- Current Issue
- Online First
- Archive
- Most Downloaded
Display Method:
2024(1):1-12, DOI: 10.19781/j.issn.1673-9140.2024.01.001
Abstract:
To address the challenges posed by the large-scale integration of electric vehicles and new energy sources on the stability of power system operations and the efficient utilization of new energy, the integrated photovoltaic-energy storage-charging model emerges. The synergistic interaction mechanisms and optimized control strategies among its individual units have also become key issues urgently needing resolution in smart grid development. Due to the characteristics of integrated generation, load, and storage, mutual complementarity of supply and demand, and flexible dispatch, the photovoltaic-energy storage-charging (PV-ESS-EV) integrated station micro-grid (ISM) mode, incorporating "PV- PV-ESS-EV + intelligent building" features, has become a focal point for energy conservation, carbon reduction, and energy transition in China. In consideration of the challenges faced by the operational mode of microgrids, such as the strong uncertainty of distributed energy sources and the unclear interaction mechanisms during islanded and grid-connected operation, various aspects of the PV-ESS-EV ISM are reviewed, including its unit modules, key technologies, and operational states. Additionally, the current research status of PV-ESS-EV is summarized while future development trends are discussed, and the challenges that need to be addressed are examined. The research findings have important theoretical and practical implications for exploring the regulatory potential of various demand-response resources under economic incentives, ensuring the reliability of power grid supply, and serving as valuable references for both theory and practice.
To address the challenges posed by the large-scale integration of electric vehicles and new energy sources on the stability of power system operations and the efficient utilization of new energy, the integrated photovoltaic-energy storage-charging model emerges. The synergistic interaction mechanisms and optimized control strategies among its individual units have also become key issues urgently needing resolution in smart grid development. Due to the characteristics of integrated generation, load, and storage, mutual complementarity of supply and demand, and flexible dispatch, the photovoltaic-energy storage-charging (PV-ESS-EV) integrated station micro-grid (ISM) mode, incorporating "PV- PV-ESS-EV + intelligent building" features, has become a focal point for energy conservation, carbon reduction, and energy transition in China. In consideration of the challenges faced by the operational mode of microgrids, such as the strong uncertainty of distributed energy sources and the unclear interaction mechanisms during islanded and grid-connected operation, various aspects of the PV-ESS-EV ISM are reviewed, including its unit modules, key technologies, and operational states. Additionally, the current research status of PV-ESS-EV is summarized while future development trends are discussed, and the challenges that need to be addressed are examined. The research findings have important theoretical and practical implications for exploring the regulatory potential of various demand-response resources under economic incentives, ensuring the reliability of power grid supply, and serving as valuable references for both theory and practice.
ZHONG Lipeng, LIU Zulong, TANG Wenqiang, LIANG Kun, WU Jie, WANG Feng, LIANG Kaibin, TANG Nian, SUN Dongwei, HAN Xutao
2024(1):13-27, DOI: 10.19781/j.issn.1673-9140.2024.01.002
Abstract:
Environmentally friendly gases such as C4F7N, HFO1336mmz(Z), with low global warming potential (GWP) and high insulation strength, are expected to partially replace SF6 in high-voltage electrical equipment. This substitution is expected to drive the development of green, low-carbon, high-voltage equipment, aligning with the objectives of "Emission Peak and Carbon Neutrality". The characteristics of gas-solid interface discharge, the generation of solid deposits under abnormal conditions directly impact the operational safety of environmentally friendly insulation systems. Therefore, conducting thorough research before large-scale application is crucial. This paper reviews the current research progress on these topics, summarizing the global development and application of environmentally friendly insulation gases and related high-voltage equipment. It also analyzes the research progress on the charge accumulation at the gas-solid interface and the surface flashover characteristics. Additionally, it discusses the composition and formation process of solid deposits resulting from the deep decomposition, along with their impact on interface insulation and measures to inhibit their formation. This review provides valuable insights for the research and development of environmentally friendly gases and insulation equipment.
Environmentally friendly gases such as C4F7N, HFO1336mmz(Z), with low global warming potential (GWP) and high insulation strength, are expected to partially replace SF6 in high-voltage electrical equipment. This substitution is expected to drive the development of green, low-carbon, high-voltage equipment, aligning with the objectives of "Emission Peak and Carbon Neutrality". The characteristics of gas-solid interface discharge, the generation of solid deposits under abnormal conditions directly impact the operational safety of environmentally friendly insulation systems. Therefore, conducting thorough research before large-scale application is crucial. This paper reviews the current research progress on these topics, summarizing the global development and application of environmentally friendly insulation gases and related high-voltage equipment. It also analyzes the research progress on the charge accumulation at the gas-solid interface and the surface flashover characteristics. Additionally, it discusses the composition and formation process of solid deposits resulting from the deep decomposition, along with their impact on interface insulation and measures to inhibit their formation. This review provides valuable insights for the research and development of environmentally friendly gases and insulation equipment.
2024(1):28-46, DOI: 10.19781/j.issn.1673-9140.2024.01.003
Abstract:
The combination of cyber-physical-social systems and demand response assessment is reviewed. First, the history and framework of cyber-physical systems are analyzed. Then, summaries are provided for the existing research on demand response, including the significance, classification, and evaluation methods of demand response potential assessment, as well as the data sources for demand response capability assessment, including questionnaire surveys and operational data collection. In terms of the combination of cyber-physical-social systems and demand response, the physical domain, information domain and social domain foundation of demand response are analyzed respectively, and the corresponding modeling methods and research contents are introduced. Finally, prospects are provided for market assessment mechanisms, rapid simulation and modeling technologies, and demand response management under integrated energy systems.
The combination of cyber-physical-social systems and demand response assessment is reviewed. First, the history and framework of cyber-physical systems are analyzed. Then, summaries are provided for the existing research on demand response, including the significance, classification, and evaluation methods of demand response potential assessment, as well as the data sources for demand response capability assessment, including questionnaire surveys and operational data collection. In terms of the combination of cyber-physical-social systems and demand response, the physical domain, information domain and social domain foundation of demand response are analyzed respectively, and the corresponding modeling methods and research contents are introduced. Finally, prospects are provided for market assessment mechanisms, rapid simulation and modeling technologies, and demand response management under integrated energy systems.
