAD deviation and has strong anti?noise ability. Compared with the existing methods, this method only needs data under single power flow condition to realize the estimation and correction, and is suitable for the correction of different types of time?varying deviation.
One of the advantages of the phasor measurement unit (PMU) is to provide synchronous phase angle data. However, due to factors such as abnormal time synchronization, device failures and other factors, some of the measured PMU phase angle data are abnormal, which could affect the PMU application. This paper proposes a method for correcting the time?varying deviation of PMU phase angle difference (PAD) at both ends of the line based on line reactive power loss. Firstly, based on the measured value and estimated value of the line reactive power loss, a single?time PAD deviation estimation model is constructed; Secondly, aiming at the problem that the single?time estimation model is greatly affected by noise, based on the relationship between the voltage PAD and the line parameter, the time?varying deviation estimation model by single?snapshot data is transformed into a constant line parameter estimation model by multi?snapshots data; after estimating the line parameters through the golden section search algorithm, the PAD deviation can be calculated by the PMU amplitude and power data, the estimation and correction of the time?varying PAD deviation at multiple times are realized. The test results of simulated and measured PMU data from a province show that the method could accurately estimate the PAD deviation and has strong anti?noise ability. Compared with the existing methods, this method only needs data under single power flow condition to realize the estimation and correction, and is suitable for the correction of different types of time?varying deviation.
2023(1):191-200, DOI: 10.19781/j.issn.1673?9140.2023.01.022
Abstract:
The uncertainty of new energy power generation poses a great challenge to the transmission system. Since the transmission cable has a certain overload capacity, it can be overloaded for a short time under the premise that the temperature does not exceed the limit value. A method of making full use of the overload level of the cable is proposed to improve the transmission capacity of the cable to new energy power generation in a short time. This method firstly uses the finite element method to calculate the cable temperature field distribution, establishes the allowable overload running time of the line and analyzes its influencing factors. Then the improved BP neural network algorithm is introduced to predict the overload time in combination with the actual power generation output curve. The results show that the BP neural network model has high accuracy and can be applied to evaluate the cable limit transmission capacity and provide rapid support for dispatching decisions.
The uncertainty of new energy power generation poses a great challenge to the transmission system. Since the transmission cable has a certain overload capacity, it can be overloaded for a short time under the premise that the temperature does not exceed the limit value. A method of making full use of the overload level of the cable is proposed to improve the transmission capacity of the cable to new energy power generation in a short time. This method firstly uses the finite element method to calculate the cable temperature field distribution, establishes the allowable overload running time of the line and analyzes its influencing factors. Then the improved BP neural network algorithm is introduced to predict the overload time in combination with the actual power generation output curve. The results show that the BP neural network model has high accuracy and can be applied to evaluate the cable limit transmission capacity and provide rapid support for dispatching decisions.
2023(1):201-209, DOI: 10.19781/j.issn.1673?9140.2023.01.023
Abstract:
With the increase of electricity demand, the heavy overload of distribution network lines during the peak period of electricity consumption becomes more serious, which increases the potential threats on the safety of grid operation. The short?term forecast of the heavy overload state of distribution lines is of great significance for rationally arranging the operation mode, for dispatch management, and for the safety operation of the line during peak load periods. This paper proposes a short?term forecast method for the heavy overload state of lines and a prediction model that CNN?GRU hybrid neural network with Attention mechanism. The historical load rate of lines with high auto?correlation and meteorological factors are combined as the input features, which is further used to extract the valid features by the CNN. The GRU neural network is utilized to analyze and predict time series data. By using the Attention mechanism to reassign corresponding weights, the load rate regression prediction result can be outputed，which can be finally converted into the load level according to the load level division standard. The method in this paper is performed on a 10kV line in a certain district of Shanghai. The experimental results show that this prediction method is more suitable for line heavy overload prediction than the method using the classification prediction model with the same model structure but with load level as input.
With the increase of electricity demand, the heavy overload of distribution network lines during the peak period of electricity consumption becomes more serious, which increases the potential threats on the safety of grid operation. The short?term forecast of the heavy overload state of distribution lines is of great significance for rationally arranging the operation mode, for dispatch management, and for the safety operation of the line during peak load periods. This paper proposes a short?term forecast method for the heavy overload state of lines and a prediction model that CNN?GRU hybrid neural network with Attention mechanism. The historical load rate of lines with high auto?correlation and meteorological factors are combined as the input features, which is further used to extract the valid features by the CNN. The GRU neural network is utilized to analyze and predict time series data. By using the Attention mechanism to reassign corresponding weights, the load rate regression prediction result can be outputed，which can be finally converted into the load level according to the load level division standard. The method in this paper is performed on a 10kV line in a certain district of Shanghai. The experimental results show that this prediction method is more suitable for line heavy overload prediction than the method using the classification prediction model with the same model structure but with load level as input.
2023(1):210-217, DOI: 10.19781/j.issn.1673?9140.2023.01.024
Abstract:
The safe operation of transmission lines is an important basis for ensuring stable transmission of electric energy, and the safety is greatly affected by meteorological factors. In order to evaluate and improve the risk early warning capability in the transmission system, this paper proposes a transmission line safety evaluation model that takes into account meteorological factors. Firstly, according to the characteristics of the transmission line architecture, an evaluation index system reflecting the operation status of the transmission line is constructed. At the same time, a new graph model weighting method is proposed based on the principle of graph theory to overcome the human subjectivity factor disadvantages in the weighting of the traditional matter?element extension model. Secondly, based on the matter?element extension theory, the comprehensive risk matter?element and safety rating of transmission lines are constructed, and the risk safety assessment and dynamic management model of transmission lines considering meteorological factors are established. Finally, taking a certain region as an example to study the operation risk of its transmission lines, the analysis results verify the scientificity and practicability of the transmission line safety assessment model.
