Economic energy optimization in microgrid with PV/wind/battery integrated wireless electric vehicle battery charging system using improved Harris Hawk Optimization
Abstract This paper investigates the economic energy management of a wireless electric vehicle charging stations (EVCS) connected to hybrid renewable energy system comprising photovoltaic (PV), wind, battery storage, and the main grid. The study adopts an Improved Harris Hawk Optimization (IHHO) alg...
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Nature Portfolio
2025-03-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-94285-7 |
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| author | Perne Mallikarjun Sundar Rajan Giri Thulasiraman Praveen Kumar Balachandran Muhammad Ammirrul Atiqi Mohd Zainuri |
| author_facet | Perne Mallikarjun Sundar Rajan Giri Thulasiraman Praveen Kumar Balachandran Muhammad Ammirrul Atiqi Mohd Zainuri |
| author_sort | Perne Mallikarjun |
| collection | DOAJ |
| description | Abstract This paper investigates the economic energy management of a wireless electric vehicle charging stations (EVCS) connected to hybrid renewable energy system comprising photovoltaic (PV), wind, battery storage, and the main grid. The study adopts an Improved Harris Hawk Optimization (IHHO) algorithm to optimize energy management and minimize operational costs under varying scenarios. Three distinct wireless EV charging load profiles are considered to evaluate the performance of the proposed optimization technique. Simulation results demonstrate that the IHHO algorithm achieves significant cost reductions and improves energy utilization efficiency compared to other state-of-the-art optimization algorithms such as Improved Quantum Particle Swarm Optimization (IQPSO), Honeybee Mating Optimization (HBMO), and Enhanced Exploratory Whale Optimization Algorithm (EEWOA). For scenarios with renewable energies, the IHHO algorithm reduced electricity costs by up to 36.41%, achieving a per-unit cost as low as 3.17 INR for the most demanding EV charging profile. Under scenarios of renewable generation disconnection, the IHHO algorithm maintained its superiority, reducing costs by up to 37.89% compared to unoptimized dispatch strategies. The integration of battery storage further enhanced the system’s resilience and cost-effectiveness, particularly during periods of renewable unavailability. The IHHO algorithm’s robust performance, reflected in its ability to handle dynamic and challenging operational conditions, demonstrates its potential for practical deployment in real-world wireless EVCS powered by hybrid renewable energy systems. The findings highlight the IHHO algorithm as a reliable and efficient tool for optimizing energy dispatch, promoting the integration of renewable energy, and supporting sustainable wireless EVCS infrastructure development. Simulation results demonstrate that IHHO outperforms all benchmark algorithms, achieving electricity cost reductions of up to 35.82% in EV Profile 3, with a minimum per-unit electricity cost of 3.11 INR/kWh across all scenarios. Specifically, IHHO achieved the lowest electricity cost of 6479.72 INR/day for EV Profile 1, 10,893.23 INR/day for EV Profile 2, and 20,821.63 INR/day for EV Profile 3, consistently outperforming IQPSO, HBMO, and EEWOA. |
| format | Article |
| id | doaj-art-0b925b532aa6436080fe8946ef8cbe97 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-0b925b532aa6436080fe8946ef8cbe972025-08-20T02:51:28ZengNature PortfolioScientific Reports2045-23222025-03-0115113010.1038/s41598-025-94285-7Economic energy optimization in microgrid with PV/wind/battery integrated wireless electric vehicle battery charging system using improved Harris Hawk OptimizationPerne Mallikarjun0Sundar Rajan Giri Thulasiraman1Praveen Kumar Balachandran2Muhammad Ammirrul Atiqi Mohd Zainuri3Department of Electrical and Electronics Engineering, Sathyabama Institute of Science and TechnologyDepartment of Electrical and Electronics Engineering, Sathyabama Institute of Science and TechnologyDepartment of Electrical, Electronic and Systems Engineering, Faculty Engineering and Built Environment, Universiti Kebangsaan MalaysiaDepartment of Electrical, Electronic and Systems Engineering, Faculty Engineering and Built Environment, Universiti Kebangsaan MalaysiaAbstract This paper investigates the economic