含光伏发电的配电网动态无功优化研究

摘要

A large number of photovoltaic power generations were applied in power distribution network in recent years, but its random output led to the inaccurate power flow optimization results.In order to optimize the power flow of distribution network containing photovoltaic power generations with the load changing and reduce the power loss, the paper proposed a method which divided the photovoltaic power generation and changeable load into 24 periods, used the genetic algorithm(GA) to calculate the static power flow in each period,and utilized dynamic programming(DP) with the ability of solving the problem of time sequence optimization, and built the action time table of the control e-quipment considering the minimum of power loss summation of each period as the objective function.In order to avoid complex calculations and simplify the operation, the method can not only ignore the invalid search path but also ensure voltage stability.The method model is simple and effective, can reduce the power loss under the conditions that the numbers of capacitors actions are under constraints and increase the life of the capacitors.Numerical results show that the proposed method is feasible and effective, and can achieve the expected purpose.%近些年光伏发电在配电网中得到大量的应用，但由于其出力带有一定的随机性，使得潮流优化结果不准确。为了能够在负荷变化的同时准确地优化含光伏发电的配电网潮流以降低网损，文中将一天内的光伏出力和负荷的变化分成24段，利用遗传算法将各时段进行静态潮流计算，利用动态规划法具有解决时间序列优化问题能力的特点，以各时段的网损值之和最小为目标函数，建立设备的动作时间表。为了避免运算复杂，简化运算的步骤，忽略无效的搜索路径同时也保证了电压稳定性。该方法的模型简单有效，且保证了电容器组的动作次数在约束限制下降低网损，减少电容器的损耗。通过算例结果表明该运算方法可行有效，可达到预期目标。