基于场景概率潮流的电力系统无功优化研究

Research on Reactive Power Optimization Based on Scenario Probabilistic Load Flow

多风电场出力的随机性和互相关性特点对电力系统无功优化调度有着不可忽视的影响。针对这一问题,提出一种基于场景概率潮流的电力系统无功优化方法。该方法将风电出力场景化,结合概率潮流计算,以系统有功网损、发电机无功偏差和节点电压偏差期望加权值最小作为无功优化目标函数,利用粒子群算法求得各风电出力场景下的最优无功控制策略。在含多风电场的IEEE 30节点系统中对所提方法进行测试,并与确定性的场景无功优化方法相对比,验证了所提方法的有效性。

The randomness and cross- correlation of wind farms output have a negligible impact on reactive power optimization scheduling of power system. Aiming at this problem,a reactive power optimization method based on scenario probabilistic load flow is proposed. The wind farm output is scenarized in this method. Combining with the probabilistic load flow,it takes the minimum weighted value of system network loss expectation,generator reactive power and node voltage deviation expectation as the target function and uses the particle swarm optimization to get the optimal reactive power control strategy in each scene.The proposed method is tested in IEEE 30 node system including wind farms and compared with the deterministic scenarios optimization method. The simulation results demonstrate the effectiveness of the proposed method.