Affiliations: [a] Department of Electrical and Electronics Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamilnadu, India
| [b] Department of Electrical and Electronics Engineering, PSNA College of Engineering and Technology, Dindigul, Tamilnadu, India
| [c] Department of Electrical and Electronics Engineering, National Institute of Technology Puducherry, Karaikal, India
Correspondence:
[*]
Corresponding author. K. Banumalar, Department of Electrical and Electronics Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamilnadu, India. Tel.: +91 9865899435; Fax: +91 4562 235111; E-mail: [email protected].
Abstract: This paper presents a new multi-objective problem formulation based optimal placement of Phasor Measurement Units (PMUs) considering the power system observability and reliability conditions. In this proposed method, Optimal Placement of PMUs (OPP) are determined to satisfy two objectives simultaneously such as minimizing the number of PMUs for achieving the complete observability and maximizing the reliability for better operation of power systems. Since the above two objectives are conflicting in nature, Fuzzified Clustered Gravitational Search Algorithm (FCGSA) is proposed to solve Multi-objective Optimal Placement of PMUs (MOPP) problem to provide a good tradeoff solution between the competing objectives. The fuzzy membership for each objective function is designed and proposed to determine the best solution of MOPP problem. Conventional rules are applied to minimize the number of PMUs and a new rule is developed to maximize the observability as well as reliability of the power systems. It helps the system operators to make necessary remedial actions to prevent the outage of the low reliability bus. The proposed method is validated on IEEE 14, 30 and 57 bus systems. The most effective strategy of allocating the optimal number of PMUs and their locations is demonstrated by comparing its performance with other methods reported in the available literatures.
Keywords: Phasor measurement unit, optimal placement, clustered gravitational search
algorithm, fuzzy set theory, multi-objective problem
