基于乌鸦搜索算法的孤岛微网多目标优化调度

Multi-objective Optimal Operation of Islanded Microgrid Based on Crow Search Algorithm

为促进孤岛微网中可再生能源的消纳,减小负荷峰谷差。文中在孤岛微网中引入价格型需求响应,以微网运行成本最低和柴油发电机出力最少为目标,综合考虑功率平衡、抽水蓄能机组启停与工况转换等约束条件,构建了含风电、抽水蓄能和柴油发电机的孤岛微网多目标优化调度模型,并采用乌鸦搜索算法进行求解。仿真结果表明:在孤岛微网中引入价格型需求响应能有效削减负荷峰谷差,经济效益显著。与粒子群优化算法相比,乌鸦搜素算法在收敛速度和全局寻优的能力上具有明显优势。

In order to promote the renewable energy accommodation of insular island microgrid and reduce the load peak and off-peak difference.In this paper the islanded microgrid introduced price-based demand response,with minimized the cost of operation and diesel generator output as the objective function,considering the constraints of power balance,unit startup-shutdown and state change of pumped storage.A multi objective optimal operation model for insular island microgrid is established,and solved using crow search algorithm(CSA).The simulation results show that the introduction of price-based demand response in the insular island microgrid can effectively reduce the load peak and off-peak difference,and the economic benefit is remarkable.Compared with the particle swarm optimization(PSO)algorithm,the crow search algorithm has obvious advantages in the ability of convergence speed and globaloptimization.