A Measurement Optimization Configuration Method Based on Investment Cost Constraints for Distribution Network

With the large-scale distributed generation connected to the distribution network, the observability of the distribution network is insufficient and the energy management ability is reduced. Considering investment cost constraints and state estimation accuracy requirements, it is crucial to realize the optimal configuration of distribution network measurement. In this paper, a measurement optimization configuration method considering investment cost constraints is proposed to obtain the measurement optimization configuration scheme with the high state estimation accuracy, which is to solve the measurement configuration problem with mixed integer nonlinear programming based on the ant colony algorithm. The results of case study analysis show that the proposed method can effectively improve the calculation efficiency and obtain better measurement configuration results. And it showed the computational performance of the proposed method is far superior to some popular other simplified calculation methods based on Fisher information and circuit representation error in terms of accuracy, computational efficiency, and scalability.