부산대학교 도서관

This paper proposes a new method for robust state estimation in distribution systems. Distribution system state estimation (DSSE) is different from transmission system state estimation (TSSE) in a way that distribution systems have a much smaller number of measurements. As the conventional DSSE method, Weighted Least Squares (WLS) with pseudo-measurements have been proposed as research papers, but the accuracy of pseudo-measurements was not so good from a standpoint of network reconfigurations that imply network topology changes. In practice, it is not guaranteed that the redundancy of measurements is equal or more than unity in distribution systems. This paper focuses on the nest structure of DistFlow for distribution system power flow calculation and formulates DSSE as a nonlinear optimization problem. In this paper, Quantum Brain Storm optimization (QBSO) is proposed to solve the problem. It is one of the high-performance Evolutionary Computation methods in nonlinear optimization. Also, the cost function with the L 1 norm is employed to make the optimal solutions more robust. The effectiveness of the proposed method is tested in a sample system.