Open AccessEconomical placement of PMUs considering observability and voltage stability using binary coded ant lion optimization
Author(s) -
Manoharan Hariprasath,
Srikrishna Subramanian,
Sivarajan Ganesan,
Manoharan Abirami
Publication year - 2018
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/etep.2591
Subject(s) - observability , units of measurement , phasor , phasor measurement unit , electric power system , mathematical optimization , computer science , reliability engineering , stability (learning theory) , optimization problem , control theory (sociology) , engineering , power (physics) , mathematics , control (management) , machine learning , artificial intelligence , physics , quantum mechanics
Summary Phasor measurement unit (PMU) plays a key role in concurrent power system state estimation and security enhancement processes. Considering the cost of PMU as an important concern, confined number of PMUs is located at hazardous locations for power system observability. The PMU placements can be explored further for various power system operational studies. One promising indicator is that not only the PMUs should be informative, but also they should be able to perceive the voltage stability levels under critical loading conditions. In topical eons the role of voltage stability is essential which causes severe difficulty. Regrettably, this results in enhancement and impractical vision because of same cost of consumption of PMUs. It is sufficient to reduce the deployment cost provided that the factors such as reliability of the measurement system, observability can be certain for effective placement of PMUs. In line with the above concern, to solve the problem efficiently, a realistic multiobjective model that includes 3 objectives such as (1) system observability with minimum number of PMUs, (2) envisaging the communication cost involved in these placements, and (3) enhancing the voltage stability levels of the system is proposed. The developed model is solved as a nonlinear and constrained optimization problem in multiobjective framework. The binary coding scheme is conventionally preferred for solving PMU placement problem, hence, binary‐coded ant lion optimizer has been developed and is applied for the first time to solve the developed multiobjective PMU placement model. The standard IEEE test systems (14 bus, 30 bus, and 57 bus systems) and a large scale system containing 2383 buses are used to ratify the proposed model and the envisioned optimization tool. Numerical outcome specifies that binary‐coded ant lion optimizer is robust and effective in finding the best compromise solution.