A fast heuristic optimization algorithm for measurement placement in distribution system state estimation

Abstract

An accurate, real‐time estimation of the states of a power distribution system is highly desirable but hard to achieve because of the complexity of the network and the relative inefficiency of the measuring system. To increase the efficiency, this paper analyzes the mathematical relationship between the measurement errors and estimation errors of the state vector using the classic weighted least square method. Then a heuristic algorithm is proposed to improve the accuracy by optimizing the deployment of the real‐time measuring points, which is based on the deterministic factors of the measuring points/branches over the system state. The basic implementation starts with an initial measurement set and replaces the least important branches in the set with the most important branches outside the set using iterative optimization. The algorithm was tested in the IEEE 14‐bus and 33‐bus distribution systems and achieved 50% increase in accuracy at much lower computational cost compared with exhaustive search. Moreover, the proposed algorithm has also been compared with representative and widely used evolution algorithms such as particle swarm optimization and quantum‐behaved particle swarm optimization. This comparison shows that our method can achieve stable and comparable accuracy with a speed at least 10 times higher. The performance of our method can be even better with increasing network size. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Resource‐Constrained Emergency Scheduling for Forest Fires with Priority Areas: An Efficient Integer‐Programming Approach

“…For example, the priority level of a fire point might change when some factors such as wind force, fuel types, and terrain slope vary over the emergency-scheduling horizon, extending the studied problem to a time-dependent one by considering time-dependent priorities of fire points is an important research direction and deserves more and deep study. Effective problem-specific heuristic algorithms should be developed for them [34][35][36][37][38][39][40]. Moreover, we may also extend the proposed model to multiobjective ones by simultaneously considering multiple objectives.…”