Abstract The dispatch of an integrated power system involves how to balance the interests of all participants and alleviate the negative effects of uncertainties. In this paper, a game-theoretic robust optimization approach for a small-scale integrated power system is proposed. This optimization approach consists of two stages, i.e. the day ahead dispatch stage and the realtime feedback correction stage. In the day ahead dispatch stage, a game theory based optimal algorithm is established to address the issue that participants in the power system have distinct objectives and their interests are in conflict. Using the gaming results of the day ahead dispatch, a realtime feedback correction algorithm is implemented to enhance the robustness of the power system against the uncertainties of renewable energy resources (RERs) and loads. It is shown that with the communication between the power plant, microgrids and independent end users, the Nash equilibrium can be reached after several iterations and the scheduling plan of each participant is obtained. Meanwhile, with the error prediction over a certain period prescribed in the future, the negative effects of uncertainties are extensively reduced. A small-scale power system is used as a case to illustrate the effectiveness of the proposed optimization approach.

中文翻译：

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小规模综合电力系统的博弈论鲁棒优化

摘要 综合电力系统调度涉及如何平衡所有参与者的利益，缓解不确定性带来的负面影响。在本文中，提出了一种针对小规模综合电力系统的博弈论鲁棒优化方法。这种优化方法包括两个阶段，即日前调度阶段和实时反馈修正阶段。在日前调度阶段，针对电力系统参与者目标不同、利益冲突的问题，建立了基于博弈论的最优算法。利用前一天调度的博弈结果，实施了实时反馈校正算法，以增强电力系统对可再生能源 (RER) 和负载的不确定性的鲁棒性。结果表明，通过发电厂、微电网和独立终端用户之间的通信，经过多次迭代可以达到纳什均衡，得到每个参与者的调度计划。同时，随着未来一定时期的误差预测，不确定性的负面影响得到了广泛的降低。以一个小规模电力系统为例来说明所提出的优化方法的有效性。