2024(1):47-56, DOI: 10.19781/j.issn.1673-9140.2024.01.004
Abstract:
The intermittency and volatility of wind speed changes pose great challenges to the accurate prediction of wind power. Fully exploring the inherent laws of key factors such as wind power and wind speed is an effective way to improve the accuracy of wind power prediction. A method for ultra-short-term wind power prediction is proposed, which incorporates a temporal pattern attention (TPA) mechanism into a multi-layer stacked bidirectional long short-term memory network. Firstly, outlier detection for the wind power dataset is performed using a density-based noisy spatial clustering method (DBSCAN) and a linear regression algorithm, followed by data reconstruction of outlier points using k-nearest neighbor (KNN) interpolation. Next, the intrinsic correlations between wind power and various meteorological features are comprehensively considered, and the TPA mechanism is introduced into the MBLSTM network to properly allocate time step weights, capturing the underlying logical patterns of the wind power time series. Finally, the effectiveness of the proposed method is verified through experimental simulation data analysis. Results show that this method can fully explore the relationship between wind power and wind speed influencing factors, thereby improving its prediction accuracy.
The intermittency and volatility of wind speed changes pose great challenges to the accurate prediction of wind power. Fully exploring the inherent laws of key factors such as wind power and wind speed is an effective way to improve the accuracy of wind power prediction. A method for ultra-short-term wind power prediction is proposed, which incorporates a temporal pattern attention (TPA) mechanism into a multi-layer stacked bidirectional long short-term memory network. Firstly, outlier detection for the wind power dataset is performed using a density-based noisy spatial clustering method (DBSCAN) and a linear regression algorithm, followed by data reconstruction of outlier points using k-nearest neighbor (KNN) interpolation. Next, the intrinsic correlations between wind power and various meteorological features are comprehensively considered, and the TPA mechanism is introduced into the MBLSTM network to properly allocate time step weights, capturing the underlying logical patterns of the wind power time series. Finally, the effectiveness of the proposed method is verified through experimental simulation data analysis. Results show that this method can fully explore the relationship between wind power and wind speed influencing factors, thereby improving its prediction accuracy.
2024(1):57-64, DOI: 10.19781/j.issn.1673-9140.2024.01.005
Abstract:
Wind turbine blades are susceptible to icing caused by frost or rime and other extreme weather conditions in winter, which directly affects the wind turbine output, even leads to safety problems such as ice accumulation and subsequent shedding. Therefore, it is necessary to investigate the anti /deicing technologies for wind turbine blades. In this paper, a deicing method for wind turbine blades based on microwave heating is proposed. To improve the microwave heating performance of the blade, carbon black and carbon fiber are incorporated into the blade composite. The study employs a combination of COMSOL and MATLAB to optimize the parameters of the filling medium within the blade. Subsequently, simulations are conducted to analyze the microwave heating and deicing performance of the optimized blade composite, examining the influences of microwave heating power and ambient temperature on deicing time. The results indicate that the optimum carbon black filling concentration is 3.98%. Under this condition, the carbon fibers within the composite form a sandwich structure?denser at the top and bottom and sparser in the middle, which effectively improves the microwave absorption rate of the composite. Furthermore, it is observed that increasing microwave power and ambient temperature significantly reduce the deicing time, with microwave power exerting a more pronounced effect compared to ambient temperature.
Wind turbine blades are susceptible to icing caused by frost or rime and other extreme weather conditions in winter, which directly affects the wind turbine output, even leads to safety problems such as ice accumulation and subsequent shedding. Therefore, it is necessary to investigate the anti /deicing technologies for wind turbine blades. In this paper, a deicing method for wind turbine blades based on microwave heating is proposed. To improve the microwave heating performance of the blade, carbon black and carbon fiber are incorporated into the blade composite. The study employs a combination of COMSOL and MATLAB to optimize the parameters of the filling medium within the blade. Subsequently, simulations are conducted to analyze the microwave heating and deicing performance of the optimized blade composite, examining the influences of microwave heating power and ambient temperature on deicing time. The results indicate that the optimum carbon black filling concentration is 3.98%. Under this condition, the carbon fibers within the composite form a sandwich structure?denser at the top and bottom and sparser in the middle, which effectively improves the microwave absorption rate of the composite. Furthermore, it is observed that increasing microwave power and ambient temperature significantly reduce the deicing time, with microwave power exerting a more pronounced effect compared to ambient temperature.
2024(1):65-73,92, DOI: 10.19781/j.issn.1673-9140.2024.01.006
Abstract:
In response to the integration of wind power into the multi terminal flexible DC transmission system, this paper proposes an additional adaptive frequency division control strategy on the basis of existing droop control, in order to fully utilize the wind power's participation in system frequency regulation ability and solve the voltage and frequency fluctuations caused by AC/DC grid connection faults in the DC system. The DC voltage deviation signal is taken as the input signal of the controller, and the input signal is divided into high-frequency fluctuation signal and low-frequency fluctuation signal through the first-order low-pass filter. According to the different frequency modulation capabilities of the wind power and DC transmission systems, the high-frequency fluctuation signal is added to the active power control loop of the converter at the rotor side of the wind turbine, and the low-frequency fluctuation signal is added to the external loop of the DC active power control, At the same time,voltage source converter （VSC） real-time power margin and DC voltage variation are introduced into frequency division control to adjust the time constant of the low-pass filter in real time and dynamically adjust the power output to improve system stability. A simulation model is built in PSCAD/EMTDC to verify the effectiveness of the proposed control strategy.
In response to the integration of wind power into the multi terminal flexible DC transmission system, this paper proposes an additional adaptive frequency division control strategy on the basis of existing droop control, in order to fully utilize the wind power's participation in system frequency regulation ability and solve the voltage and frequency fluctuations caused by AC/DC grid connection faults in the DC system. The DC voltage deviation signal is taken as the input signal of the controller, and the input signal is divided into high-frequency fluctuation signal and low-frequency fluctuation signal through the first-order low-pass filter. According to the different frequency modulation capabilities of the wind power and DC transmission systems, the high-frequency fluctuation signal is added to the active power control loop of the converter at the rotor side of the wind turbine, and the low-frequency fluctuation signal is added to the external loop of the DC active power control, At the same time,voltage source converter （VSC） real-time power margin and DC voltage variation are introduced into frequency division control to adjust the time constant of the low-pass filter in real time and dynamically adjust the power output to improve system stability. A simulation model is built in PSCAD/EMTDC to verify the effectiveness of the proposed control strategy.
2024(1):74-83, DOI: 10.19781/j.issn.1673-9140.2024.01.007
Abstract:
Exploring the influence law of different photovoltaic penetration rates on the capacity allocation and operation of wind-solar-fire storage systems, a three-layer capacity optimization model considering penetration rate constraints and integrated control of thermal storage is constructed, using a wind-solar-thermal-storage combined generation system as an example. Firstly, introducing the golden search optimization (GSO) algorithm into the solution of capacity optimization configuration, the best capacity configuration of the system under different penetration rate constraints is provided, and the resulting data of system operation indicators is obtained. Then, the obtained results are subjected to a least squares curve fitting, yielding curves depicting the variations of system economics, reliability, and stability with different penetration rates. Finally, the main reasons for the trend changes in the curves are systematically analyzed, providing insights for the optimization and planning of capacity allocation and operation planning of renewable energy systems such as wind and solar.
