中文摘要：

提出一种计及负荷不确定性等影响因素的无功优化模型与算法,以克服单一负荷水平下无功优化模型不能全面刻画其负荷随机特性的不足。该模型目标函数为系统有功功率损耗最小,并将节点电压越限和补偿设备的调节代价作为罚函数计及其中。以负荷正态随机分布特性为基础,将系统总负荷分段并得到多组负荷样本及其对应的概率值,对每一负荷样本分别进行优化,最后结合其对应的概率,即可得到不确定负荷下的最终解。针对无功优化多目标、多约束的特点,采用遗传算法对其进行求解。将问题的解转化为染色体组,通过对染色体组进行选择、交叉和变异等遗传操作,搜索问题的最优解。通过IEEE-30节点算例对所提出的方法进行了验证,结果验证了该模型和方法的可行性和有效性。

英文摘要：

A reactive power optimization model（ROM）and algorithm considering many factors including load uncertainty is proposed to overcome the shortage that the reactive power optimization model under the single load level can’t fully describe the random nature of load.The model takes the minimum of the power loss as objective function and takes account of the penalty functions which are limits of bus voltages and the adjusting cost of compensation equipments.The system load is divided to get several load samples and their corresponding probability based on the normal random distribution,each load sample is optimized separately and the final solution of uncertain load can be obtained combined with its corresponding probability.The reactive optimization which has the features of multi-objective and multi-constraint is carried out by the genetic algorithm.After transferring the solutions to the genome,the optimal solution is searched according to the selection,crossover and mutation on the genome.The results on IEEE 30-bus system demonstrate the feasibility and effectiveness of the proposed model and method.