The safe operation of transmission lines is an important basis for ensuring stable transmission of electric energy, and the safety is greatly affected by meteorological factors. In order to evaluate and improve the risk early warning capability in the transmission system, this paper proposes a transmission line safety evaluation model that takes into account meteorological factors. Firstly, according to the characteristics of the transmission line architecture, an evaluation index system reflecting the operation status of the transmission line is constructed. At the same time, a new graph model weighting method is proposed based on the principle of graph theory to overcome the human subjectivity factor disadvantages in the weighting of the traditional matter?element extension model. Secondly, based on the matter?element extension theory, the comprehensive risk matter?element and safety rating of transmission lines are constructed, and the risk safety assessment and dynamic management model of transmission lines considering meteorological factors are established. Finally, taking a certain region as an example to study the operation risk of its transmission lines, the analysis results verify the scientificity and practicability of the transmission line safety assessment model.
2023(1):218-225, DOI: 10.19781/j.issn.1673?9140.2023.01.025
Abstract:
Reliability evaluation based on the failure rate data is an important basis for the health status management and maintenance of smart meters. However, the small sample characteristics of outliers and failure rates limit the evaluation performance of traditional smart energy meter reliability prediction models. Therefore, a prediction model of smart meter failure rate under multi?environment stress based on weighted local outlier factor and Gaussian process regression is proposed in this paper. Firstly, a weighted local outlier factor is employed with the model to identify and then delete potential outliers in failure rate data sets; then, different kernel functions are selected to match the characteristics of multiple stress inputs in typical environments, and choose the best one. Finally, the interval change of the 95% confidence level of the failure rate is predicted by the posterior distribution of the Gaussian process, and the interval reliability is obtained based on this. Case analysis of fault samples of smart meters in two typical environmental areas shows that the proposed model could effectively predict the trend of failure rate of smart meters under multi?environmental stress, and could accurately solve its reliability.
Reliability evaluation based on the failure rate data is an important basis for the health status management and maintenance of smart meters. However, the small sample characteristics of outliers and failure rates limit the evaluation performance of traditional smart energy meter reliability prediction models. Therefore, a prediction model of smart meter failure rate under multi?environment stress based on weighted local outlier factor and Gaussian process regression is proposed in this paper. Firstly, a weighted local outlier factor is employed with the model to identify and then delete potential outliers in failure rate data sets; then, different kernel functions are selected to match the characteristics of multiple stress inputs in typical environments, and choose the best one. Finally, the interval change of the 95% confidence level of the failure rate is predicted by the posterior distribution of the Gaussian process, and the interval reliability is obtained based on this. Case analysis of fault samples of smart meters in two typical environmental areas shows that the proposed model could effectively predict the trend of failure rate of smart meters under multi?environmental stress, and could accurately solve its reliability.
2023(1):226-234, DOI: 10.19781/j.issn.1673?9140.2023.01.026
Abstract:
This paper addresses the difficulty of the accurately detecting electricity theft in complex grid environment and proposes a multi?category electricity theft detection method based on CNN?LSTM hybrid model. Firstly, the excellent feature abstraction ability of convolutional neural networks (CNN) is utilized to extract the non?periodic local features of one?dimensional electricity consumption data. Then, the long short?term memory (LSTM) is adopted to capture the correlation between daily power consumption data and extract periodic power consumption features to establish feature fusion layer network. After that, the feature vectors extracted by CNN and LSTM are horizontally splicing to obtain a new fusion vector. Based on this, the accurate detection of multiple types of electric theft behavior are realized. Experimental results show that the proposed method can accurately identify multiple types of electric theft behavior, and the detection results are more comprehensive and accurate than the existing detection methods.
This paper addresses the difficulty of the accurately detecting electricity theft in complex grid environment and proposes a multi?category electricity theft detection method based on CNN?LSTM hybrid model. Firstly, the excellent feature abstraction ability of convolutional neural networks (CNN) is utilized to extract the non?periodic local features of one?dimensional electricity consumption data. Then, the long short?term memory (LSTM) is adopted to capture the correlation between daily power consumption data and extract periodic power consumption features to establish feature fusion layer network. After that, the feature vectors extracted by CNN and LSTM are horizontally splicing to obtain a new fusion vector. Based on this, the accurate detection of multiple types of electric theft behavior are realized. Experimental results show that the proposed method can accurately identify multiple types of electric theft behavior, and the detection results are more comprehensive and accurate than the existing detection methods.
2023(1):235-242, DOI: 10.19781/j.issn.1673?9140.2023.01.027
Abstract:
The complex electromagnetic environment around the high-voltage transmission line affects the steady operation of the patrol UAV directly, and further affects the evaluation results of the patrol inspection by ground operators. In order to ensure the reliability of UAV in the harsh electromagnetic environment, the electromagnetic environment around UAV is simulated. Based on the coupling path of interference electromagnetic wave, the electric field coupling model and the magnetic field coupling model are constructed respectively. The coupling between the internal electrical structure of UAV and the high-voltage transmission line is analyzed to determine the disturbed target. Based on the generation of the interference source and the electromagnetic coupling path, the electromagnetic compatibility optimization of the UAV is carried out. The electromagnetic shielding is used to weaken the electromagnetic interference to the internal electrical structure and sensitive components of the UAV, so that the electromagnetic compatibility performance of the UAV is improved, and the operation stability of the patrol UAV is guaranteed.