Exploring the influence law of different photovoltaic penetration rates on the capacity allocation and operation of wind-solar-fire storage systems, a three-layer capacity optimization model considering penetration rate constraints and integrated control of thermal storage is constructed, using a wind-solar-thermal-storage combined generation system as an example. Firstly, introducing the golden search optimization (GSO) algorithm into the solution of capacity optimization configuration, the best capacity configuration of the system under different penetration rate constraints is provided, and the resulting data of system operation indicators is obtained. Then, the obtained results are subjected to a least squares curve fitting, yielding curves depicting the variations of system economics, reliability, and stability with different penetration rates. Finally, the main reasons for the trend changes in the curves are systematically analyzed, providing insights for the optimization and planning of capacity allocation and operation planning of renewable energy systems such as wind and solar.
2024(1):84-92, DOI: 10.19781/j.issn.1673-9140.2024.01.008
Abstract:
To address the operational quality assessment requirements of the high speed power line carrier communication (HPLC) unit in energy metering equipment, a multi-model integration-based assessment method utilizing KICA-CIM is proposed. Firstly, the main performance influencing factors of local internet of things (IoT) application scenarios and communication technologies of typical customer-side metering equipment are integrated and analyzed, and a universally applicable index library for performance evaluation of IoT scenarios is comprehensively constructed. Next, in the operational scenario with multi-source, heterogeneous, and high-dimensional data environment, on the one hand, kernel independent component analysis (KICA) is used to process nonlinear features and solve principal components, calculating individual weights of each indicator. On the other hand, component importance measure (CIM) model is utilized to distinguish and measure the different impact levels of each indicator evaluation result on the overall evaluation effect, assigning importance weights to the indicators to determine the functional weight of each indicator. Through the implementation of integrated weighting models, comprehensive assessment of operational quality is achieved. Finally, the feasibility and effectiveness of the proposed method are verified using data from energy metering equipment in a certain region, which contributes to improving the accuracy and rationality of the assessment results.
To address the operational quality assessment requirements of the high speed power line carrier communication (HPLC) unit in energy metering equipment, a multi-model integration-based assessment method utilizing KICA-CIM is proposed. Firstly, the main performance influencing factors of local internet of things (IoT) application scenarios and communication technologies of typical customer-side metering equipment are integrated and analyzed, and a universally applicable index library for performance evaluation of IoT scenarios is comprehensively constructed. Next, in the operational scenario with multi-source, heterogeneous, and high-dimensional data environment, on the one hand, kernel independent component analysis (KICA) is used to process nonlinear features and solve principal components, calculating individual weights of each indicator. On the other hand, component importance measure (CIM) model is utilized to distinguish and measure the different impact levels of each indicator evaluation result on the overall evaluation effect, assigning importance weights to the indicators to determine the functional weight of each indicator. Through the implementation of integrated weighting models, comprehensive assessment of operational quality is achieved. Finally, the feasibility and effectiveness of the proposed method are verified using data from energy metering equipment in a certain region, which contributes to improving the accuracy and rationality of the assessment results.
2024(1):93-104, DOI: 10.19781/j.issn.1673-9140.2024.01.009
Abstract:
Detecting user-side electricity theft accurately has long been a challenge for power supply companies, with traditional theft detection methods having certain limitations. Addressing the highly imbalanced positive and negative samples in the field of theft detection, and the poor performance of single classification models, this study proposes a theft detection method based on an improved Rotation Forest algorithm. The Rotation Forest algorithm uses Principal Component Analysis (PCA) for feature extraction, training each base classifier with all principal components of the original training set. Building upon the classical Rotation Forest algorithm, improvements are made in three aspects: balancing the positive and negative samples in the subset using the Synthetic Minority Oversampling Technique (SMOTE) algorithm, further sampling the training subset using Bootstrap sampling in the Bagging algorithm, and selectively integrating base classifiers based on accuracy. A case study using actual user data from a region in East China demonstrates that the proposed theft detection method achieves better results in multiple evaluation metrics compared to single classification models and existing ensemble learning strategies.
Detecting user-side electricity theft accurately has long been a challenge for power supply companies, with traditional theft detection methods having certain limitations. Addressing the highly imbalanced positive and negative samples in the field of theft detection, and the poor performance of single classification models, this study proposes a theft detection method based on an improved Rotation Forest algorithm. The Rotation Forest algorithm uses Principal Component Analysis (PCA) for feature extraction, training each base classifier with all principal components of the original training set. Building upon the classical Rotation Forest algorithm, improvements are made in three aspects: balancing the positive and negative samples in the subset using the Synthetic Minority Oversampling Technique (SMOTE) algorithm, further sampling the training subset using Bootstrap sampling in the Bagging algorithm, and selectively integrating base classifiers based on accuracy. A case study using actual user data from a region in East China demonstrates that the proposed theft detection method achieves better results in multiple evaluation metrics compared to single classification models and existing ensemble learning strategies.
2024(1):105-114, DOI: 10.19781/j.issn.1673-9140.2024.01.010
Abstract:
To meet the requirements of accommodating new energy sources and balancing power supply and demand, a new type of power system dominated by new energy sources needs to maximize the load-side regulation capability. To address the problem of insufficient exploitation of load-side regulation capability, this study proposes an electricity load optimization method based on an interactive real-time electricity price mechanism. Firstly, a generalized benchmark new energy output curve is established based on the total new energy within a regional power grid. Secondly, a source-load similarity calculation method based on improved time series morphological similarity is proposed to calculate the similarity between electricity load and the generalized new energy benchmark curve, and a model for the correlation between load and electricity price is constructed. Then, an interactive real-time electricity price mechanism based on source-load similarity is proposed to guide user participation in response. Finally, a multi-objective optimization model is constructed for load optimization. Simulation results show that the proposed interactive real-time electricity price mechanism achieves better load optimization results, effectively increases user participation in demand-side response, and accurately measures the similarity between new energy and load curves. This approach stabilizes the net load power and promotes the high-quality integration of new energy.
