Efficient economic operation based on load dispatch of power systems using a leader white shark optimization algorithm

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: 36(18), P. 10613 - 10635

Published: March 27, 2024

Abstract This article proposes the use of a leader white shark optimizer (LWSO) with aim improving exploitation conventional (WSO) and solving economic operation-based load dispatch (ELD) problem. The ELD problem is crucial aspect power system operation, involving allocation generation resources to meet demand while minimizing operational costs. proposed approach aims enhance performance efficiency WSO by introducing leadership mechanism within optimization process, which aids in more effectively navigating complex solution space. LWSO achieves increased utilizing leader-based mutation selection throughout each sharks. efficacy algorithm tested on 13 engineer benchmarks non-convex problems from CEC 2020 compared recent metaheuristic algorithms such as dung beetle (DBO), WSO, fox (FOX), moth-flame (MFO) algorithms. also used address different case studies (6 units, 10 11 40 units), 20 separate runs using other competitive being statistically assessed demonstrate its effectiveness. results show that outperforms algorithms, achieving best for minimum fuel cost Additionally, statistical tests are conducted validate competitiveness algorithm.

Language: Английский

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Enhanced gorilla troops optimizer powered by marine predator algorithm: global optimization and engineering design

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: April 1, 2024

Abstract This study presents an advanced metaheuristic approach termed the Enhanced Gorilla Troops Optimizer (EGTO), which builds upon Marine Predators Algorithm (MPA) to enhance search capabilities of (GTO). Like numerous other algorithms, GTO encounters difficulties in preserving convergence accuracy and stability, notably when tackling intricate adaptable optimization problems, especially compared more techniques. Addressing these challenges aiming for improved performance, this paper proposes EGTO, integrating high low-velocity ratios inspired by MPA. The EGTO technique effectively balances exploration exploitation phases, achieving impressive results utilizing fewer parameters operations. Evaluation on a diverse array benchmark functions, comprising 23 established functions ten complex ones from CEC2019 benchmark, highlights its performance. Comparative analysis against techniques reveals EGTO's superiority, consistently outperforming counterparts such as tuna swarm optimization, grey wolf optimizer, gradient based artificial rabbits algorithm, pelican Runge Kutta algorithm (RUN), original algorithms across various test functions. Furthermore, efficacy extends addressing seven challenging engineering design encompassing three-bar truss design, compression spring pressure vessel cantilever beam welded speed reducer gear train design. showcase robust rate, adeptness locating local/global optima, supremacy over alternative methodologies explored.

Language: Английский

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Optimizing economic dispatch problems in power systems using manta ray foraging algorithm: an oppositional-based approach

Computers & Electrical Engineering, Journal Year: 2024, Volume and Issue: 117, P. 109279 - 109279

Published: May 9, 2024

Language: Английский

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Probabilistic prediction-based multi-objective optimization approach for multi-energy virtual power plant

International Journal of Electrical Power & Energy Systems, Journal Year: 2024, Volume and Issue: 161, P. 110200 - 110200

Published: Aug. 28, 2024

Language: Английский

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A New Cloud-Stochastic Framework for Optimized Deployment of Hydrogen Storage in Distribution Network Integrated with Renewable Energy Considering Hydrogen-Based Demand Response

Energy, Journal Year: 2025, Volume and Issue: 316, P. 134483 - 134483

Published: Jan. 13, 2025

Language: Английский

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Solving multi-area economic dispatch with disjoint operating regions using special ordered sets

Electric Power Systems Research, Journal Year: 2025, Volume and Issue: 242, P. 111454 - 111454

Published: Jan. 31, 2025

Language: Английский

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A swank raccoon yin yang pair optimization (RYi-YaP) model for solving economic load dispatch (ELD) and combined emission dispatch (CED) problems

Computers & Electrical Engineering, Journal Year: 2025, Volume and Issue: 123, P. 110149 - 110149

Published: Feb. 21, 2025

Language: Английский

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Dual-layer scheduling coordination algorithm for power supply guarantee using multi-objective optimization in spot market environment

Energy Informatics, Journal Year: 2025, Volume and Issue: 8(1)

Published: March 18, 2025

Language: Английский

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Arithmetic Optimization Algorithm with Cosine Composite Chaotic Mapping in Polar Coordinate System for Economic Load Dispatching Problems in Power Systems

Applied Soft Computing, Journal Year: 2025, Volume and Issue: unknown, P. 113039 - 113039

Published: March 1, 2025

Language: Английский

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Solving the Economic Load Dispatch Problem by Attaining and Refining Knowledge-Based Optimization

Mathematics, Journal Year: 2025, Volume and Issue: 13(7), P. 1042 - 1042

Published: March 23, 2025

The Static Economic Load Dispatch (SELD) problem is a paramount optimization challenge in power engineering that seeks to optimize the allocation of between generating units meet imposed constraints while minimizing energy requirements. Recently, researchers have employed numerous meta-heuristic approaches tackle this challenging, non-convex problem. This work introduces an innovative algorithm, named “Attaining and Refining Knowledge-based Optimization (ARKO)”, which uses ability humans learn from their surroundings by leveraging collective knowledge population. ARKO algorithm consists two distinct phases: attaining refining. In phase, gathers population’s top candidates, refining phase enhances performance other selected candidates. way learning improving with help candidates provides robust exploration exploitation capability for algorithm. To validate efficacy ARKO, we conduct comprehensive evaluation against eleven established algorithms using diverse set 41 test functions CEC-2017 CEC-2022 suites, then, three real-life applications also verify its practical ability. Subsequently, implement SELD considering several instances. examination numerical statistical results confirms remarkable efficiency potential complex tasks.

Language: Английский

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