The complex electromagnetic environment around the high-voltage transmission line affects the steady operation of the patrol UAV directly, and further affects the evaluation results of the patrol inspection by ground operators. In order to ensure the reliability of UAV in the harsh electromagnetic environment, the electromagnetic environment around UAV is simulated. Based on the coupling path of interference electromagnetic wave, the electric field coupling model and the magnetic field coupling model are constructed respectively. The coupling between the internal electrical structure of UAV and the high-voltage transmission line is analyzed to determine the disturbed target. Based on the generation of the interference source and the electromagnetic coupling path, the electromagnetic compatibility optimization of the UAV is carried out. The electromagnetic shielding is used to weaken the electromagnetic interference to the internal electrical structure and sensitive components of the UAV, so that the electromagnetic compatibility performance of the UAV is improved, and the operation stability of the patrol UAV is guaranteed.
2023(1):243-248, DOI: 10.19781/j.issn.1673?9140.2023.01.028
Abstract:
In order to analyze the impulse characteristics of tower grounding device under continuous lightning impulse, continuous impact tests of typical grounding bodies with different soils, materials and shapes are carried out. Under continuous pulse impact, with the increase of impulse time interval, the secondary impact grounding resistance increases from the lower value at soil breakdown to the single pulse impact grounding resistance. However, within a certain time interval, the secondary impulse grounding resistance of grounding device in soil with less water content is significantly greater than that of single pulse impulse. The secondary impulse grounding resistances of grounding bodies with different shapes and materials are different. In the tower grounding design, the increase of impulse grounding resistance under continuous lightning impulse needs to be considered, and the material and shape of grounding body should be comprehensively considered. Based on the experimental results, the ATP Draw simulation modeling method of tower grounding system under continuous lightning impulse is proposed. This method achieves good effect when simulating the spark effect of impulse grounding and the recovery process of soil resistivity after soil breakdown.
In order to analyze the impulse characteristics of tower grounding device under continuous lightning impulse, continuous impact tests of typical grounding bodies with different soils, materials and shapes are carried out. Under continuous pulse impact, with the increase of impulse time interval, the secondary impact grounding resistance increases from the lower value at soil breakdown to the single pulse impact grounding resistance. However, within a certain time interval, the secondary impulse grounding resistance of grounding device in soil with less water content is significantly greater than that of single pulse impulse. The secondary impulse grounding resistances of grounding bodies with different shapes and materials are different. In the tower grounding design, the increase of impulse grounding resistance under continuous lightning impulse needs to be considered, and the material and shape of grounding body should be comprehensively considered. Based on the experimental results, the ATP Draw simulation modeling method of tower grounding system under continuous lightning impulse is proposed. This method achieves good effect when simulating the spark effect of impulse grounding and the recovery process of soil resistivity after soil breakdown.
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,35(4):3-12, DOI: 10.19781/j.issn.16739140.2020.04.001
Abstract:
The disordered planning and unreasonable allocation of electric vehicle charging stations have a serious impact on the safty，stability and economy of the distribution network operation．To solve this problem, this paper constructs an optimal planning model of electric vehicle charging stations based on the voltage stability index of distribution network．The model not only could balance the construction investment of charging stations，the economic operation of distribution system and the quality of power supply，but also take full account of the demand and convenience of the electric vehicle charging．The improved adaptive particle swarm optimization (APSO) algorithm with fast speed and high accuracy is adopted to solve the nolinear optimization problem with multiple constraints. Finally, the simulation results based on IEEE33bus system show the effectiveness of the proposed method.
The disordered planning and unreasonable allocation of electric vehicle charging stations have a serious impact on the safty，stability and economy of the distribution network operation．To solve this problem, this paper constructs an optimal planning model of electric vehicle charging stations based on the voltage stability index of distribution network．The model not only could balance the construction investment of charging stations，the economic operation of distribution system and the quality of power supply，but also take full account of the demand and convenience of the electric vehicle charging．The improved adaptive particle swarm optimization (APSO) algorithm with fast speed and high accuracy is adopted to solve the nolinear optimization problem with multiple constraints. Finally, the simulation results based on IEEE33bus system show the effectiveness of the proposed method.
,35(4):91-98, DOI: 10.19781/j.issn.16739140.2020.04.012
Abstract:
Windthermal bundling external power transmission use thermal power to suppress the fluctuation of wind power and improve the utilization rate of the line. It is an important way to absorb wind power on a large scale. Therefore, the choice of windthermal bundling external power transmission lines and supporting thermal power is crucial. And the transmission capacity of the external power transmission line is related to its cross section and environmental temperature. Considering the line heat capacity or namely the influence of environmental temperature, this paper proposes a method to optimize transmission line crosssection and thermal power capacity of windthermal bundling external power. This method comprehensively considers the impact of wind power and thermal power income, total cost of thermal power, line investment cost, and wind curtailment cost on social benefits. The calculation example shows that this method can give full play to the transmission capacity of the line and increase social benefits compared with the method without considering the thermal load capacity.
Windthermal bundling external power transmission use thermal power to suppress the fluctuation of wind power and improve the utilization rate of the line. It is an important way to absorb wind power on a large scale. Therefore, the choice of windthermal bundling external power transmission lines and supporting thermal power is crucial. And the transmission capacity of the external power transmission line is related to its cross section and environmental temperature. Considering the line heat capacity or namely the influence of environmental temperature, this paper proposes a method to optimize transmission line crosssection and thermal power capacity of windthermal bundling external power. This method comprehensively considers the impact of wind power and thermal power income, total cost of thermal power, line investment cost, and wind curtailment cost on social benefits. The calculation example shows that this method can give full play to the transmission capacity of the line and increase social benefits compared with the method without considering the thermal load capacity.
(4):124-131, DOI: 10.19781/j.issn.1673-9140.2021.04.016
Abstract:
Travel temperature directly affects the specific energy consumption of electric vehicle through various interferences, resulting in the difference in charging power demand at different temperatures. According to the statistical principle, under the support of a large number of samples, the least squares method to obtain the specific relationship between the electric power consumption per km of electric vehicles and the travel temperatures in this paper. Then a power calculation model for electric vehicles considering the influence of travel temperature is proposed. The distribution network of a certain residential district in Beijing is taken as an example. Monte Carlo method is used to simulate the specific difference of electric vehicle charging load under different seasons (temperatures). The different impacts of EV load on the regional power grid in different seasons are analyzed to provide a new seasonal scheduling idea for the orderly control of EV charging behavior in the future.