To meet the requirements of accommodating new energy sources and balancing power supply and demand, a new type of power system dominated by new energy sources needs to maximize the load-side regulation capability. To address the problem of insufficient exploitation of load-side regulation capability, this study proposes an electricity load optimization method based on an interactive real-time electricity price mechanism. Firstly, a generalized benchmark new energy output curve is established based on the total new energy within a regional power grid. Secondly, a source-load similarity calculation method based on improved time series morphological similarity is proposed to calculate the similarity between electricity load and the generalized new energy benchmark curve, and a model for the correlation between load and electricity price is constructed. Then, an interactive real-time electricity price mechanism based on source-load similarity is proposed to guide user participation in response. Finally, a multi-objective optimization model is constructed for load optimization. Simulation results show that the proposed interactive real-time electricity price mechanism achieves better load optimization results, effectively increases user participation in demand-side response, and accurately measures the similarity between new energy and load curves. This approach stabilizes the net load power and promotes the high-quality integration of new energy.
2024(1):115-123,133, DOI: 10.19781/j.issn.1673-9140.2024.01.011
Abstract:
To eliminate the impact of spatial distribution uncertainty on the accuracy of ultra-short-term forecasting of electric vehicle charging load, a method based on the utilization rate of charging piles for electric vehicle charging load ultra-short-term forecasting is proposed. Firstly, the charging load power of each charging pile within the region is extracted from massive charging transaction data, and then quantified values of the utilization rate of charging piles are obtained through encoding. Then, the utilization rate of charging piles and charging load power data are merged to obtain training samples and test sets for long short-term memory (LSTM) neural networks, forming a deep learning model for ultra-short-term forecasting of electric vehicle charging load, with a time resolution of up to 0.5 h. Finally, the effectiveness and accuracy of the proposed method are validated in scenarios with different scales of charging load. The results indicate that compared to the unoptimized LSTM neural network load forecasting method, the proposed method achieves an increase in the average absolute percentage error of approximately 5%. This can provide significant support for the optimization operation of distribution grids under future vehicle-grid interaction.
To eliminate the impact of spatial distribution uncertainty on the accuracy of ultra-short-term forecasting of electric vehicle charging load, a method based on the utilization rate of charging piles for electric vehicle charging load ultra-short-term forecasting is proposed. Firstly, the charging load power of each charging pile within the region is extracted from massive charging transaction data, and then quantified values of the utilization rate of charging piles are obtained through encoding. Then, the utilization rate of charging piles and charging load power data are merged to obtain training samples and test sets for long short-term memory (LSTM) neural networks, forming a deep learning model for ultra-short-term forecasting of electric vehicle charging load, with a time resolution of up to 0.5 h. Finally, the effectiveness and accuracy of the proposed method are validated in scenarios with different scales of charging load. The results indicate that compared to the unoptimized LSTM neural network load forecasting method, the proposed method achieves an increase in the average absolute percentage error of approximately 5%. This can provide significant support for the optimization operation of distribution grids under future vehicle-grid interaction.
2024(1):124-133, DOI: 10.19781/j.issn.1673-9140.2024.01.012
Abstract:
To address the "peak upon peak" phenomenon caused by unorganized charging of electric vehicles on a large scale, this study divides the distribution network into microgrids for residential, office, and commercial areas based on the location of electric vehicle charging. A multi-objective electric vehicle charging mode is proposed, considering peak-to-valley difference, time-of-use electricity prices, and user satisfaction. A dual-profit multi-objective optimization scheduling model is established to minimize the peak-to-valley difference for microgrid operators while minimizing user charging costs and maximizing charging satisfaction. Real mixed residential, office, and commercial complexes in Shanghai are used as a case study, and the MATLAB/NSGA-Ⅱ algorithm is employed to solve the load shaping degree. The particle swarm optimization algorithm is used to solve the optimal charging satisfaction for electric vehicle owners, guiding the timing and power of electric vehicle charging. Simulation results of the actual case demonstrate that this method effectively reduces the peak-to-valley difference in the distribution network, improves the efficiency of electric vehicle charging, and meets user charging demands.
To address the "peak upon peak" phenomenon caused by unorganized charging of electric vehicles on a large scale, this study divides the distribution network into microgrids for residential, office, and commercial areas based on the location of electric vehicle charging. A multi-objective electric vehicle charging mode is proposed, considering peak-to-valley difference, time-of-use electricity prices, and user satisfaction. A dual-profit multi-objective optimization scheduling model is established to minimize the peak-to-valley difference for microgrid operators while minimizing user charging costs and maximizing charging satisfaction. Real mixed residential, office, and commercial complexes in Shanghai are used as a case study, and the MATLAB/NSGA-Ⅱ algorithm is employed to solve the load shaping degree. The particle swarm optimization algorithm is used to solve the optimal charging satisfaction for electric vehicle owners, guiding the timing and power of electric vehicle charging. Simulation results of the actual case demonstrate that this method effectively reduces the peak-to-valley difference in the distribution network, improves the efficiency of electric vehicle charging, and meets user charging demands.
2024(1):134-143, DOI: 10.19781/j.issn.1673-9140.2024.01.013
Abstract:
The metro stray current leaked during the train operation causes the surface potential fluctuation, resulting nearby transformer DC bias. Firstly, a equivalent resistance network model was established to realize actual time numerical calculation of stray current. Then, the stray current field equation was further derived, and the dynamic simulation of the geopotential potential distribution was realized during the train operation. Based on the potential distribution caused by stray current and the equivalent DC resistance model of AC power grid, the numerical calculation of DC bias current and excitation current of grounding transformer was realized. The index of neutral point current and waveform distortion rate is established, so the effective evaluation of the transformer DC bias could be realized. The simulation results show that the operating conditions and distance between the metro train have obvious effects on the transformer DC bias, so formulating a reasonable metro operation strategy could effectively restrain transformer DC bias interference for nearby substations.
The metro stray current leaked during the train operation causes the surface potential fluctuation, resulting nearby transformer DC bias. Firstly, a equivalent resistance network model was established to realize actual time numerical calculation of stray current. Then, the stray current field equation was further derived, and the dynamic simulation of the geopotential potential distribution was realized during the train operation. Based on the potential distribution caused by stray current and the equivalent DC resistance model of AC power grid, the numerical calculation of DC bias current and excitation current of grounding transformer was realized. The index of neutral point current and waveform distortion rate is established, so the effective evaluation of the transformer DC bias could be realized. The simulation results show that the operating conditions and distance between the metro train have obvious effects on the transformer DC bias, so formulating a reasonable metro operation strategy could effectively restrain transformer DC bias interference for nearby substations.
