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基于协同演化博弈算法的微网和配电网动态优化
引用本文:徐意婷,艾 芊,胡剑生.基于协同演化博弈算法的微网和配电网动态优化[J].电力系统保护与控制,2016,44(18):8-16.
作者姓名:徐意婷  艾 芊  胡剑生
作者单位:上海交通大学电子信息与电气工程学院,上海 200240,上海交通大学电子信息与电气工程学院,上海 200240,许继集团有限公司,河南 许昌 461000
基金项目:国家自然科学基金项目(51577115)
摘    要:微网和配电网在互动运行时是相互影响、相互制约的。为了使整个系统获得最好的效益,需要整合考虑微网和配电网的效益。微网和配电网作为两个需要同时优化的主体,具有一定的效益冲突。研究微网和配电网互动运行时相互影响情况,分别分析其运行效益,将效益目标作为虚拟博弈参与者建立了模型,并采用模糊数学方法将其隶属化。结合演化博弈理论和协同进化算法,提出了一种协同演化博弈算法(Co-evolutionary Game Algorithm,CGA)对模型进行求解。在此基础上,考虑分布式能源随机性影响建立了基于不满意度的动态优化子模型,对协同演化博弈算法进行动态调整。对某一欧洲典型微网接入IEEE 33配电网结构的系统进行仿真,并且与传统的多目标优化方法进行对比。结果表明,最终优化稳定策略可以使微网和配电网整体达到最佳运行状态,证明了所提模型和算法的有效性和优越性。

关 键 词:微网  配电网  协同演化博弈算法  动态优化
收稿时间:2015/9/22 0:00:00
修稿时间:2015/11/4 0:00:00

Dynamic optimization of microgrid and distribution network based on co-evolutionary game algorithm
XU Yiting,AI Qian and HU Jiansheng.Dynamic optimization of microgrid and distribution network based on co-evolutionary game algorithm[J].Power System Protection and Control,2016,44(18):8-16.
Authors:XU Yiting  AI Qian and HU Jiansheng
Affiliation:School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University,Shanghai 200240, China,School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University,Shanghai 200240, China and XJ Group Corporation, Xuchang 461000, China
Abstract:Microgrid and distribution network have mutual influences and constraints when interactive operation. Thus, it is necessary to integrate interests of microgrid and distribution network together in order to benefit the entire system. Microgrid and distribution network, as two objectives that need to be optimized at the same time, have some conflicts of interests. The interaction of microgrid and distribution network is studied when interactive operation to analyze their operation benefits respectively. The benefit objectives are modeled as virtual game participants to establish models and fuzzy mathematics method is applied to generalize the benefit functions to membership. In combination with evolutionary game theory and cooperative co-evolutionary algorithm, a co-evolutionary game algorithm is proposed to solve the problem. Then, a maximum dissatisfaction based dynamic optimal sub-model considering the randomness of distributed energy is established to make dynamic adjustments in co-evolutionary game algorithm. A typical Europe microgrid connected with IEEE 33 distribution network is simulated and a simulation with multi-objective optimization method is also carried out for comparison. The results show that the final optimal stable strategy allows the entire microgrid and distribution network to achieve the best operation, thus the effectiveness and superiority of the proposed model and algorithm are proved. This work is supported by National Natural Science Foundation of China (No. 51577115).
Keywords:microgrid  distribution network  co-evolutionary game algorithm  dynamic optimization
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