Travel temperature directly affects the specific energy consumption of electric vehicle through various interferences, resulting in the difference in charging power demand at different temperatures. According to the statistical principle, under the support of a large number of samples, the least squares method to obtain the specific relationship between the electric power consumption per km of electric vehicles and the travel temperatures in this paper. Then a power calculation model for electric vehicles considering the influence of travel temperature is proposed. The distribution network of a certain residential district in Beijing is taken as an example. Monte Carlo method is used to simulate the specific difference of electric vehicle charging load under different seasons (temperatures). The different impacts of EV load on the regional power grid in different seasons are analyzed to provide a new seasonal scheduling idea for the orderly control of EV charging behavior in the future.
(4):116-123, DOI: 10.19781/j.issn.1673-9140.2021.04.015
Abstract:
Power grid operation section is an important measure in power system operation control. Faced with the numerous intelligent generation methods of grid operation sections at present, how to make a reasonable choice has become an important content of the research in the field of online generation algorithms for grid operation sections. To solve this problem, a dynamic detection method for power grid operation section based on Qlearning algorithm is proposed. The main feature of this method is that the Qlearning agent is trained, and the grid operation section generation method is dynamically selected according to the grid operation characteristics, so as to make full use of the algorithm advantages of different generation methods in different scenarios. Finally, a case study based on the actual data in a certain provincial power grid shows that the dynamic detection method can improve the accuracy of the generated results by optimizing the selection of the detection algorithms in different scenarios. For the applied sample set, the method could improve the accuracy by nearly 5.2%.
Power grid operation section is an important measure in power system operation control. Faced with the numerous intelligent generation methods of grid operation sections at present, how to make a reasonable choice has become an important content of the research in the field of online generation algorithms for grid operation sections. To solve this problem, a dynamic detection method for power grid operation section based on Qlearning algorithm is proposed. The main feature of this method is that the Qlearning agent is trained, and the grid operation section generation method is dynamically selected according to the grid operation characteristics, so as to make full use of the algorithm advantages of different generation methods in different scenarios. Finally, a case study based on the actual data in a certain provincial power grid shows that the dynamic detection method can improve the accuracy of the generated results by optimizing the selection of the detection algorithms in different scenarios. For the applied sample set, the method could improve the accuracy by nearly 5.2%.
,35(4):161-168, DOI: 10.19781/j.issn.16739140.2020.04.022
Abstract:
Due to the lack of secondary cable circuit model, the information model of intelligent substation is incomplete. It is not only harm to intelligent substation comprehensive online monitoring and operational diagnosis, but also infect the development of smart substation Informationization. In this paper, a modeling method for secondary cable loops in the intelligent substation is proposed firstly. Then, the secondary cable loop configuration process is designed and the secondary cable loop model structure is introduced. The multidimensional visual display of secondary subcircuit for the intelligent substation is realized by the secondary cable loop model file visualization tool. Finally, the secondary cable loop information model is associated with the physical model by mapping the information model in the SCD file to the secondary cable loop model. The online monitoring and fault location of the secondary cable loop of the intelligent substation is realized successfully.
Due to the lack of secondary cable circuit model, the information model of intelligent substation is incomplete. It is not only harm to intelligent substation comprehensive online monitoring and operational diagnosis, but also infect the development of smart substation Informationization. In this paper, a modeling method for secondary cable loops in the intelligent substation is proposed firstly. Then, the secondary cable loop configuration process is designed and the secondary cable loop model structure is introduced. The multidimensional visual display of secondary subcircuit for the intelligent substation is realized by the secondary cable loop model file visualization tool. Finally, the secondary cable loop information model is associated with the physical model by mapping the information model in the SCD file to the secondary cable loop model. The online monitoring and fault location of the secondary cable loop of the intelligent substation is realized successfully.
,35(6):157-162, DOI: 10.19781/j.issn.16739140.2020.06.021
Abstract:
The parameters of Siemens PSS3B power system stabilizer are difficult to tune, therefore, a parameter tuning method is proposed in this paper. Firstly, the PSS3B feedback transfer function structure is equivalently converted into a series transfer function structure by analyzing the transfer function structure of the power system stabilizer. Then the phase compensation parameters of transfer function is adjusted based on the phase compensation principle. Finally, the gain coefficient of the power system stabilizer is adjusted by checking the damping ratio corresponding to the dominant characteristic root of the closedloop transfer function and the oscillation frequency. After the adjustment, the PSS3B power system stabilizer has a good suppression effect on the lowfrequency oscillation of active power, which verifies the effectiveness of the method.
The parameters of Siemens PSS3B power system stabilizer are difficult to tune, therefore, a parameter tuning method is proposed in this paper. Firstly, the PSS3B feedback transfer function structure is equivalently converted into a series transfer function structure by analyzing the transfer function structure of the power system stabilizer. Then the phase compensation parameters of transfer function is adjusted based on the phase compensation principle. Finally, the gain coefficient of the power system stabilizer is adjusted by checking the damping ratio corresponding to the dominant characteristic root of the closedloop transfer function and the oscillation frequency. After the adjustment, the PSS3B power system stabilizer has a good suppression effect on the lowfrequency oscillation of active power, which verifies the effectiveness of the method.