2024(1):144-154, DOI: 10.19781/j.issn.1673-9140.2024.01.014
Abstract:
The floating crane supply system usually incorporates large-capacity multiple asynchronous motors. During the starting process of these motors, simultaneous activation can result in substantial current surges. Consequently, the transformer bears a heavy current burden, potentially triggering the false overcurrent protection and leading to further industrial production losses. This paper investigates a protection scheme for transformers supplying multiple high-capacity motors. Firstly, the mechanism of the overcurrent during motor starting is analyzed by an equivalent model. Subsequently, a random scenario generating algorithm is proposed to generate a large number of scenarios for analysis. Furthermore, the Hilbert-Huang transform technique is employed to examine the time-frequency domain characteristics of both fault current and normal current, leading to improvements in the conventional overcurrent protection scheme. Finally, The effectiveness of the proposed protection scheme is validated through a realistic floating crane supply project in Hunan province.
The floating crane supply system usually incorporates large-capacity multiple asynchronous motors. During the starting process of these motors, simultaneous activation can result in substantial current surges. Consequently, the transformer bears a heavy current burden, potentially triggering the false overcurrent protection and leading to further industrial production losses. This paper investigates a protection scheme for transformers supplying multiple high-capacity motors. Firstly, the mechanism of the overcurrent during motor starting is analyzed by an equivalent model. Subsequently, a random scenario generating algorithm is proposed to generate a large number of scenarios for analysis. Furthermore, the Hilbert-Huang transform technique is employed to examine the time-frequency domain characteristics of both fault current and normal current, leading to improvements in the conventional overcurrent protection scheme. Finally, The effectiveness of the proposed protection scheme is validated through a realistic floating crane supply project in Hunan province.
2024(1):155-163, DOI: 10.19781/j.issn.1673-9140.2024.01.015
Abstract:
The capacitance current to ground in a non-earthing system is increased due to cables, which results in the low-frequency nonlinear oscillation caused by the single-phase earthing fault and hence leads to the fuse of potential transformer (PT), seriously affect the safe operation. The principle of PT fuse caused by low-frequency nonlinear oscillation is analyzed, and a 10 kV neutral point ungrounded system is simulated with ATP-EMTP software. Calculations show that the maximum overvoltage of low-frequency nonlinear oscillation is less than 2.0 p.u.; after 0.1 s of fault occurse, the capacitance relative to the earth increases, the zero-sequence resistance decreases, and the fuse risk increases. Simulation results show the effectiveness of suppression measures for PT with four wires and the neutral point at its high voltage side in series with a varistor. Measurement errors of the zero-sequence voltage are also calculated. Finally, the platform of a 10 kV system for low-frequency nonlinear oscillation tests is built to verify the validity. It is valuable to improve the safety of PT operation in distribution network.
The capacitance current to ground in a non-earthing system is increased due to cables, which results in the low-frequency nonlinear oscillation caused by the single-phase earthing fault and hence leads to the fuse of potential transformer (PT), seriously affect the safe operation. The principle of PT fuse caused by low-frequency nonlinear oscillation is analyzed, and a 10 kV neutral point ungrounded system is simulated with ATP-EMTP software. Calculations show that the maximum overvoltage of low-frequency nonlinear oscillation is less than 2.0 p.u.; after 0.1 s of fault occurse, the capacitance relative to the earth increases, the zero-sequence resistance decreases, and the fuse risk increases. Simulation results show the effectiveness of suppression measures for PT with four wires and the neutral point at its high voltage side in series with a varistor. Measurement errors of the zero-sequence voltage are also calculated. Finally, the platform of a 10 kV system for low-frequency nonlinear oscillation tests is built to verify the validity. It is valuable to improve the safety of PT operation in distribution network.
2024(1):164-170, DOI: 10.19781/j.issn.1673-9140.2024.01.016
Abstract:
It is one of the most important problems in power system reliability to detect the fault types and locations of transmission lines in time and accurately.Th is paper presents an approach for fault identification and location of transmission lines based on convolutional neural networks (CNN) paralled with extreme learning machine (ELM) based on fast Fourier transform (FFT). First, CNN is constructed with fault voltage sequence diagram as input. Then FFT is used to decompose the fault voltage data in time domain and extract the peak voltage and phase angle of each frequency band as fault feature samples. The ELM network is then constructed by taking the extracted fault feature sample set as input. Finally, the two neural networks are fused by the feature fusion layer to output the fault type and location results. Experimental results show that the accuracy of the method is 99.95%, the error of fault location is less than 500 m and the average error is 263.5 m; the reliability of the method is better than other models.
It is one of the most important problems in power system reliability to detect the fault types and locations of transmission lines in time and accurately.Th is paper presents an approach for fault identification and location of transmission lines based on convolutional neural networks (CNN) paralled with extreme learning machine (ELM) based on fast Fourier transform (FFT). First, CNN is constructed with fault voltage sequence diagram as input. Then FFT is used to decompose the fault voltage data in time domain and extract the peak voltage and phase angle of each frequency band as fault feature samples. The ELM network is then constructed by taking the extracted fault feature sample set as input. Finally, the two neural networks are fused by the feature fusion layer to output the fault type and location results. Experimental results show that the accuracy of the method is 99.95%, the error of fault location is less than 500 m and the average error is 263.5 m; the reliability of the method is better than other models.
2024(1):171-182, DOI: 10.19781/j.issn.1673-9140.2024.01.017
Abstract:
When a single-phase-to-ground fault occurs in the small current system, its fault characteristics are easily affected by weak fault conditions such as the high grounding transition resistance and the small initial phase angle. Therefore, this paper presents a method of the single-phase-to-ground fault line selection based on an improved Hilbert?Huang transform-random forest. Firstly, the current transient signals of every lines are extracted. Then the pure transient electrical quantities are extracted by the improved Hilbert?Huang transform, and three kinds of eigenvectors such as standard deviations, energy entropy and amplitude distortion degrees are constructed. In the following, the eigenvectors are input into the random forest classifier to establish a fault line selection model, and the fault line selection problem is then transformed into a binary classification problem which realizing the automatic identification of fault lines. The simulation results show that the proposed method can effectively improve the accuracy of fault line selection by comprehensively using the amplitude, frequency and energy of transient signal; whatsmore it is not affected by weak fault condition and feeder structure, it hence has strong adaptability and reliability.
When a single-phase-to-ground fault occurs in the small current system, its fault characteristics are easily affected by weak fault conditions such as the high grounding transition resistance and the small initial phase angle. Therefore, this paper presents a method of the single-phase-to-ground fault line selection based on an improved Hilbert?Huang transform-random forest. Firstly, the current transient signals of every lines are extracted. Then the pure transient electrical quantities are extracted by the improved Hilbert?Huang transform, and three kinds of eigenvectors such as standard deviations, energy entropy and amplitude distortion degrees are constructed. In the following, the eigenvectors are input into the random forest classifier to establish a fault line selection model, and the fault line selection problem is then transformed into a binary classification problem which realizing the automatic identification of fault lines. The simulation results show that the proposed method can effectively improve the accuracy of fault line selection by comprehensively using the amplitude, frequency and energy of transient signal; whatsmore it is not affected by weak fault condition and feeder structure, it hence has strong adaptability and reliability.
