考虑风光不确定性和调峰主动性的多能互补系统优化调度

Optimization Scheduling of Multi-Energy Complementary Systems Considering Wind and Solar Uncertainty and Peak Shaving Initiative

摘要: 为促进清洁能源消纳，利用多种能源之间的互补特性，构建了水风光火储多能互补系统。考虑到风电和光伏出力的不确定性，采用蒙特卡洛场景抽样生成法与基于概率距离的场景缩减技术处理风电和光伏出力的不确定性，形成了含风光概率信息的典型场景。同时，为提高火电机组的调峰主动性，搭建了多能互补系统的机组调峰补偿与分摊模型，建立调峰主动性约束。考虑到水风光储系统与火电的优化方向不同，采用双层优化调度方案，上层模型以水风光清洁能源发电量最大、储能系统运行效益最大和余留负荷波动最小为目标函数，下层模型，以火电运行成本最小为目标函数，并基于分解协调思想，通过MATLAB平台调用CPLEX进行求解。最后，选取清水江区域多能互补系统进行算例分析，结果表明，提出的多能互补系统短期优化调度模型能有效提高风光能源利用率，降低弃风率和弃光率。

Abstract: To promote the consumption of clean energy, utilizes the complementary characteristics of multiple energy sources to construct a multi energy complementary system for water, solar, and fire storage. Considering the uncertainty of wind and solar power output, Monte Carlo scene sampling generation method and probability distance based scene reduction technology were used to deal with the uncertainty of wind and solar power output, forming a typical scenario containing wind and solar probability information. At the same time, in order to improve the peak shaving initiative of thermal power units, a multi energy complementary system unit peak shaving compensation and allocation model was built, and peak shaving initiative constraints were established. Considering the different optimization directions between water solar energy storage systems and thermal power systems, a double-layer optimization scheduling scheme is adopted. The upper layer model takes the maximum clean energy generation of water solar energy, the maximum operating efficiency of the energy storage system, and the minimum residual load fluctuation as the objective functions, while the lower layer model takes the minimum operating cost of thermal power as the objective function. Based on the decomposition coordination idea, CPLEX is called on the MATLAB platform for solution. Finally, a case study was conducted on the multi energy complementary system in the Qingshui River region, and the results showed that the proposed short-term optimization scheduling model for the multi energy complementary system can effectively improve the utilization efficiency of wind and solar energy, and reduce wind and solar curtailment rates.