基于虚拟电价的含电动汽车并网型微网经济调度策略

Economic dispatching strategy of grid-connected micro grid with electric vehicles based on virtual electricity price

中文关键词: 并网型微网  电动汽车  动态虚拟电价  改进粒子群算法  经济调度

英文关键词: grid-connected micro grid  electric vehicle  dynamic virtual electricity price  improved particle swarm optimization algorithm  economic dispatch

中文摘要:

      大规模可再生能源和电动汽车接入微网，可再生能源出力的波动性和电动汽车充放电行为的无序性会导致微网弃风弃光严重，也给微网的经济调度带来了挑战。在传统峰谷电价基础上结合可再生能源出力及等效负荷的功率差额提出了含电动汽车并网型微网经济调度策略。首先根据微网可再生能源和负荷功率水平分析微网调度优先级。以微网的运行成本最小和最大化消纳光伏为目的，构建虚拟花费最小的目标函数优化模型。最后在实例中采用改进的粒子群算法进行求解，对比采用动态虚拟电价和传统峰谷电价、实时电价3种方式下微网一个调度周期的光伏利用率、负荷峰谷差、微网的运行成本来验证所提方法的有效性。

英文摘要:

      Large scale renewable energy and electric vehicles are connected to the micro grid. Due to the fluctuation of renewable energy output and the disorderly charging and discharging behavior of electric vehicles, the wind and light electricity are seriously abandoned in the micro grid, which also brings challenges to the economic dispatching of the micro grid. Based on the traditional peak-valley electricity price and combined with the power difference between renewable energy output and equivalent load, the economic dispatching strategy of grid - connected micro - grid containing electric vehicles is proposed. Firstly, the scheduling characteristics of micro grid are analyzed. Then, the scheduling priority of micro grid is analyzed in combination with renewable energy and load power level of micro grid. With micro network operation costminimum and maximum given photovoltaic, the purpose of building virtual of the objective function is minimum cost optimization model. Finally, the improved particle swarm algorithm is used to solve the case. The case is studied under three different pricing mechanisms of dynamic virtual price、traditional peak valley price and real -time electricity price micro network. The effectiveness of the proposed method is verified by comparing the photovoltaic utilization rate, load peak valley difference and operation cost of microgrid in one dispatching cycle under three pricing methods.