2024(1):183-192, DOI: 10.19781/j.issn.1673-9140.2024.01.018
Abstract:
After a fault occurs in the distribution network, active distribution network can realize the real-time power supply and demand balance of user side and meet the demand of load recovery after fault. Users' participation in the dispatching of distribution network is also one of the ways to improve the proportion of load recovery. The translational load has strong controllability, which improves the flexibility of active distribution network. The access of new controllable devices, such as soft open point, also makes it possible for power supply quickly. In this paper, a fault recovery model of active distribution network considering translatable load and soft open point is established. The importance coefficient of load is considered. Through the simulation analysis of the modified IEEE 33-node test system, three scenarios of single fault, multi-point fault and short-term fault are built, the effectiveness of the proposed method and the improvement of load recovery after fault by the controllable device are verified.
After a fault occurs in the distribution network, active distribution network can realize the real-time power supply and demand balance of user side and meet the demand of load recovery after fault. Users' participation in the dispatching of distribution network is also one of the ways to improve the proportion of load recovery. The translational load has strong controllability, which improves the flexibility of active distribution network. The access of new controllable devices, such as soft open point, also makes it possible for power supply quickly. In this paper, a fault recovery model of active distribution network considering translatable load and soft open point is established. The importance coefficient of load is considered. Through the simulation analysis of the modified IEEE 33-node test system, three scenarios of single fault, multi-point fault and short-term fault are built, the effectiveness of the proposed method and the improvement of load recovery after fault by the controllable device are verified.
2024(1):193-200, DOI: 10.19781/j.issn.1673-9140.2024.01.019
Abstract:
In order to improve the efficiency of substation electromagnetic environment information collection and the accuracy of data measurement, an intelligent mobile monitoring device is designed and manufactured in this paper. Self-designed power frequency electric field probe can realize synchronous measurement of power frequency electric field in three directions. The power frequency magnetic field acquisition circuit with reset circuit can eliminate the abnormal problem caused by the interference of strong magnetic field to the magneto-resistive sensor. External temperature and humidity module are installed to ensure the accuracy of measurement. When the humidity is less than 70%, the measurement error is within 5%. The third-party test results show that the error of electromagnetic field measurement results is within 5%. The electromagnetic environment measuring results in actual 110 kV substation indicate that, this device can walk and measure accurately following the specified path. A three-dimensional model is established to simulate the spatial electromagnetic field distribution. The measured data and simulation data achieve the same change trend, which further verifies the measuring accuracy of the device.
In order to improve the efficiency of substation electromagnetic environment information collection and the accuracy of data measurement, an intelligent mobile monitoring device is designed and manufactured in this paper. Self-designed power frequency electric field probe can realize synchronous measurement of power frequency electric field in three directions. The power frequency magnetic field acquisition circuit with reset circuit can eliminate the abnormal problem caused by the interference of strong magnetic field to the magneto-resistive sensor. External temperature and humidity module are installed to ensure the accuracy of measurement. When the humidity is less than 70%, the measurement error is within 5%. The third-party test results show that the error of electromagnetic field measurement results is within 5%. The electromagnetic environment measuring results in actual 110 kV substation indicate that, this device can walk and measure accurately following the specified path. A three-dimensional model is established to simulate the spatial electromagnetic field distribution. The measured data and simulation data achieve the same change trend, which further verifies the measuring accuracy of the device.
2024(1):201-207, DOI: 10.19781/j.issn.1673-9140.2024.01.020
Abstract:
Direct current?based high?power charging (DC?HPC) technology can significantly reduce the charging time of electric vehicles and therefore alleviates concerns about charging duration. However, the rapid temperature increase of charging connectors under high voltage and current poses a challenge, impacting their lifespan and safety. This paper proposes a phase change cooling technology for the high?power super?charging connectors. Through a comparative numerical analysis of the single?phase and phase change cooling performance, the influence of coolant type, flow rate and casing thickness on the thermal behavior of the charging cable with active cooling are investigated. The results indicate that the cable temperature can be reduced to 69 ℃ when using 40 ℃ water as single?phase coolant at a 5 min charging time and a 600 A loading current. In contrast, the two?phase cooling coolant can further decrease the cable temperature to below 40 ℃. The charging cable temperature exhibits a decrease with increasing two?phase coolant flow and an increase with rising coolant sleeve thickness. The coolant sleeve thickness has a more significant effect on cable temperature than the coolant flow rate.
Direct current?based high?power charging (DC?HPC) technology can significantly reduce the charging time of electric vehicles and therefore alleviates concerns about charging duration. However, the rapid temperature increase of charging connectors under high voltage and current poses a challenge, impacting their lifespan and safety. This paper proposes a phase change cooling technology for the high?power super?charging connectors. Through a comparative numerical analysis of the single?phase and phase change cooling performance, the influence of coolant type, flow rate and casing thickness on the thermal behavior of the charging cable with active cooling are investigated. The results indicate that the cable temperature can be reduced to 69 ℃ when using 40 ℃ water as single?phase coolant at a 5 min charging time and a 600 A loading current. In contrast, the two?phase cooling coolant can further decrease the cable temperature to below 40 ℃. The charging cable temperature exhibits a decrease with increasing two?phase coolant flow and an increase with rising coolant sleeve thickness. The coolant sleeve thickness has a more significant effect on cable temperature than the coolant flow rate.
2024(1):208-217, DOI: 10.19781/j.issn.1673-9140.2024.01.021
Abstract:
Meteorological factors play an important role in the stable operation of transmission lines, which should be considered in risk assessment. This paper presents a method of transmission line meteorological risk early warning and protection. Considering the temporal and spatial power generation forecasting, equipment health and reliability assessment, probabilistic load forecasting and other aspects, a refined meteorological risk model is established, and a new risk measurement standard is proposed based on Meteorological hazards, grid vulnerability and post disaster recovery cost. In addition, aiming at the restoration of load interruption and the alleviation of power congestion, the online warning and defense strategy of meteorological disasters is proposed. Finally, the proposed method is tested and analyzed in the simulation to verify the effectiveness of the method.
Meteorological factors play an important role in the stable operation of transmission lines, which should be considered in risk assessment. This paper presents a method of transmission line meteorological risk early warning and protection. Considering the temporal and spatial power generation forecasting, equipment health and reliability assessment, probabilistic load forecasting and other aspects, a refined meteorological risk model is established, and a new risk measurement standard is proposed based on Meteorological hazards, grid vulnerability and post disaster recovery cost. In addition, aiming at the restoration of load interruption and the alleviation of power congestion, the online warning and defense strategy of meteorological disasters is proposed. Finally, the proposed method is tested and analyzed in the simulation to verify the effectiveness of the method.
