基于遗传算法的微电网DSM优化模型

为降低微电网发电侧运行成本, 同时优化微电网需求侧用户的用电体验, 建立了将需求侧管理(DSM:Demand Side Management)纳入微电网经济优化的模型。该模型包括一个光伏发电装置, 两个柴油发电机和一个蓄电池, 需求侧用户根据动态定价机制作出响应并对负荷进行转移, 以节省电费。将用户感到的不便与负荷转移时间建立联系, 运用遗传算法同时优化发电侧经济性和需求侧用户体验。仿真结果表明, 实施DSM 后,发电成本显著降低, 用户获得了一定的经济效益。

Optimization of Micro-Grid with DSM Based on Genetic Algorithm

To lower the cost of generation and optimization for electric customers experience, an economic scheduling model for a micro-grid is proposed considering DSM(Demand Side Management) with one solar source, two diesel generators and one battery. Demand-side electric customers respond to the dynamic pricing mechanism and transfer the load to achieve the purpose of saving electricity costs. Connecting the inconvenience caused to the customer with the duration of shifting and using genetic algorithm to minimize inconvenience and electricity costs of customer. The simulation results show that the cost of generation is less with DSM compared to the case without DSM and there is savings for the customer.