计及电动汽车和风光资源不确定性的微电网优化配置

Optimal configuration of micro-grid considering uncertainties of electric vehicles and PV/wind sources

电动汽车(electric vehicles,EVs)的规模化并网和风光等可再生能源的不稳定出力,给微电网电源容量优化带来更多不确定性影响。利用分时电价机制引导和蒙特卡洛方法模拟不同管理模式下的EV负荷,采用场景生成和K均值聚类算法构造风光典型场景集,以年总经济成本最优为目标函数,经粒子群算法优化得出含EV的微电网容量配置方案。仿真结果表明,考虑风光资源不确定性的配置方案能提高微电网的可靠性;有效的能量管理模式可以发挥EV的削峰填谷作用,降低EV用户年充放电成本和微电网年总经济成本。

The optimal configuration of power capacity in micro-grid has more uncertain influence with large-scale of electric vehicles （EVs） integrated into micro-grid and unstable renewable energy sources such as wind and solar ener- gy. The price incentive model and Monte Carlo method were applied to simulate different management modes of EV load. Based on scenario generation and K-medoids cluster, the configuration optimization would be done by using par- ticle swarm algorithm in typical scenarios with the objective to minimize the comprehensive cost. The simulation result validates that optimal configuration will increase the reliability of micro-grid considering randomness of wind and solar energy. And effective energy management mode can decrease the fluctuation of load, as well as reduce the annual costs of EV users and comprehensive costs of micro-grid.