2024(1):218-224, DOI: 10.19781/j.issn.1673-9140.2024.01.022
Abstract:
Aiming at the fluctuation of maintenance and repair costs in substation life cycle cost, a traditional grey model and an improved grey model are adopted respectively, to forecast the maintenance and repair costs of a substation in the next 3 years in order to optimize cost allocation strategy. Simulation results show that the prediction accuracy of both models is one grade; while both the average relative error and the posterior error ratio of the improved model are lower than those of the traditional one. The prediction accuracy of the improved model is hence higher than that of the traditional one, and can be suitable to predict the maintenance and repair costs of a substation. Finally, the improved grey model is used to predict the maintenance and repair costs during 2019 to 2021 of a specified substation in a city.
Aiming at the fluctuation of maintenance and repair costs in substation life cycle cost, a traditional grey model and an improved grey model are adopted respectively, to forecast the maintenance and repair costs of a substation in the next 3 years in order to optimize cost allocation strategy. Simulation results show that the prediction accuracy of both models is one grade; while both the average relative error and the posterior error ratio of the improved model are lower than those of the traditional one. The prediction accuracy of the improved model is hence higher than that of the traditional one, and can be suitable to predict the maintenance and repair costs of a substation. Finally, the improved grey model is used to predict the maintenance and repair costs during 2019 to 2021 of a specified substation in a city.
2024(1):225-233,284, DOI: 10.19781/j.issn.1673-9140.2024.01.023
Abstract:
To address the shortcomings of low DC voltage utilization and high insulated gate bipolar transistors (IGBT) loss in the three-phase voltage source inverter applied by the space vector pulse width modulation (SVPWM) drive method with constant switching frequency and rated DC bus voltage, permanent magnet synchronous motor (PMSM) and output cycle-based IGBT loss control model is established, based on which the optimal switching frequency and DC bus voltage for output cycle based IGBT loss are obtained by applying the dwarf mongoose optimization algorithm with the output current quality as the constraint and the switching frequency and DC bus voltage as the constraint variables. The proposed strategy is simulated and experimented to verify that the proposed strategy reduces loss and increases reliability while maintaining control system performance by comparing the output current total harmonic distortion (THD), current waveform and IGBT loss and junction temperature performance.
To address the shortcomings of low DC voltage utilization and high insulated gate bipolar transistors (IGBT) loss in the three-phase voltage source inverter applied by the space vector pulse width modulation (SVPWM) drive method with constant switching frequency and rated DC bus voltage, permanent magnet synchronous motor (PMSM) and output cycle-based IGBT loss control model is established, based on which the optimal switching frequency and DC bus voltage for output cycle based IGBT loss are obtained by applying the dwarf mongoose optimization algorithm with the output current quality as the constraint and the switching frequency and DC bus voltage as the constraint variables. The proposed strategy is simulated and experimented to verify that the proposed strategy reduces loss and increases reliability while maintaining control system performance by comparing the output current total harmonic distortion (THD), current waveform and IGBT loss and junction temperature performance.
2024(1):234-242, DOI: 10.19781/j.issn.1673-9140.2024.01.024
Abstract:
In this paper, the oscillation mode of wind power through DC transmission system is analyzed, and the interaction mechanism between the circulating current zero sequence component of MMC system internal oscillation and capacitor voltage is revealed. The mechanism of the internal oscillation of MMC system caused by the interaction between the zero sequence component of the circulating current and the capacitor voltage of MMC is revealed. The dynamic relationship between the total energy stored by the equivalent capacitance of each arm of the MMC system and the zero-sequence current is constructed. The differential modulus and the common modulus of the total energy stored by the equivalent capacitance of each arm of the MMC system are derived. The zero-sequence current control strategy is proposed. The dynamic model of the control strategy is constructed, and the oscillation mode of MMC system with zero sequence current control strategy is analyzed after considering the intermediate variables of the model. The results show that the proposed control strategy can make the real part of the oscillation mode move left and increase the total damping. The electromagnetic transient simulation model of wind power through DC transmission system with zero sequence current control strategy is constructed. The simulation results show that the proposed strategy greatly increases the damping level of the system, improving the stability.
In this paper, the oscillation mode of wind power through DC transmission system is analyzed, and the interaction mechanism between the circulating current zero sequence component of MMC system internal oscillation and capacitor voltage is revealed. The mechanism of the internal oscillation of MMC system caused by the interaction between the zero sequence component of the circulating current and the capacitor voltage of MMC is revealed. The dynamic relationship between the total energy stored by the equivalent capacitance of each arm of the MMC system and the zero-sequence current is constructed. The differential modulus and the common modulus of the total energy stored by the equivalent capacitance of each arm of the MMC system are derived. The zero-sequence current control strategy is proposed. The dynamic model of the control strategy is constructed, and the oscillation mode of MMC system with zero sequence current control strategy is analyzed after considering the intermediate variables of the model. The results show that the proposed control strategy can make the real part of the oscillation mode move left and increase the total damping. The electromagnetic transient simulation model of wind power through DC transmission system with zero sequence current control strategy is constructed. The simulation results show that the proposed strategy greatly increases the damping level of the system, improving the stability.
2024(1):243-250, DOI: 10.19781/j.issn.1673-9140.2024.01.025
Abstract:
Based on the VIENNA rectifier front-end circuit of the electric vehicle DC charging pile, a small signal method is proposed to model the VIENNA rectifier. This method derives the mathematical model of the VIENNA rectifier in the dq0 coordinate system by employing local linearization techniques and state-space averaging method. It obtains the relevant transfer function matrix, namely the linearized small-signal model of the VIENNA rectifier, which is then utilized for controller design. Subsequently, the voltage loop and current loop are designed separately using frequency domain methods. The effects of various parameters on the system are analyzed in detail using frequency domain methods and root locus plots. Additionally, curves describing the changes in the system's stability region with respect to various parameters are provided through curve fitting. Finally the correctness of the proposed method is verified through the experiments.
Based on the VIENNA rectifier front-end circuit of the electric vehicle DC charging pile, a small signal method is proposed to model the VIENNA rectifier. This method derives the mathematical model of the VIENNA rectifier in the dq0 coordinate system by employing local linearization techniques and state-space averaging method. It obtains the relevant transfer function matrix, namely the linearized small-signal model of the VIENNA rectifier, which is then utilized for controller design. Subsequently, the voltage loop and current loop are designed separately using frequency domain methods. The effects of various parameters on the system are analyzed in detail using frequency domain methods and root locus plots. Additionally, curves describing the changes in the system's stability region with respect to various parameters are provided through curve fitting. Finally the correctness of the proposed method is verified through the experiments.
