采用随机约束和多目标算法的电动汽车换电站能量管理

Energy management with stochastic constraint and multi-objective optimization algorithm for electric vehicle battery swap station

针对电动汽车换电站的能量管理进行优化。由于实时电价环境下电动汽车换电站的能量管理具有一定的风险性,因此所建的模型考虑了电动汽车换电需求和市场电价的不确定性,是以运行成本的期望和方差为目标的电动汽车换电站的能量管理模型,并采用基于免疫克隆选择的多目标智能优化算法进行求解。算例仿真结果表明通过所提出的模型可以实现电动汽车换电站购电成本的降低,并通过负荷转移给电网带来好处。

The optimization of energy management for electric vehicle battery swap station is researched. Because the energy management of electric vehicle battery swap station has a certain risk ,its model,built with the consideration of the uncertainties in electricity price and power demand,takes the expectation and variance of cost as its objectives and solved by a multi-objective optimization algorithm based on immune clone method. Simulative results show that,the electricity purchase cost of battery swap station is lowered by the optimized energy management and the power network obtains benefit by the load transfer.