低碳化背景下配电网“源—储—荷”多目标优化配置
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TM715

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福建省中青年教师教育科研项目(JA14064)


Multiobjective optimal allocation of "generationstorageload" under the lowcarbon background
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    摘要:

    清洁能源的分布式电源(DG)及电动汽车(EV)的利用是低碳化背景下实现可持续发展的关键部分。为降低DG出力及电动汽车充电负荷波动性对配电网的不良影响,首先,在规划阶段引入分布式储能系统(DESS),建立DG、DESS及电动汽车充电站(EVCS)的协调优化配置模型。其次,引入碳减排量指标,建立考虑配电网综合收益、碳减排量、电压质量指标、综合净负荷波动指标及网络损耗的多目标函数,并采用粒子群—和声搜索混合算法进行模型的求解。最后,以IEEE 33节点配电系统为例进行仿真验证,结果表明,所建立的“源—储—荷”联合规划模型能够有效降低系统碳排放量及网损,改善电压质量及负荷波动指标。

    Abstract:

    Distributed generation (DG) and electric vehicle (EV) are the key parts of sustainable development under the lowcarbon background. In order to reduce the negative impact of DG output and electric vehicle charging load volatility on the distribution network, a distributed energy storage system (DESS) is introduced in the planning stage to establish a coordinated and optimized configuration model of DG, DESS and electric vehicle charging stations(EVCS). By introducing the carbon emission reduction index, a multiobjective function is established. The comprehensive income of the distribution network, carbon emission reduction, voltage quality index, comprehensive net load fluctuation index and network loss are considered. Then, the particle swarmharmony search hybrid algorithm is applied to solve the model. Lastly, an IEEE 33bus power distribution system is simulated, it is shown that the established "generationstorageload" joint planning model can effectively reduce system carbon emissions and network losses, and also improve voltage quality and load fluctuation indicators.

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黄宗龙,江修波,刘丽军.低碳化背景下配电网“源—储—荷”多目标优化配置[J].电力科学与技术学报,2020,35(5):36-45.
HUAGNZ Zonglong, JIANG Xiubo, LIU Lijun. Multiobjective optimal allocation of "generationstorageload" under the lowcarbon background[J]. Journal of Electric Power Science and Technology,2020,35(5):36-45.

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