一种含风电-电池储能的多场景输电网规划方法

以可再生新能源(如风电、光伏)及化学电池为载体的电源系统已为航天器及电动机等用电客户提供了一种有效供电方式。针对风电的不确定性以及电池储能系统功率双向流动特性，尤其是风电的波动性与间歇性对输电网规划的影响，采用多场景概率法以风电场的风速数据作为划分依据，以风机的切入风速、切出风速以及额定风速的组合区间作为划分区间，利用Monte Carlo方法来计算场景概率，以输电网规划建设成本与过负荷费用最低为目标函数，设计了一种含风电-电池储能的输电网扩展规划模型，并采用遗传算法对规划模型进行求解。最后，以Garver-6节点系统为仿真算例，验证所设计规划方法的有效性。仿真结果表明，接入储能系统后,其输电网规划适应度很小(约为900)，可提高系统经济效益。

A Multi-scenario Transmission Network Planning Method with Wind Power and Battery Energy Storage

As one of the valid alternatives, the power system with chemical battery and renewable sources, such as wind and photovoltaic, is widely applied to support the space vehicles and the motions. To considering the uncertainty of the wind power and the bidirectional flow power of the battery energy storage, especially the influence of the intermittence and fluctuation of the wind power on transmission network planning, a transmission network planning method based on multi-scenario probability theory is developed in this paper. The wind speed data of the wind farm is analyzed and divided into various scenarios based on cut-in power speed and cut-out power speed and rated power speed. The probability of various scenarios is calculated by the Monte Carlo method. To minimize the cost of transmission network construction and over load, a transmission network planning model including the wind power and the battery energy storage is designed, and the planning model is solved by the genetic algorithm. Finally, the validity of the developed model is verified in the Garver-6 system. Moreover, the simulation results show that the fitness of the transmission network planning converges to a small value (about 900), which can increase the system economic benefits.