Optimization of grid-connected photovoltaic/wind/battery/supercapacitor systems using a hybrid artificial gorilla troops optimizer with a quadratic interpolation algorithm
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- 6 December 2024
- journal article
- research article
- Published by Springer Nature in Neural Computing and Applications
- Vol. 37 (4) , 2497-2535
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- Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
This publication has 53 references indexed in Scilit:
- Optimal design of a hybrid energy system considering techno-economic factors for off-grid electrification in remote areasClean Technologies and Environmental Policy, 2024
- Sustainable energy integration and optimization in microgrids: enhancing efficiency with electric vehicle charging solutionsElectrical Engineering, 2024
- Quadratic Interpolation Optimization (QIO): A new optimization algorithm based on generalized quadratic interpolation and its applications to real-world engineering problemsComputer Methods in Applied Mechanics and Engineering, 2023
- Metaheuristic-based isolated microgrid sizing and uncertainty quantification considering EVs as shiftable loadsEnergy Reports, 2022
- Performance analysis of autonomous green energy system based on multi and hybrid metaheuristic optimization approachesEnergy Conversion and Management, 2022
- Controlled V2Gs and battery integration into residential microgrids: Economic and environmental impactsEnergy Conversion and Management, 2022
- Tri-objective techno-economic sizing optimization of Off-grid and On-grid renewable energy systems using Electric system Cascade Extended analysis and system Advisor ModelApplied Energy, 2022
- Artificial gorilla troops optimizer: A new nature‐inspired metaheuristic algorithm for global optimization problemsInternational Journal of Intelligent Systems, 2021
- Scheduling controller for microgrids energy management system using optimization algorithm in achieving cost saving and emission reductionApplied Energy, 2021
- A demand response-centred approach to the long-term equipment capacity planning of grid-independent micro-grids optimized by the moth-flame optimization algorithmEnergy Conversion and Management, 2019