分布式能源接入下虚拟电厂负荷优化调度决策

doi:10.3969/j.issn.2097-0706.2025.01.008

摘要/Abstract

摘要：

针对分布式能源接入带来的电网特性变化和优化调度复杂性增加问题，以电动汽车（EV）为研究对象，探讨了其在虚拟电厂负荷优化调度中的潜在作用。基于构建的EV充电行为上、下界，建立了电动汽车聚合体（EVA）的功率容量预测模型，为虚拟电厂负荷优化调度提供了保障。考虑到EV具有不同的功率调节动态响应特性，提出了基于改进后自组织映射（SOM）算法的EV聚类方法，并使用Davies-Bouldin指数来评估聚类效果，以保证不同功率调节特性下EV聚类的准确性。进一步考虑风电接入和电动汽车并网可能带来的不利影响，以及功率平衡等多方面约束，构建了虚拟电厂的负荷优化调度决策模型。仿真结果表明，该虚拟电厂负荷优化调度决策模型保证了合理分配EVA容量情况下电网的安全运行。

关键词: 分布式能源, 虚拟电厂, 负荷优化调度, 电动汽车, 智能电网, Davies-Bouldin指数, 改进的SOM算法, 综合能源

Abstract:

Aiming to solve the problems of the variation in load characteristics and the complication in optimization scheduling caused by distributed energy access，the potential role of electric vehicles（EVs）in load optimization scheduling of virtual power plant is discussed. Firstly，the upper and lower bounds of EV charging behavior are defined，and the power and capacity prediction model of EV aggregates is constructed based on the behavior boundary，providing guarantee for the load optimal scheduling of virtual power plants. Considering that EVs have different dynamic response characteristics in power regulation，an EV clustering method based on an improved SOM algorithm is proposed. The Davis-Bouldin index is used to evaluate its clustering result，so as to ensure the accuracy of EV clustering with different power regulation characteristics. Further，considering the adverse effects of wind power and grid-connected EVs，power balance and other constraints，the load optimization scheduling model for virtual power plants is constructed. Finally，the simulation results show that the virtual power plant load optimization scheduling model can ensure the safe operation of power grid，given the circumstances that the capacities of EV aggregates are reasonably allocated.

Key words: distributed energy, virtual power plant, load optimal scheduling, electric vehicle, smart grid, Davies-Bouldin index, improved SOM, integrated energy

中图分类号:

TK01

胡嘉诚, 张宁, 曹雨桐, 胡存刚. 分布式能源接入下虚拟电厂负荷优化调度决策[J]. 综合智慧能源, 2025, 47(1): 62-69.

HU Jiacheng, ZHANG Ning, CAO Yutong, HU Cungang. Load optimization scheduling decision for virtual power plants with distributed energy accessed[J]. Integrated Intelligent Energy, 2025, 47(1): 62-69.

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聚类算法	DBI	计算时间/s
改进的SOM算法	0.721 5	80.57
k-means算法	1.837 4	20.34
SOM算法	0.844 5	124.51