基于多种群协同进化遗传算法的智能小区需求响应调度策略

Demand response dispatching strategy for intelligent community based on multi⁃group co⁃evolution genetic algorithm

中文关键词: 智能小区  电动汽车  储能系统  优化调度

英文关键词: intelligent community  electric vehicle  energy storage system  optimized dispatching

中文摘要:

      针对包含多种用能资源的智能小区中需求响应调度问题，首先建立储能、光伏和电动汽车的优化模型，目标函数设置为系统和电网的交换电量和总运行费用最小。然后利用多种群协同进化遗传算法优化结果。最后，以某智能小区为例，利用MATLAB工具对负荷模型进行仿真分析，验证所建模型的正确性和可行性，结果表明所设计的策略提高了光伏消纳率，降低了小区的运行费用。

英文摘要:

      For the demand response scheduling problems in an intelligent community containing multiple energy resources, the optimal model is firstly established concerning energy storage, photovoltaic and electric vehicles. The objective function is the minimum exchange quantity and total operation cost between the system and the grid. Then the multi?group collaborative purification genetic algorithm is used to obtain the optimization result. Finally,taking a smart community as an example, MATLAB tool is used to simulate the load model and verify its correctness and feasibility. It shows that the proposed strategy improves the PV consumption rate and reduces the operating cost.