Please use this identifier to cite or link to this item: http://hdl.handle.net/11189/9247
DC FieldValueLanguage
dc.contributor.authorMataifa, Haltoren_US
dc.contributor.authorKrishnamurthy, Senthilen_US
dc.contributor.authorKriger, Carlen_US
dc.date.accessioned2023-08-14T10:13:21Z-
dc.date.available2023-08-14T10:13:21Z-
dc.date.issued2022-
dc.identifier.citationMataifa, H., Krishnamurthy, S. & Kriger, C. 2022. Volt/VAR optimization: a survey of classical and heuristic optimization methods. IEEE Access, 10: 13379-13399. [https://doi.org/10.1109/ACCESS.2022.3146366]en_US
dc.identifier.issn2169-3536-
dc.identifier.urihttp://hdl.handle.net/11189/9247-
dc.descriptionArticleen_US
dc.description.abstractReactive power optimization and voltage control is one of the most critical components of power system operation, impacting both the economy and security of system operation. It is also one of the most complex optimization problems, being highly nonlinear, and comprising both continuous and discrete decision variables. This paper presents the problem formulation, and a thorough literature review and detailed discussion of the various solution methods that have been applied to the Volt/VAR optimization problem. Each optimization method is described in detail, and its strengths and shortcomings are outlined. The review provides detailed information on classical and heuristic methods that have been applied to the Volt/VAR optimization problem. The classical methods reviewed include (i) first- and second-order gradient-based methods, (ii) Quadratic Programming, (iii) Linear Programming, (iv) Interior-Point Methods, (iv) and mixed-integer programming and decomposition methods. The heuristic methods covered include (i) Genetic Algorithm, (ii) Evolutionary Programming, (iii) Particle Swarm Optimization, (iv) Fuzzy Set Theory, and (v) Expert Systems. A comparative analysis of the key characteristics of the classical and heuristic optimization methods is also presented along with the review.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofIEEE Accessen_US
dc.subjectVolt/VAR optimizationen_US
dc.subjectreactive power/voltage controlen_US
dc.subjectclassical/numerical optimizationen_US
dc.subjectheuristic methodsen_US
dc.subjectartificial intelligence techniquesen_US
dc.titleVolt/VAR optimization: a survey of classical and heuristic optimization methodsen_US
dc.identifier.doihttps://doi.org/10.1109/ACCESS.2022.3146366-
dc.typeArticleen_US
Appears in Collections:Eng - Journal articles (DHET subsidised)
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