2020
DOI: 10.1007/978-3-030-42363-6_59
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Sine-Cosine Algorithm Based Automatic Load-Frequency Control of Hybrid Microgrid with Demand Side Management

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Cited by 4 publications
(3 citation statements)
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“…Another important aspect that influences the performance of controllers in HPS is the selection of proper optimization tool for tuning the controller parameters. In line with this, BOA 21 grasshopper optimization algorithm (GOA), 7,24 SHO, 17 SSO, 18 WCA, 19 genetic algorithm (GA), 27 sine‐cosine algorithm (SCA), 28 salp swarm algorithm (SSA) 29 have been researched in connection with LFC in interconnected HPS. With the breakthrough of optimization tool, the benefit of some other algorithm such as Harris's hawk optimization (HHO) 30 could further enhance the performance of the controller employed in an interconnected HPS.…”
Section: Introductionmentioning
confidence: 92%
“…Another important aspect that influences the performance of controllers in HPS is the selection of proper optimization tool for tuning the controller parameters. In line with this, BOA 21 grasshopper optimization algorithm (GOA), 7,24 SHO, 17 SSO, 18 WCA, 19 genetic algorithm (GA), 27 sine‐cosine algorithm (SCA), 28 salp swarm algorithm (SSA) 29 have been researched in connection with LFC in interconnected HPS. With the breakthrough of optimization tool, the benefit of some other algorithm such as Harris's hawk optimization (HHO) 30 could further enhance the performance of the controller employed in an interconnected HPS.…”
Section: Introductionmentioning
confidence: 92%
“…Another category of the algorithm is based on genetic evolution like the genetic algorithm (GA) [56]. We also have algorithms based on physical phenomena such as the sine cosine algorithm (SCA) [57]. For more details, a review is presented in [58] and [50] where many algorithms and their owcharts are presented.…”
Section: Fitness Functionmentioning
confidence: 99%
“…Faced with multiple uncertainties in MGs, the H-In nity controller coupled with µ-synthesis and µ-analysis [47][48][49] also allows for improved stability of the frequency. The metaheuristic algorithms [50][51][52][53][54][55][56][57][58] are also very often observed when we want to optimize some parameter. Thus, the genetic algorithm (GA), the particle swarm optimization (PSO), the grey wolf optimization (GWO), and many others are used in the literature, and the notion of the objective function is also discussed in this work.…”
Section: Introductionmentioning
confidence: 99%