energy management of a wireless electric vehicle charging stations (EVCS) connected to hybrid renewable energy system comprising photovoltaic (PV), wind, battery storage, and the main grid. The study adopts an Improved Harris Hawk Optimization (IHHO) algorithm to optimize energy management and minimize operational costs under varying scenarios. Three distinct wireless EV charging load profiles are considered to evaluate the performance of the proposed optimization technique. Simulation results demonstrate that the IHHO algorithm achieves significant cost reductions and improves energy utilization efficiency compared to other state-of-the-art optimization algorithms such as Improved Quantum Particle Swarm Optimization (IQPSO), Honeybee Mating Optimization (HBMO), and Enhanced Exploratory Whale Optimization Algorithm (EEWOA). For scenarios with renewable energies, the IHHO algorithm reduced electricity costs by up to 36.41%, achieving a per-unit cost as low as 3.17 INR for the most demanding EV charging profile. Under scenarios of renewable generation disconnection, the IHHO algorithm maintained its superiority, reducing costs by up to 37.89% compared to unoptimized dispatch strategies. The integration of battery storage further enhanced the system’s resilience and cost-effectiveness, particularly during periods of renewable unavailability. The IHHO algorithm’s robust performance, reflected in its ability to handle dynamic and challenging operational conditions, demonstrates its potential for practical deployment in real-world wireless EVCS powered by hybrid renewable energy systems. The findings highlight the IHHO algorithm as a reliable and efficient tool for optimizing energy dispatch, promoting the integration of renewable energy, and supporting sustainable wireless EVCS infrastructure development. Simulation results demonstrate that IHHO outperforms all benchmark algorithms, achieving electricity cost reductions of up to 35.82% in EV Profile 3, with a minimum per-unit electricity cost of 3.11 INR/kWh across all scenarios. Specifically, IHHO achieved the lowest electricity cost of 6479.72 INR/day for EV Profile 1, 10,893.23 INR/day for EV Profile 2, and 20,821.63 INR/day for EV Profile 3, consistently outperforming IQPSO, HBMO, and EEWOA.https://doi.org/10.1038/s41598-025-94285-7Improved Harris Hawk Optimization (IHHO)Economic energy dispatchWireless electric vehicle charging stations (EVCS)Hybrid renewable energy systemBattery storage optimization |
| spellingShingle | Perne Mallikarjun Sundar Rajan Giri Thulasiraman Praveen Kumar Balachandran Muhammad Ammirrul Atiqi Mohd Zainuri Economic energy optimization in microgrid with PV/wind/battery integrated wireless electric vehicle battery charging system using improved Harris Hawk Optimization Scientific Reports Improved Harris Hawk Optimization (IHHO) Economic energy dispatch Wireless electric vehicle charging stations (EVCS) Hybrid renewable energy system Battery storage optimization |
| title | Economic energy optimization in microgrid with PV/wind/battery integrated wireless electric vehicle battery charging system using improved Harris Hawk Optimization |
| title_full | Economic energy optimization in microgrid with PV/wind/battery integrated wireless electric vehicle battery charging system using improved Harris Hawk Optimization |
| title_fullStr | Economic energy optimization in microgrid with PV/wind/battery integrated wireless electric vehicle battery charging system using improved Harris Hawk Optimization |
| title_full_unstemmed | Economic energy optimization in microgrid with PV/wind/battery integrated wireless electric vehicle battery charging system using improved Harris Hawk Optimization |
| title_short | Economic energy optimization in microgrid with PV/wind/battery integrated wireless electric vehicle battery charging system using improved Harris Hawk Optimization |
| title_sort | economic energy optimization in microgrid with pv wind battery integrated wireless electric vehicle battery charging system using improved harris hawk optimization |
| topic | Improved Harris Hawk Optimization (IHHO) Economic energy dispatch Wireless electric vehicle charging stations (EVCS) Hybrid renewable energy system Battery storage optimization |
| url | https://doi.org/10.1038/s41598-025-94285-7 |
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