基于多模态多目标果蝇优化的风光燃储微网优化调度

Optimal Scheduling of Wind,Photovoltaic,Gas Turbines and Energy Storage Microgrid Based on Multimodal and Multi-objective Drosophila Optimization

为了实现风光燃储微电网经济环保优化运行,提出了基于种群分区多模态多目标果蝇优化的微网优化调度算法。引入可平移负荷和可中断负荷响应,建立了以风光燃储微电网的运行经济成本和环境污染成本最小为目标函数的多目标优化模型。模型的求解采用三分区的多策略多模态多目标果蝇优化算法——将果蝇种群分为3个区并引入特殊拥挤距离,自适应地调整收敛性和多样性。与5种其他算法进行对比仿真实验,结果表明,所提出的风光燃储微网优化调度算法在全局最优求解、收敛性、多样性以及所得到的最优解集精度等方面具有明显的优势,能有效降低微电网优化的运行成本和环境成本。

In order to realize the economical and environmental optimization operation of wind,photovoltaic,gas turbines,and energy storage microgrids,a microgrid optimization scheduling algorithm based on population partitioning,multimodal and multi-objective drosophila optimization was proposed.By introducing translational load and interruptible load response,a multi-objective optimization model was established with the minimum economic cost and environmental pollution cost of the wind,photovoltaic,gas turbines and energy storage microgrid as the objective function.The model is solved using 3 partition multi strategy,multimodal,and multi-objective drosophila optimization algorithm,which divides the drosophila population into 3 regions and introduces special crowding distances to adjust convergence and diversity adaptively.Compared with 5 other algorithms,the simulation results show that the proposed optimization scheduling algorithm for wind,photovoltaic,gas turbines and energy storage microgrids has significant advantages in global optimization,convergence and diversity,as well as the accuracy of the obtained optimal solution set.It can effectively reduce the operating and environmental costs of microgrid optimization.