基于自适应人工鱼群算法的微电网优化运行

Micro Grid Optimal Operation Based on Adaptive Artificial Fish Algorithm

针对含风、光、储、微型燃气轮机和燃料电池的并网和离网型微电网,综合考虑燃料、电能交互、投资折旧、维护及环境成本等变动成本,使系统在一个调度周期内的总运行成本最低,建立了微电网多目标经济优化模型。采用约束优化自适应人工鱼群算法(AFSA),求得一个调度周期内各分布式电源的最佳出力及运行总成本,并与基本人工鱼群算法求得的结果作对比。仿真结果表明:改进的算法具有收敛速度快和精度高的特点。

For the connected grid and isolated micro grids containing wind turbine, photovohaic cell, micro turbine fuel cell and energy storage system, considering comprehensively the changing costs of fuel, electricity exchange, investment depreciation, maintenance and environment, a model of multi-objective economic optimization micro--grid is built to make the operating cost of system the lowest in the scheduling period. Using the constrained optimization adaptive artificial fish swarm algorithm（AFSA）the optimal output and total operation cost of each micro power source in the scheduling period are obtained by calculation, and then compared with the results obtained with basic AFSA. The simulation example shows that the improved algorithm has the characteristics of quick convergence speed and high accuracy.