,35(4):20-26, DOI: 10.19781/j.issn.16739140.2020.04.003
Abstract:
The accuracy of the impedance model of the converter station directly affects the small interference stability analysis of the flexible DC transmission system. However, the more accurate the model, the higher the order, which increases the complexity of the analysis. To analyze the influence of the phaselocked loop on the impedance characteristics of the converter station, we firstly establish the admittance matrix of the AC side of the converter station under the two conditions of dq coordinates with and without consideration of the phaselocked loop, and then establish the same order and mirror admittance of the converter station at the static coordinates. By comparing and not considering the input admittance of the phaselocked loop, it is concluded that the influence of the phaselocked loop on the input admittance value is directly related to the cutoff frequency of the phaselocked loop transfer function. Finally, the simulation model is established in PSCAD software. We use the signal injection method to obtain the homologous and mirror admittance of the converter station to verify the correctness of the theoretical analysis.
The accuracy of the impedance model of the converter station directly affects the small interference stability analysis of the flexible DC transmission system. However, the more accurate the model, the higher the order, which increases the complexity of the analysis. To analyze the influence of the phaselocked loop on the impedance characteristics of the converter station, we firstly establish the admittance matrix of the AC side of the converter station under the two conditions of dq coordinates with and without consideration of the phaselocked loop, and then establish the same order and mirror admittance of the converter station at the static coordinates. By comparing and not considering the input admittance of the phaselocked loop, it is concluded that the influence of the phaselocked loop on the input admittance value is directly related to the cutoff frequency of the phaselocked loop transfer function. Finally, the simulation model is established in PSCAD software. We use the signal injection method to obtain the homologous and mirror admittance of the converter station to verify the correctness of the theoretical analysis.
,35(4):128-132, DOI: 10.19781/j.issn.16739140.2020.04.017
Abstract:
The LLC resonant converter can achieve softswitching while it operates in highfrequency and then improves the power density and efficiency of power supply. The fundamental approximation and mode analysis are two classic analysis methods of LLC resonant converter, but the comparative studies in the voltage gain accuracy, efficiency and application is not intensively discussed. On this background, the principle of the above methods is illustrated firstly. Then, the operation mode of LLC resonant converter is analyzed in PSIM simulation environment. Based on the operation modes, the voltage gain accuracy of the two methods is compared in simulation. Finally, the resonant parameters are selected based on the peak voltage gain, and a 1.5 kW/28 V prototype is set up. The experimental results show that actual gain is higher than the gain curve based on FHA 10% to 15% below the resonant zone, and have high accordance with the voltage gain based on the mode analysis in whole frequency range. And the iterative parameters based on mode analysis have higher efficiency with the experimental prototype.
The LLC resonant converter can achieve softswitching while it operates in highfrequency and then improves the power density and efficiency of power supply. The fundamental approximation and mode analysis are two classic analysis methods of LLC resonant converter, but the comparative studies in the voltage gain accuracy, efficiency and application is not intensively discussed. On this background, the principle of the above methods is illustrated firstly. Then, the operation mode of LLC resonant converter is analyzed in PSIM simulation environment. Based on the operation modes, the voltage gain accuracy of the two methods is compared in simulation. Finally, the resonant parameters are selected based on the peak voltage gain, and a 1.5 kW/28 V prototype is set up. The experimental results show that actual gain is higher than the gain curve based on FHA 10% to 15% below the resonant zone, and have high accordance with the voltage gain based on the mode analysis in whole frequency range. And the iterative parameters based on mode analysis have higher efficiency with the experimental prototype.
(1):79-86, DOI: 10.19781/j.issn.16739140.2021.01.009
Abstract:
The home microgrid contains uncertain power sources and loads such as photovoltaics and electric vehicles. The lack of a reasonable energy management strategy can easily lead to instability of the household microgrid.In the V2G system, a model that simultaneously considers electric vehicles, houses, batteries, and renewable energy power generation systems is constructed. Under the restriction of electric vehicle charging and discharging strategy, a power production planning for the residence and for the microturbine is determined.Then a dynamic energy management is proposed. Finally, the proposed home microgrid energy management method is verified by simulation. By comparing the equivalent load and energy storage operation of the microgrid under the conditions of random charging, orderly charging and discharging of electric vehicles,the feasibility of proposed method is verified when the charging state of the battery is restricted.
The home microgrid contains uncertain power sources and loads such as photovoltaics and electric vehicles. The lack of a reasonable energy management strategy can easily lead to instability of the household microgrid.In the V2G system, a model that simultaneously considers electric vehicles, houses, batteries, and renewable energy power generation systems is constructed. Under the restriction of electric vehicle charging and discharging strategy, a power production planning for the residence and for the microturbine is determined.Then a dynamic energy management is proposed. Finally, the proposed home microgrid energy management method is verified by simulation. By comparing the equivalent load and energy storage operation of the microgrid under the conditions of random charging, orderly charging and discharging of electric vehicles,the feasibility of proposed method is verified when the charging state of the battery is restricted.
,35(4):42-48, DOI: 10.19781/j.issn.16739140.2020.04.006
Abstract:
The effect of the oscillating wave on the interfacial and internal defects of cable from the perspective of the electric field is studied in order to understand the test results of the oscillating wave voltage method for different defects in cables. Firstly, an oscillating wave test platform is set up to partial discharge tests the artificial defective models including longitudinal knife defects and external semiconductor lap defects. Then, the excitation characteristics of oscillation wave are analyzed primarily by PDIV and PRPD. Furthermore, the electric field distribution of cables with defects are simulated by utilizing a finite element simulation software in threedimension. Artificial defects with different sizes are fabricated to represent the diversity of the defect site and the characteristics of defective discharges are explained by the electric field distortion at the defects. Experimental and simulation results show that: it is hard to detect the internal defects due to the filling of hard grease by using the oscillation wave voltage method, whereas interfacial defects of poor connection of outer semiconductor has better characterization results.
