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A novel approach to multi-objective OPF by a new parallel non-dominated Sorting Genetic Algorithm-considering diverse constraints


Article Information

Title: A novel approach to multi-objective OPF by a new parallel non-dominated Sorting Genetic Algorithm-considering diverse constraints

Authors: S. Ragavan Swaminathan, E. Nandakumar

Journal: ARPN Journal of Engineering and Applied Sciences

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
X 2020-07-01 2021-06-30

Publisher: Khyber Medical College, Peshawar

Country: Pakistan

Year: 2016

Volume: 11

Issue: 9

Language: English

Categories

Abstract

Transient stability constrained optimal power flow (TSCOPF) is able to reduce costs while keeping the operation point away from the stability boundary. While especially useful in modern power system operations, TSCOPF problems are practically very hard to solve; unacceptable computational time is considered to be one of the largest barriers in applying TSCOPF-based solutions. The basic idea of the proposed method is to model transient stability as an objective function rather than an inequality constraint and consider classic Transient Stability Constrained OPF (TSCOPF) as a tradeoff procedure using Pareto ideology. Second, a parallel elitist Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to solve the proposed multi-objective optimization problem; the parallel algorithm shows an excellent acceleration effect and provides a set of Pareto optimal solutions for decision makers to select. Case study results demonstrate the proposed multi-objective algorithm in IEEE39 bus system is quite strategic.


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