2024(1):251-259, DOI: 10.19781/j.issn.1673-9140.2024.01.026
Abstract:
With the permeability increase of renewable energy, the interaction between power electronic converters and power grid causes oscillation accidents frequently. In order to study the characteristics of oscillation induced by grid-connected new energy sources, this paper explains the mechanism that a single-frequency disturbance voltage as input to a single-phase inverter considering the PLL effect leads to double-frequency disturbance current as output, through the relationship of real number signal and complex vector. The mechanism of frequency coupling in weak power grid is further explained. The models of self-admittance and mutual-admittance are established, and the equivalent output admittance of inverter is then derived. Finally, the correctness of the self-admittance and mutual-admittance models are verified by MATLAB/Simulink. The equivalent output impedance of inverter can be utilized to judge the stability of an interconnected system according to the Nyquist stability criterion.
With the permeability increase of renewable energy, the interaction between power electronic converters and power grid causes oscillation accidents frequently. In order to study the characteristics of oscillation induced by grid-connected new energy sources, this paper explains the mechanism that a single-frequency disturbance voltage as input to a single-phase inverter considering the PLL effect leads to double-frequency disturbance current as output, through the relationship of real number signal and complex vector. The mechanism of frequency coupling in weak power grid is further explained. The models of self-admittance and mutual-admittance are established, and the equivalent output admittance of inverter is then derived. Finally, the correctness of the self-admittance and mutual-admittance models are verified by MATLAB/Simulink. The equivalent output impedance of inverter can be utilized to judge the stability of an interconnected system according to the Nyquist stability criterion.
2024(1):260-271, DOI: 10.19781/j.issn.1673-9140.2024.01.027
Abstract:
Aiming at the open-circuit fault of the photovoltaic grid-connected three-phase voltage-type inverter,.a fault diagnosis method combining deep cascade mode-principal component analysis (DCM-PCA) and genetic algorithm-optimized BP(GA-BP) neural network is proposed. Firstly, the open-circuit fault of the inverter is analyzed and simulated, the three-phase current is determined as the fault signal, and 22 types of fault states are selected as the diagnosis objects, and the fault features are extracted through the deep cascade model with sparse representation classification as the basic operation unit, the DCM fault features are stratified based on the characteristics of hierarchical learning. The t-SNE method is used to verify that DCM has good feature extraction ability. PCA is used to reduce the redundancy of fault features, retain valuable principal components to improve the network mapping ability. Finally, the fault feature vector is used as the input of the GA-BP neural network to identify the fault and output the diagnosis result. The fault diagnosis accuracy of this method is 95.64% through simulation and experiments, compared with the DCM-PCA-BP, FFT-GA-BP and FFT-BP, the accuracy is increased by 8.71%, 20.64% and 51.70% respectively, indicating that the proposed method has better fault feature extraction capability and better fault diagnosis performance.
Aiming at the open-circuit fault of the photovoltaic grid-connected three-phase voltage-type inverter,.a fault diagnosis method combining deep cascade mode-principal component analysis (DCM-PCA) and genetic algorithm-optimized BP(GA-BP) neural network is proposed. Firstly, the open-circuit fault of the inverter is analyzed and simulated, the three-phase current is determined as the fault signal, and 22 types of fault states are selected as the diagnosis objects, and the fault features are extracted through the deep cascade model with sparse representation classification as the basic operation unit, the DCM fault features are stratified based on the characteristics of hierarchical learning. The t-SNE method is used to verify that DCM has good feature extraction ability. PCA is used to reduce the redundancy of fault features, retain valuable principal components to improve the network mapping ability. Finally, the fault feature vector is used as the input of the GA-BP neural network to identify the fault and output the diagnosis result. The fault diagnosis accuracy of this method is 95.64% through simulation and experiments, compared with the DCM-PCA-BP, FFT-GA-BP and FFT-BP, the accuracy is increased by 8.71%, 20.64% and 51.70% respectively, indicating that the proposed method has better fault feature extraction capability and better fault diagnosis performance.
2024(1):272-284, DOI: 10.19781/j.issn.1673-9140.2024.01.028
Abstract:
In response to the phenomena of significant oscillations and incomplete noise reduction when dealing with partial discharge signals using traditional methods, a combined approach based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and tunable Q-factor wavelet transform (TQWT) is adopted to denoise the PD signals. Firstly, the CEEMDAN is employed to decompose the noisy transformer PD signals into multiple intrinsic mode functions (IMF), and the correlation coefficient is utilized to assess the correlation between the IMF components and the original signal. Those with weak correlations are considered inferior IMFs. They are decomposed using TQWT. Energy proportion and kurtosis indicators are utilized to select wavelet sub-bands, extracting effective detailed information from the IMF. Subsequently, inverse transformation of the TQWT is applied to obtain new IMF components. The IMFs with strong correlations are considered high-quality. They are reconstructed together with the transformed new IMF components to obtain the denoising result. Simulation and field signal analysis verify the effectiveness and practicability of the proposed method. Compared to the traditional empirical mode decomposition(EMD) method, the percentage of waveform distortion decreased by 44.94% after denoising simulated signals using the proposed method. Compared to using only CEEMDAN, the noise suppression ratio increases by 26.64% after denoising on-site signals using the proposed method.
In response to the phenomena of significant oscillations and incomplete noise reduction when dealing with partial discharge signals using traditional methods, a combined approach based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and tunable Q-factor wavelet transform (TQWT) is adopted to denoise the PD signals. Firstly, the CEEMDAN is employed to decompose the noisy transformer PD signals into multiple intrinsic mode functions (IMF), and the correlation coefficient is utilized to assess the correlation between the IMF components and the original signal. Those with weak correlations are considered inferior IMFs. They are decomposed using TQWT. Energy proportion and kurtosis indicators are utilized to select wavelet sub-bands, extracting effective detailed information from the IMF. Subsequently, inverse transformation of the TQWT is applied to obtain new IMF components. The IMFs with strong correlations are considered high-quality. They are reconstructed together with the transformed new IMF components to obtain the denoising result. Simulation and field signal analysis verify the effectiveness and practicability of the proposed method. Compared to the traditional empirical mode decomposition(EMD) method, the percentage of waveform distortion decreased by 44.94% after denoising simulated signals using the proposed method. Compared to using only CEEMDAN, the noise suppression ratio increases by 26.64% after denoising on-site signals using the proposed method.
Display Method:
显示方式：3
Display Method:
,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.
,36(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.
,36(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):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.
,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(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(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.
,36(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):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):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):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):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):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):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):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):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):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.