The effect of the oscillating wave on the interfacial and internal defects of cable from the perspective of the electric field is studied in order to understand the test results of the oscillating wave voltage method for different defects in cables. Firstly, an oscillating wave test platform is set up to partial discharge tests the artificial defective models including longitudinal knife defects and external semiconductor lap defects. Then, the excitation characteristics of oscillation wave are analyzed primarily by PDIV and PRPD. Furthermore, the electric field distribution of cables with defects are simulated by utilizing a finite element simulation software in threedimension. Artificial defects with different sizes are fabricated to represent the diversity of the defect site and the characteristics of defective discharges are explained by the electric field distortion at the defects. Experimental and simulation results show that: it is hard to detect the internal defects due to the filling of hard grease by using the oscillation wave voltage method, whereas interfacial defects of poor connection of outer semiconductor has better characterization results.
,35(4):13-19, DOI: 10.19781/j.issn.16739140.2020.04.002
Abstract:
With the construction of smart grid, power companies gradually use unmanned aerial vehicles (UAV) to replace manual inspection of transmission lines. This paper proposes a method for processing aerial images of transmission line insulators captured by UAV. Firstly, the threshold and range of RGB components in the color model are used to segment the target and background areas. Secondly, mathematical morphology and nonoverlapping window texture features are applied to roughly mark the target area. Finally, a minimum circumscribed horizontal rectangular frame is generated. Then the texture features of all the patterns within the minimum circumscribed horizontal rectangular frame are identified to locate the minimum horizontal rectangular area of the aerial image of the insulator string. In the end, we use two images to verify the algorithm and compare with the algorithms in the literature. The results show that the algorithm proposed in this paper can better identify the position of insulator strings.
With the construction of smart grid, power companies gradually use unmanned aerial vehicles (UAV) to replace manual inspection of transmission lines. This paper proposes a method for processing aerial images of transmission line insulators captured by UAV. Firstly, the threshold and range of RGB components in the color model are used to segment the target and background areas. Secondly, mathematical morphology and nonoverlapping window texture features are applied to roughly mark the target area. Finally, a minimum circumscribed horizontal rectangular frame is generated. Then the texture features of all the patterns within the minimum circumscribed horizontal rectangular frame are identified to locate the minimum horizontal rectangular area of the aerial image of the insulator string. In the end, we use two images to verify the algorithm and compare with the algorithms in the literature. The results show that the algorithm proposed in this paper can better identify the position of insulator strings.
,35(4):107-113, DOI: 10.19781/j.issn.16739140.2020.04.014
Abstract:
In the microgrid with the energy storage system as the main power source, the output characteristics of the energy storage system directly affect the power quality of the microgrid. When the output of the energy storage system can not be adjusted quickly, the problem occurs that the power quality of the microgrid does not meet the requirements. The traditional V/f control strategy adopts the reactivevoltage droop control strategy. When the island is running, there is a voltage offset, which will affect the overall power quality of the microgrid. And in the droop control, the droop coefficient parameter selection inevitably leads to misadjustment. In order to solve these problems, this paper discusses the relationship between the DC and AC power of the inverter. Based on the implementation of the control strategy of the energy storage inverter, DC current control is added to solve the problem of voltage offset and misadjustment to achieve nonamplitude difference control of microgrid. Finally, the PSCAD software is used to build the wind and solar storage microgrid model for simulation and verification, proving the effectiveness of the control strategy.
In the microgrid with the energy storage system as the main power source, the output characteristics of the energy storage system directly affect the power quality of the microgrid. When the output of the energy storage system can not be adjusted quickly, the problem occurs that the power quality of the microgrid does not meet the requirements. The traditional V/f control strategy adopts the reactivevoltage droop control strategy. When the island is running, there is a voltage offset, which will affect the overall power quality of the microgrid. And in the droop control, the droop coefficient parameter selection inevitably leads to misadjustment. In order to solve these problems, this paper discusses the relationship between the DC and AC power of the inverter. Based on the implementation of the control strategy of the energy storage inverter, DC current control is added to solve the problem of voltage offset and misadjustment to achieve nonamplitude difference control of microgrid. Finally, the PSCAD software is used to build the wind and solar storage microgrid model for simulation and verification, proving the effectiveness of the control strategy.
,35(4):49-57, DOI: 10.19781/j.issn.16739140.2020.04.007
Abstract:
Singlephasetoground fault section location in small current grounded system is generally realized by a master station comprehensively calculating several different electrical quantities. This method is unsuitable for distribution networks with complex structures since its large workload and complicated calculations easily brings large errors. Under the background, a fault location method of distribution network based on threephase current amplitude analysis is proposed. In views of the analysis on the threephase current of singlephasetoground fault in small current grounded system, the current changes of the two nonfault phases on the fault path are approximately equal and less than the current change of fault phase. The phase current change of the two nonfault phases on the nonfault path are approximately equal and also equal to the current change of fault phase. By calculating the amplitude change of threephase current before and after fault and setting the criterion, the fault phase can be selected and the fault section can be located. ATP simulation results verify the applicability in neutral ungrounded system and neutral point grounding system via arc suppression coil. The local location of fault is realized successfully. The proposed method is simple in location criterion and reduces the computational complexity of the master station.
Singlephasetoground fault section location in small current grounded system is generally realized by a master station comprehensively calculating several different electrical quantities. This method is unsuitable for distribution networks with complex structures since its large workload and complicated calculations easily brings large errors. Under the background, a fault location method of distribution network based on threephase current amplitude analysis is proposed. In views of the analysis on the threephase current of singlephasetoground fault in small current grounded system, the current changes of the two nonfault phases on the fault path are approximately equal and less than the current change of fault phase. The phase current change of the two nonfault phases on the nonfault path are approximately equal and also equal to the current change of fault phase. By calculating the amplitude change of threephase current before and after fault and setting the criterion, the fault phase can be selected and the fault section can be located. ATP simulation results verify the applicability in neutral ungrounded system and neutral point grounding system via arc suppression coil. The local location of fault is realized successfully. The proposed method is simple in location criterion and reduces the computational complexity of the master station.
