不确定性条件下储能配置辅助决策方法

Auxiliary Decision-making Method of Energy Storage Configuration under Uncertainty

针对新能源消纳中储能电源配置问题,基于随机规划理论,建立了考虑需求场景不确定性的储能电源配置期望值模型,提出基于场景聚类和遗传算法相结合的模型求解算法步骤,并基于某典型区域电力系统进行算例分析,验证方法的可行性和有效性。研究表明:基于期望值模型的储能配置辅助决策方法能够较好地量化新能源功率波动带来的需求场景不确定性,实现目标期望值的最优化。

The research focused on the auxiliary decision-making problem of energy storage configuration.Firstly,an expected value model of energy storage(ES)configuration considering the uncertainty of demand scenario was established based on stochastic programming theory.And the corresponding algorithm steps of model solving based on scenarios clustering and genetic algorithm were proposed.A case study based on a typical regional power system was used to verify the feasibility and validity of the method mentioned above.The results show that this decision-making method of ES configuration based on expectation model can quantify the uncertainty of demand scenario caused by randomness of renewable energy generation,and optimize the target expectation value.