工业园区参与调峰的电池储能-需求响应联合规划

工业园区理论上具备很大的调峰潜力，但由于峰谷分布不规律、多方利益交互、规划与运行高度耦合等因素导致难以实现有效规划。文中旨在探索工业园区主动参与调峰的经济性与可行性，提出运用电池储能和需求响应作为两类主要调峰手段，构建了兼顾考虑设备配置与运行调度优化的双层规划优化模型。在经济性方面，对工业园区参与调峰过程中的各种成本效益进行量化建模，并分析了与电网公司、政府之间的利益交互。在不确定性处理方面，联合运用蒙特卡洛模拟法与K-means聚类法生成多个调峰场景以提高规划结果准确性。选取广东省某工业园区作为算例，验证了所提方法的可行性与有效性。

Joint Planning of Battery Energy Storage and Demand Response for Industrial Park Participating in Peak Shaving

Industrial parks theoretically have great potential for peak shaving, whereas it is difficult to achieve effective planning due to the irregular distribution of peak and valley, multi-interest interaction, high coupling of planning and operation, etc. This paper aims at exploring the economy and feasibility of industrial parks participating in peak shaving via two main approaches, i. e. battery energy storage system(BESS)and demand response. A bi-level optimization model is built which considers both device configuration and economic dispatch optimization. Cost and benefit of industrial parks in the process of peak shaving are quantitatively modeling, and the interests interacting with the power supply companies and governments are analyzed. In terms of uncertainty processing, Monte Carlo simulation and K-means clustering method are jointly applied to form multiple peak shaving scenarios for improving the accuracy of planning results. Finally, the feasibility and effectiveness of the proposed method are verified on an industrial park in Guangdong Province of China.