,35(4):58-65, DOI: 10.19781/j.issn.16739140.2020.04.008
Abstract:
In order to improve the reliability of lineselection and faultlocation for singlephase grounding failures in distribution network, the current waveform at different stages were studied and stimulated. Firstly, in terms of the summarized common features of current waveforms during their development, the incremental current of the subtransient sawtooth wave in the grounding phase and the incremental current in the sound phase are selected as the criterion signal sources for the fault location of the insulation loss in distribution networks. The general characteristics of all grounding currents reflected by the saw tooth currents are analyzed. Then, the difference of waveform characteristics is analyzed between singlephase grounding current and operationinduced disturbance currents. It provides a criterion for identifying the authenticity of singlephase grounding failure. The line selection and location method are proposed for the singlephase grounding including the insulation loss to avoid misidentification. Finally, the proposed method is applied to the grounding locator in a low voltage distribution network model for verification.
In order to improve the reliability of lineselection and faultlocation for singlephase grounding failures in distribution network, the current waveform at different stages were studied and stimulated. Firstly, in terms of the summarized common features of current waveforms during their development, the incremental current of the subtransient sawtooth wave in the grounding phase and the incremental current in the sound phase are selected as the criterion signal sources for the fault location of the insulation loss in distribution networks. The general characteristics of all grounding currents reflected by the saw tooth currents are analyzed. Then, the difference of waveform characteristics is analyzed between singlephase grounding current and operationinduced disturbance currents. It provides a criterion for identifying the authenticity of singlephase grounding failure. The line selection and location method are proposed for the singlephase grounding including the insulation loss to avoid misidentification. Finally, the proposed method is applied to the grounding locator in a low voltage distribution network model for verification.
,35(4):33-41, DOI: 10.19781/j.issn.16739140.2020.04.005
Abstract:
In order to study the relationship between the aging and the polarization/depolarization current (PDC) of transformer oilpaper, a prediction method of transformer oilpaper aging is presented based on the BP neural network with the chicken swarm optimization algorithm. Firstly, the relationship between extended Debye parameters and the polymerization degree (DP) of oilpaper is examined. With the variation of atmosphere temperature, PDC changes and it leads to a failure of extended Debye model to response the aging status of oilpaper. In order to eliminate the error caused by temperature, a BP neural network is trained through fitting PDC and DP of oilpaper. Then, in view of the slow convergence and low efficiency of BP neural network, the chickens swarm algorithm is utilized to optimize weights and threshold of the BP neural network. After the optimization, the network convergence is speeded up and the possibility of trapping into local optimal is also reduced. Finally, the simulation results show that the environment influences to polarization/depolarization current are reduced and the oilpaper polymerization degree is predicted accurately.
In order to study the relationship between the aging and the polarization/depolarization current (PDC) of transformer oilpaper, a prediction method of transformer oilpaper aging is presented based on the BP neural network with the chicken swarm optimization algorithm. Firstly, the relationship between extended Debye parameters and the polymerization degree (DP) of oilpaper is examined. With the variation of atmosphere temperature, PDC changes and it leads to a failure of extended Debye model to response the aging status of oilpaper. In order to eliminate the error caused by temperature, a BP neural network is trained through fitting PDC and DP of oilpaper. Then, in view of the slow convergence and low efficiency of BP neural network, the chickens swarm algorithm is utilized to optimize weights and threshold of the BP neural network. After the optimization, the network convergence is speeded up and the possibility of trapping into local optimal is also reduced. Finally, the simulation results show that the environment influences to polarization/depolarization current are reduced and the oilpaper polymerization degree is predicted accurately.
,35(4):147-153, DOI: 10.19781/j.issn.16739140.2020.04.020
Abstract:
When itoccurs load mutation in cophase power supply system, conventional detection method in detecting the fundamental active current and reactive current will exist a time buffer, which in turn directly affects the detection effect of fundamental active current and reactive current at power grid side. It may lead to not timely compensate the reactiveand harmonic current in load side. Based on the above problems, this paper proposed a Scott balance transformer combined balance transform device of cophase traction power supply system mode. The twophase voltage and current analysis Through the special power supply mode of the twophase balance transformer. According to the instantaneous reactive power theory of twophase circuit, the whole singlephase fundamental wave active and reactive current signals aredetected.Theactive current in the whole singlephase circuit is decomposed. Thus,the amount of negative sequence can be obtainedin the case of mutation, and then the positive sequence under the condition of fundamental wave stability is recombined with the negative sequence. Therefore, the dynamic performancegets greatly improved when it occurs load mutation. Simulation and theoretical comprehensive analysis verify the rationality of this method.
When itoccurs load mutation in cophase power supply system, conventional detection method in detecting the fundamental active current and reactive current will exist a time buffer, which in turn directly affects the detection effect of fundamental active current and reactive current at power grid side. It may lead to not timely compensate the reactiveand harmonic current in load side. Based on the above problems, this paper proposed a Scott balance transformer combined balance transform device of cophase traction power supply system mode. The twophase voltage and current analysis Through the special power supply mode of the twophase balance transformer. According to the instantaneous reactive power theory of twophase circuit, the whole singlephase fundamental wave active and reactive current signals aredetected.Theactive current in the whole singlephase circuit is decomposed. Thus,the amount of negative sequence can be obtainedin the case of mutation, and then the positive sequence under the condition of fundamental wave stability is recombined with the negative sequence. Therefore, the dynamic performancegets greatly improved when it occurs load mutation. Simulation and theoretical comprehensive analysis verify the rationality of this method.
