Open AccessA reliability‐based optimal μ‐PMU placement scheme for efficient observability enhancement of smart distribution grids under various contingencies
Author(s) -
Abdolahi Arya,
Taghizadegan Navid,
Banaei Mohamad Reza,
Salehi Javad
Publication year - 2021
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/smt2.12067
Subject(s) - observability , phasor measurement unit , mathematical optimization , smart grid , integer programming , phasor , reliability (semiconductor) , solver , redundancy (engineering) , electric power system , linear programming , computer science , units of measurement , power (physics) , control theory (sociology) , reliability engineering , engineering , mathematics , electrical engineering , physics , quantum mechanics , control (management) , artificial intelligence
Abstract A reliability‐based optimal μ‐PMU (micro‐phasor measurement unit) placement scheme is suggested for efficient observability enhancement of smart distribution grids at steady‐state and contingencies conditions. This article introduces a unique method for the μ‐PMU allocation in reconfigurable smart distribution grids in which communication system requirements and zero injection nodes (ZINs) are considered. The original objective function and limitations are proposed aiming at minimizing the capital cost, including communication links and installation costs of μ‐PMU, optical power ground wire cost, power losses cost, and reliability cost as well as obtaining the maximum number of measurement redundancy constrained to full system observability in the presence of ZINs and tie switches. The suggested method is formulated as a mixed‐integer linear programming problem applied to find optimal μ‐PMU locations considering the cost of communication infrastructure and co‐optimize the system switching plan simultaneously. In this regard, CPLEX—a high‐performance mathematical solver—is used to solve the proposed mixed‐integer linear optimization problem to reach the global optimality. The simulations are performed on 33, 69, and 85‐bus radial distribution networks, and comprehensive simulation studies show the effectiveness of the suggested method.