基于奇异值分解和等效电流量测变换的电力系统状态估计

摘要

Aiming at the state estimation's disadvantage in dealing with ill-conditioned problems, an algorithm is proposed based on singular value decomposition and equivalent current measurement transformation. The proposed algorithm utilizes the hybrid measurement system which consists of PMU measurement and SCADA measurement By means of the right-angle coordinate's equivalent current measurement transformation, the state estimation problem can be formulated as linear measurement equations and the information matrix is constant. After that, singular value decomposition is used to solve the measurement equations only once, which increases the calculation efficiency. The singular value decomposition doesn't need observability analysis and can deal with ill-conditioned or close to ill-conditioned problems, which improves the state estimation algorithm's robustness. Through the simulation test, the validity of this method is verified.%针对电力系统状态估计中处理病态问题的不足,提出一种基于奇异值分解和等效电流量测变换的状态估计方法.该方法利用PMU和SCADA量测构成的混合测量系统,运用直角坐标形式等效电流量测变换技术处理节点注入功率量测和支路功率量测,把信息矩阵转换成常数矩阵,再运用奇异值分解求解量测方程.在迭代求解中只需进行一次奇异值分解,提高了算法的计算效率.奇异值分解无需对系统进行可观性分析,能很好地处理病态或接近病态问题,使系统鲁棒性增强.通过仿真测试,验证了所提方法的正确性和有效性.