,35(4):176-181, DOI: 10.19781/j.issn.16739140.2020.04.024
Abstract:
Aiming at the nondirectly grounded distribution network of neutral point, this paper proposes to connect the small current fault line selection device to the distribution automation system. When a singlephase ground fault occurs, through the onoff control of the intelligent switch on the line and sequential logic of singlephase grounding alarm signal to determine the fault interval.Then the method isolates the fault area through the distribution automation system, restores the power supply in the nonfault area, and realizes the singlephase ground fault selfhealing of the distribution grid. In the end, this paper verifies the effectiveness and necessity of this strategy by experiments.
Aiming at the nondirectly grounded distribution network of neutral point, this paper proposes to connect the small current fault line selection device to the distribution automation system. When a singlephase ground fault occurs, through the onoff control of the intelligent switch on the line and sequential logic of singlephase grounding alarm signal to determine the fault interval.Then the method isolates the fault area through the distribution automation system, restores the power supply in the nonfault area, and realizes the singlephase ground fault selfhealing of the distribution grid. In the end, this paper verifies the effectiveness and necessity of this strategy by experiments.
,35(4):66-75, DOI: 10.19781/j.issn.16739140.2020.04.009
Abstract:
In the traditional electromagnetic transient simulation, the computation speed of SVC (Static Var Compensator) and TCSC (Thyristor Controlled Series Compensation) is relatively slower. In order to overcome this deficiency, a new method of fast simulation for the electromagnetic transients of SVC and TCSC is proposed. For the fact that the state equations of SVC and TCSC are unchanged when the state of TCR (Thyristor Controlled Reactor) branches stay the same, the piecewise timeinvariant state equations of SVC and TCSC are developed firstly. Then, auxiliary variables are introduced and the model is transformed from a set of nonhomogeneous linear equations into homogeneous ones to obtain the unified expression suitable for varied working conditions. Finally, the scaling and squaring method is utilized to compute the matrix exponent and the response of the model is obtained. The feasibility and high efficiency of the proposed method is verified by comparing with the results from classical electromagnetic transient simulations using the PSCAD/EMTDC software package.
In the traditional electromagnetic transient simulation, the computation speed of SVC (Static Var Compensator) and TCSC (Thyristor Controlled Series Compensation) is relatively slower. In order to overcome this deficiency, a new method of fast simulation for the electromagnetic transients of SVC and TCSC is proposed. For the fact that the state equations of SVC and TCSC are unchanged when the state of TCR (Thyristor Controlled Reactor) branches stay the same, the piecewise timeinvariant state equations of SVC and TCSC are developed firstly. Then, auxiliary variables are introduced and the model is transformed from a set of nonhomogeneous linear equations into homogeneous ones to obtain the unified expression suitable for varied working conditions. Finally, the scaling and squaring method is utilized to compute the matrix exponent and the response of the model is obtained. The feasibility and high efficiency of the proposed method is verified by comparing with the results from classical electromagnetic transient simulations using the PSCAD/EMTDC software package.
,35(4):181-182, DOI: 10.19781/j.issn.16739140.2020.04.025
Abstract:
Based on the analytical expression of the static voltage stability limit derived from apparent power, this paper gives an index to identify the weak point of static voltage stability, and proposes an improved engineering calculation method for the static voltage stability limit. The power system simulation software is mainly used in the project to calculate the static voltage stability. This method simulates the load growth in the stability calculation program, and solves the problem of limit misjudgment caused by the difficulty of the convergence of the operating point near the static voltage stability limit in the ordinary power flow algorithm. In the power flow calculation program, the PV node of the generator in the region is modified to a PQ node, which solves the problem of excessive output of reactive power caused by the dynamic calculation characteristic of the generator in the stable calculation program. Finally, a certain district power grid in Beijing is used as an example to verify the adaptability of the calculation method.
Based on the analytical expression of the static voltage stability limit derived from apparent power, this paper gives an index to identify the weak point of static voltage stability, and proposes an improved engineering calculation method for the static voltage stability limit. The power system simulation software is mainly used in the project to calculate the static voltage stability. This method simulates the load growth in the stability calculation program, and solves the problem of limit misjudgment caused by the difficulty of the convergence of the operating point near the static voltage stability limit in the ordinary power flow algorithm. In the power flow calculation program, the PV node of the generator in the region is modified to a PQ node, which solves the problem of excessive output of reactive power caused by the dynamic calculation characteristic of the generator in the stable calculation program. Finally, a certain district power grid in Beijing is used as an example to verify the adaptability of the calculation method.
,35(4):133-140, DOI: 10.19781/j.issn.16739140.2020.04.018
Abstract:
Nowadays, the condition assessment of transformer doesn't consider the dynamic characteristics and variational tendency of information in different stages. On this background, a dynamic gray target assessment model based on approaching degrees is proposed in this paper. First of all, the index data of benefittype and costtype are standardized. Secondly, the variance and the mean deviation of the interval grey number are introduced to evaluate the data volatility of the interval index. Then, the best weight can be determined. After that, a dynamic grey target evaluation model of interval grey number is proposed considering the accumulation of transformer phase information and the dynamic variation of index. The approaching degree is regarded as the basis of condition assessment. At last, the multistage operation data of multiple transformers in a substation is analyzed to verify the validity of the proposed method.
Nowadays, the condition assessment of transformer doesn't consider the dynamic characteristics and variational tendency of information in different stages. On this background, a dynamic gray target assessment model based on approaching degrees is proposed in this paper. First of all, the index data of benefittype and costtype are standardized. Secondly, the variance and the mean deviation of the interval grey number are introduced to evaluate the data volatility of the interval index. Then, the best weight can be determined. After that, a dynamic grey target evaluation model of interval grey number is proposed considering the accumulation of transformer phase information and the dynamic variation of index. The approaching degree is regarded as the basis of condition assessment. At last, the multistage operation data of multiple transformers in a substation is analyzed to verify the validity of the proposed method.
