可再生能源富集区域计及条件风险价值的储能优化规划

Energy Storage Optimization Planning for Renewable Energy Enrichment Areas Considering Conditional Value-at-risk

新型电力系统双碳目标建设背景下,可再生能源富集区域与负荷中心在时空分布上的不均衡加剧了电网侧储能配置需求。针对可再生能源富集且规模化外送地区的储能优化配置问题,计及可再生能源出力、负荷不确定性导致的可再生能源外送通道利用率不足以及储能投资风险,建立储能选址定容优化规划模型。模型采用K-MILP场景聚类的条件风险价值度量上述不确定性导致的风险成本,表征系统净投资成本超过某一置信水平条件的尾部风险,并计及网架约束对可再生能源就地消纳及外送的影响;最后,将该模型转化为混合整数线性规划模型。算例结果表明,在储能优化规划中计及对储能投资风险的合理度量,有利于减少可再生能源出力极端场景导致的储能投资尾部风险,经济提升可再生能源本地和外送消纳能力。

Under the background of double carbon goal construction of the new power system,the disequilibrium of the spatial and temporal distribution of the renewable energy enrichment area and the load center aggravates the demand for energy storage configuration on the grid side.Aiming at the energy storage optimization configuration in large-scale renewable energy transmission areas,considering the insufficient utilization of renewable energy transmission channels and the risk of energy storage investment caused by the uncertainty of renewable energy output and load,an optimal planning model for energy storage location and capacity was established.Considering the influence of grid constraints on local consumption and transmission of renewable energy,the model used CVaR based on K-MILP scenario clustering to measure the risk cost caused by these uncertainties and characterized the tail risk that the net investment cost exceeds a certain confidence level.Finally,the model was transformed into mixed integer linear programming model.The results show that considering the reasonable measurement of energy storage investment risk in energy storage planning is conducive to reducing the tail risk of energy storage investment caused by extreme scenarios of renewable energy output,and improving the local and outbound consumption capacity of renewable energy economically.