Multi-orthogonal-oppositional enhanced African vultures optimization for combined heat and power economic dispatch under uncertainty

Neural Computing and Applications, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 9, 2025

Language: Английский

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A techno-economic framework for optimizing multi-area power dispatch in microgrids with tie-line constraints

Renewable Energy, Journal Year: 2024, Volume and Issue: 231, P. 120854 - 120854

Published: June 25, 2024

Language: Английский

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An advanced kernel search optimization for dynamic economic emission dispatch with new energy sources

International Journal of Electrical Power & Energy Systems, Journal Year: 2024, Volume and Issue: 160, P. 110085 - 110085

Published: June 27, 2024

Language: Английский

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Hybrid PSO-SFLA with Fuzzy Optimization for Multi-Area Dynamic Economic Load Dispatch and Demand Response

Energy 360., Journal Year: 2025, Volume and Issue: unknown, P. 100021 - 100021

Published: April 1, 2025

Language: Английский

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Hybrid machine learning and optimization method for solar irradiance forecasting

Engineering Optimization, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 36

Published: Sept. 4, 2024

Language: Английский

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Modified Opposition-Based Particle Swarm Optimization for Combined Economic and Emission Dispatch Problem

Electric Power Components and Systems, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 15

Published: April 18, 2024

Modification of the particle swarm optimization (PSO) method is proposed with an opposition-based learning strategy to find optimal solution electrical power dispatch problems. The objective algorithm address combined economic and emissions problem (CEED) thermal plants. This includes constraints such as valve point effect, prohibited zones operation, ramp rate limits. In order assess its performance, first evaluated using a set benchmark functions. Later, three generating systems having 6, 10, 40 units respectively are regarded test validate method. tested, comparison results made popular techniques reported in literature PDE, MODE, NSGA II, MOSSA. Promising have been obtained PSO their current equivalents. A was between fuel cost, emissions, CPU time two other variants: inertia factor (IFPSO) constriction (CFPSO). showed decline overall cost by approximately 3.73% decrease much 2.6 s. Furthermore, predictions consistently exhibit high level accuracy, typically approaching 100%.

Language: Английский

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Ensembled snake optimiser to solve multiobjective mixed energy generation scheduling

International Journal of Ambient Energy, Journal Year: 2024, Volume and Issue: 45(1)

Published: Nov. 4, 2024

This paper presents Ensembled Snake Optimiser (ESO), to optimise the scheduling of mixed energy generation from coordinated thermal, hydro, pumped-storage and solar units. It tackles operational constraints while minimising non-convex non-linear objectives. To reduce pollutants emitted operating cost thermal units, problem uses committed units generate power, hydro maintain water levels, maximise available volume. Utilising volume actively exceeding power-generating limit are primary obstacles satisfy load requirement. The heuristics utilised demand constraints. binary-optimistic approach commits snake optimisation algorithm tends get trapped in local minima solving complex engineering problems, which leads sluggish convergence behaviour. A search, simplex extended opposition-based learning investigated improve its exploitation aspect, behaviour, procure good solutions. Three electric power systems undertaken for simulation studies. ESO gives better results. significant savings integrated ranging 10–15%. rapid behaviour whisker box plots justify ESO's robustness.

Language: Английский

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Proposing an Advanced Trending-based Grey Wolf Optimizer for Single-objective Optimization Problems

Published: Feb. 21, 2024

optimization algorithms play a crucial role in solving complex problems various domains. Single-objective aim to discover the most optimal solution for particular objective function, commonly distinguished by single criterion or goal. Grey Wolf optimizer (GWO) is swarm-based algorithm that has gained attention due its simplicity and efficiency problems. In this article, we propose an advanced version of GWO, which referred as Advanced Trending-based (ATGWO), specifically tailored single-objective The motivation behind modification stems from need improve performance metrics original GWO avoid local optimum. By altering algorithm's coefficients, enhance convergence rate, exploration, exploitation abilities. To evaluate proposed ATGWO algorithm, conduct simulations using 7 multimodal benchmark functions. results suggest although excels accuracy, it more delay comparison with GWO. This study paves way future research about algorithms.

Language: Английский

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A multi-objective economic emission dispatch problem in microgrid with high penetration of renewable energy sources using equilibrium optimizer

Electrical Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: June 15, 2024

Language: Английский

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A novel artificial electric field strategy for economic load dispatch problem with renewable penetration

Evolutionary Intelligence, Journal Year: 2024, Volume and Issue: 17(5-6), P. 3593 - 3608

Published: July 13, 2024

Language: Английский

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