一种基于点估计的风电并网位置和容量优化方法

Point-Estimation Based Method for Optimizing Both Location and Capacity of Grid-Connected Wind Farm

风电输出的随机波动性对并网系统的实时运行状态会产生影响,优化系统典型运行方式下的风电并网位置和容量对降低系统的静态安全风险、保证运行经济性具有重要作用。文章考虑电网源荷不确定性,以及风速间、负荷间相关性,利用点估计结合Nataf逆变换生成随机相关性样本的方法,研究了风电并网系统考虑随机相关性的点估计概率潮流计算方法。进而以减小电网网损率和节点电压平均偏移为目标,通过把所研究概率潮流嵌入自适应粒子群算法,同时避免点估计方法求解概率潮流对约束条件的偏乐观性,提出了合理规划风电并网位置和容量的优化方法。最后利用IEEE 57节点系统仿真算例验证了所提优化方法的有效性。仿真结果表明了考虑随机相关性对提高优化结果可靠度的必要性。

Due to the random fluctuation of wind power having impact on the real-time operation state of power system,reasonable optimization of both location and capacity of grid-connected wind farm under the classical operation mode should be considered.It is benefitial for both reducing the static safety risk and improving the economic operation of the grid.Considering the uncertainty of both power-source side and load side,the correlation of different wind speed and the correlation of different loads,a probability power flow calculation method considering the correlation of random variables is studied in this paper,which generates the correlation samples by combing point estimation and inverse Nataf transform.Moreover,through embedding the point-estimation based algorithm for probabilistic power flow,which considers the random correlation,into the adaptive particle swarm optimization algorithm,and avoiding the optimism on the constraints caused by using the point estimation method to solve the probabilistic power flow,taking the minimization of both the active power loss rate of the grid and the average deviation of bus voltages as the objective,the method for reasonably planning both the location and capacity of grid-connected wind farm is presented.Finally,the effectiveness of the proposed optimizing method is validated by the simulation carried out on the IEEE 57-node system.At the same time,the simulation result also shows the necessity of improving the reliability of the optimizing result by considering the correlation of the random variables.