Staff View: Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach

Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach

This paper delves into the increasingly complex domain of Optimal Power Flow (OPF) within modern power systems, enhanced by the integration of unpredictable renewable energy sources. The research originally integrates stochastic photovoltaic and wind energy sources, along with a suite of Flexible AC...

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Main Authors:	Premkumar M., Hashim T.J.T., Ravichandran S., Sin T.C., Chandran R., Alsoud A.R., Jangir P.
Other Authors:	57191413142
Format:	Article
Published:	Elsevier B.V. 2025
Subjects:	Constraint handling Electric load flow Electric power system control Flexible AC transmission systems Power control Probability density function Reactive power Static Var compensators Stochastic systems Thyristors Value engineering Wind power Energy Flexible AC transmission system controller Flow direction algorithms Multi-objectives optimization Optimal power flow analyse Optimal power flows Power flow analyze System controllers ?-based constraint-handling Multiobjective optimization
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id	my.uniten.dspace-36605
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spelling	my.uniten.dspace-366052025-03-03T15:43:21Z Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach Premkumar M. Hashim T.J.T. Ravichandran S. Sin T.C. Chandran R. Alsoud A.R. Jangir P. 57191413142 57217828276 57219263030 57212007867 58873007200 55711826000 56857572500 Constraint handling Electric load flow Electric power system control Flexible AC transmission systems Power control Probability density function Reactive power Static Var compensators Stochastic systems Thyristors Value engineering Wind power Constraint handling Energy Flexible AC transmission system controller Flow direction algorithms Multi-objectives optimization Optimal power flow analyse Optimal power flows Power flow analyze System controllers ?-based constraint-handling Multiobjective optimization This paper delves into the increasingly complex domain of Optimal Power Flow (OPF) within modern power systems, enhanced by the integration of unpredictable renewable energy sources. The research originally integrates stochastic photovoltaic and wind energy sources, along with a suite of Flexible AC Transmission System (FACTS) components ? including thyristor-controlled series compensators, static VAR compensators, and thyristor-controlled phase shifters. The primary objective is to solve the OPF problem by reducing generation costs while accommodating the variable nature of renewable energy sources and load demands. This study prioritizes the examination of both constant and fluctuating load requirements. The inherent variability of PV and wind energy, along with load demand, is captured through the modelling of probability density functions. This approach enables a more detailed optimization process, incorporating not just the cost of thermal energy generation but also the scheduling costs of renewable sources and associated penalty costs. Moreover, the study examines the strategic placement and sizing of FACTS components, an aspect essential in minimizing the overall cost of power production. Employing both single- and multi-objective optimization algorithms, the research addresses the OPF problem in a modified IEEE-30 bus system through various case studies. The application of the recently developed flow direction algorithm, including its multi-objective variant with an �-based constraint-handling mechanism to OPF problem is the primary contributions of this work. The results, benchmarked against several advanced metaheuristic algorithms, reveal the proposed algorithm's superior performance. This comprehensive study not only underscores the potential of integrating renewable energy sources into the grid but also highlights the efficacy of intelligent optimization strategies in managing the complexities of modern power systems. ? 2024 Final 2025-03-03T07:43:21Z 2025-03-03T07:43:21Z 2024 Article 10.1016/j.aej.2024.02.069 2-s2.0-85188029057 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188029057&doi=10.1016%2fj.aej.2024.02.069&partnerID=40&md5=59e7d50e21756340644bab3766fdd974 https://irepository.uniten.edu.my/handle/123456789/36605 93 90 113 All Open Access; Gold Open Access Elsevier B.V. Scopus
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
topic	Constraint handling Electric load flow Electric power system control Flexible AC transmission systems Power control Probability density function Reactive power Static Var compensators Stochastic systems Thyristors Value engineering Wind power Constraint handling Energy Flexible AC transmission system controller Flow direction algorithms Multi-objectives optimization Optimal power flow analyse Optimal power flows Power flow analyze System controllers ?-based constraint-handling Multiobjective optimization
spellingShingle	Constraint handling Electric load flow Electric power system control Flexible AC transmission systems Power control Probability density function Reactive power Static Var compensators Stochastic systems Thyristors Value engineering Wind power Constraint handling Energy Flexible AC transmission system controller Flow direction algorithms Multi-objectives optimization Optimal power flow analyse Optimal power flows Power flow analyze System controllers ?-based constraint-handling Multiobjective optimization Premkumar M. Hashim T.J.T. Ravichandran S. Sin T.C. Chandran R. Alsoud A.R. Jangir P. Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach
description	This paper delves into the increasingly complex domain of Optimal Power Flow (OPF) within modern power systems, enhanced by the integration of unpredictable renewable energy sources. The research originally integrates stochastic photovoltaic and wind energy sources, along with a suite of Flexible AC Transmission System (FACTS) components ? including thyristor-controlled series compensators, static VAR compensators, and thyristor-controlled phase shifters. The primary objective is to solve the OPF problem by reducing generation costs while accommodating the variable nature of renewable energy sources and load demands. This study prioritizes the examination of both constant and fluctuating load requirements. The inherent variability of PV and wind energy, along with load demand, is captured through the modelling of probability density functions. This approach enables a more detailed optimization process, incorporating not just the cost of thermal energy generation but also the scheduling costs of renewable sources and associated penalty costs. Moreover, the study examines the strategic placement and sizing of FACTS components, an aspect essential in minimizing the overall cost of power production. Employing both single- and multi-objective optimization algorithms, the research addresses the OPF problem in a modified IEEE-30 bus system through various case studies. The application of the recently developed flow direction algorithm, including its multi-objective variant with an �-based constraint-handling mechanism to OPF problem is the primary contributions of this work. The results, benchmarked against several advanced metaheuristic algorithms, reveal the proposed algorithm's superior performance. This comprehensive study not only underscores the potential of integrating renewable energy sources into the grid but also highlights the efficacy of intelligent optimization strategies in managing the complexities of modern power systems. ? 2024
author2	57191413142
author_facet	57191413142 Premkumar M. Hashim T.J.T. Ravichandran S. Sin T.C. Chandran R. Alsoud A.R. Jangir P.
format	Article
author	Premkumar M. Hashim T.J.T. Ravichandran S. Sin T.C. Chandran R. Alsoud A.R. Jangir P.
author_sort	Premkumar M.
title	Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach
title_short	Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach
title_full	Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach
title_fullStr	Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach
title_full_unstemmed	Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach
title_sort	optimal operation and control of hybrid power systems with stochastic renewables and facts devices: an intelligent multi-objective optimization approach
publisher	Elsevier B.V.
publishDate	2025
_version_	1825816067540254720
score	13.244109

Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach

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