An Effective Approach for the Probabilistic and Deterministic Multistage PMU Placement Using Cuckoo Search: Iran's National Power System

Abstract

In recent years, phasor measurement units (PMUs) as vital elements have been widely increased in control, monitoring and protection of power systems. In practice, as the size of a power system is large, it is not possible to install all PMUs over a short period of time mainly due to the financial and technical barriers. One solution would be installing the PMUs over different stages. Accordingly, the paper presents an effective approach for multistage PMU placement (MSPP) in power systems, called dynamic MSPP. Furthermore, since the probabilistic concept of observability reflects a more realistic image of power system observability compared to deterministic ones, this paper, unlike most of the existing MSPP models, investigates the MSPP model in both probabilistic and deterministic frameworks. Compared to the existing approaches and results, the obtained ones in this paper show a considerable improvement in the observability level during PMU installation period. In the proposed approach, PMUs are installed at intermediate stages aimed at maximizing the cumulative network observability in a single optimization process, instead of several subsidiary optimizations in conventional approaches. Briefly, the proposed approach offers a complete search space for the problem, while the existing models lead to limited ones. Moreover, because of the nonlinearity posed by the probabilistic concept of observability as well as the proposed MSPP, cuckoo search optimization algorithm is used to handle the complexity and a new problem encoding/decoding technique for the proposed MSPP is utilized. Eventually, the suggested framework is implemented on different case studies as well as Iranian Transmission Network to reveal the performance of the presented model.