基于改进乌鸦搜索算法的微电网多目标优化

摘要

为响应国家节能减排的号召，对微电网中分布式电源的出力进行合理的发电调度，将经济成本最小和环境成本最低作为目标函数，并建立数学模型，才用改进的乌鸦搜索算法(GCSA)对该模型进行求解。通过案例仿真并与传统的乌鸦搜索算法(CSA)、遗传算法(GA)和粒子群算法(PSO)相比，验证了所提模型及算法能够有效地降低经济成本和环境成本，改进的乌鸦搜索算法具有更好的寻优能力。 In response to the national call for energy conservation and emission reduction, the distributed power output in the micro-grid is to be dispatched reasonably; while the lowest economic cost and the environmental cost are taken as the objective function, so as to establish mathematical models, as well as adopting the improved crow search algorithm (GCSA) to solve the model. Based on case simulation and compared with the traditional crow search algorithm (CSA), genetic algorithm (GA) and particle swarm optimization (PSO), it is verified that the proposed model and algorithm can ef-fectively reduce economic and environmental costs. In addition, the improved crow search algorithm (GCSA) has better optimization capabilities.