2022
DOI: 10.1109/access.2022.3146366
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Volt/VAR Optimization: A Survey of Classical and Heuristic Optimization Methods

Abstract: Reactive 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.… Show more

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Cited by 25 publications
(23 citation statements)
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References 134 publications
(165 reference statements)
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“…The primary objective of Volt/VAR optimization is to facilitate the maintenance of network voltage profile within the predetermined nominal range, and at the same time optimize network reactive power dispatch so as to enhance the economical operation of the power system. Key objectives considered in the framework of Volt/VAR optimization are [20]:…”
Section: A Objectivesmentioning
confidence: 99%
See 1 more Smart Citation
“…The primary objective of Volt/VAR optimization is to facilitate the maintenance of network voltage profile within the predetermined nominal range, and at the same time optimize network reactive power dispatch so as to enhance the economical operation of the power system. Key objectives considered in the framework of Volt/VAR optimization are [20]:…”
Section: A Objectivesmentioning
confidence: 99%
“…reduced-gradient, generalized reduced-gradient, conjugate-gradient, Newton and quasi-Newton methods), and local-approximation methods such as sequential linear programming (SLP) and sequential quadratic programming (SQP). Heuristic optimization methods encompass genetic algorithm, evolutionary programming, particle swarm optimization, fuzzy set theory, and expert systems, among others [20].…”
Section: Introductionmentioning
confidence: 99%
“…The technique in the papers scheduled a large number of appliances of different types. The authors in [36,37] use a heuristic-based evolutionary algorithm to reduce the PAR and minimize the cost by shifting the peak hour load to different sources.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In relation to the heuristic approaches, techniques such as the Genetic Algorithms (GA) [156], the Evolutionary Programming (EP) [157], the Particle Swarm Optimization (PSO) [158], and the Expert Systems (ES) [159]. These techniques can handle problems in which the previous knowledge is not necessary, they are good for looking values in searching spaces with non-linearities, non-convexities, and with high dimensionality.…”
Section: Techniques That Could Be Possible Potential Solutions To The...mentioning
confidence: 99%