An enhanced multi-objective reactive power dispatch for hybrid Wind-Solar power system using Archimedes optimization algorithm
•Improved ORPD using Archimedes Optimization (AOA) for power loss and voltage control.•Models wind and solar uncertainties via Weibull and lognormal distributions.•AOA outperforms other metaheuristic algorithms on IEEE 57-bus system with faster convergence.•Achieves 15.7% power loss reduction and 83...
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| Vydané v: | International journal of electrical power & energy systems Ročník 168; s. 110676 |
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| Hlavní autori: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier Ltd
01.07.2025
Elsevier |
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| ISSN: | 0142-0615 |
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| Abstract | •Improved ORPD using Archimedes Optimization (AOA) for power loss and voltage control.•Models wind and solar uncertainties via Weibull and lognormal distributions.•AOA outperforms other metaheuristic algorithms on IEEE 57-bus system with faster convergence.•Achieves 15.7% power loss reduction and 83.9% VSI improvement using AOA.•Handles RE uncertainty in ORPD using scenario-based AOA modelling.
Optimal reactive power dispatch (ORPD) is essential for addressing power system challenges related to distributed generation (DG), particularly from renewable energy (RE) sources such as wind and solar. The intermittent nature and uncertainty of these energy sources, influenced by varying wind speeds and solar irradiation, complicate their integration into power systems. This paper proposes a solution to the ORPD problem in systems with RE-DG integration using the Archimedes Optimization Algorithm (AOA). The uncertainties of wind and solar power generation were modelled using Weibull and lognormal probability density functions (PDFs), respectively, and the optimization model was tested using a scenario-based method. The AOA was applied to the IEEE 57 bus system to minimize power loss, voltage deviation, and voltage stability index (VSI). The results demonstrated that AOA contributed to a 15.7% reduction in power loss, and an 83.9% enhancement in VSI compared to the base case. In the multi-objective optimization scenario, AOA achieved a 7.1% reduction in power loss, with an additional 11.6% improvement upon the integration of DGs. The performance of AOA was also compared with other metaheuristic algorithms, demonstrating superior results in terms of tracking accuracy and convergence speed. AOA outperformed the multi-objective ant lion optimization (MOALO) and the Levy-based Interior Search Algorithm (LISA) in terms of power loss reduction and voltage stability. AOA achieved a 1.83% lower power loss and a 29.67% lower VSI compared to MOALO. When compared to LISA, AOA achieved a 1.68% lower power loss, demonstrating its superior optimization capabilities. These findings confirm that AOA is a highly effective method for solving the ORPD problem, accounting for renewable energy uncertainties and improving overall system performance. |
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| AbstractList | Optimal reactive power dispatch (ORPD) is essential for addressing power system challenges related to distributed generation (DG), particularly from renewable energy (RE) sources such as wind and solar. The intermittent nature and uncertainty of these energy sources, influenced by varying wind speeds and solar irradiation, complicate their integration into power systems. This paper proposes a solution to the ORPD problem in systems with RE-DG integration using the Archimedes Optimization Algorithm (AOA). The uncertainties of wind and solar power generation were modelled using Weibull and lognormal probability density functions (PDFs), respectively, and the optimization model was tested using a scenario-based method. The AOA was applied to the IEEE 57 bus system to minimize power loss, voltage deviation, and voltage stability index (VSI). The results demonstrated that AOA contributed to a 15.7% reduction in power loss, and an 83.9% enhancement in VSI compared to the base case. In the multi-objective optimization scenario, AOA achieved a 7.1% reduction in power loss, with an additional 11.6% improvement upon the integration of DGs. The performance of AOA was also compared with other metaheuristic algorithms, demonstrating superior results in terms of tracking accuracy and convergence speed. AOA outperformed the multi-objective ant lion optimization (MOALO) and the Levy-based Interior Search Algorithm (LISA) in terms of power loss reduction and voltage stability. AOA achieved a 1.83% lower power loss and a 29.67% lower VSI compared to MOALO. When compared to LISA, AOA achieved a 1.68% lower power loss, demonstrating its superior optimization capabilities. These findings confirm that AOA is a highly effective method for solving the ORPD problem, accounting for renewable energy uncertainties and improving overall system performance. •Improved ORPD using Archimedes Optimization (AOA) for power loss and voltage control.•Models wind and solar uncertainties via Weibull and lognormal distributions.•AOA outperforms other metaheuristic algorithms on IEEE 57-bus system with faster convergence.•Achieves 15.7% power loss reduction and 83.9% VSI improvement using AOA.•Handles RE uncertainty in ORPD using scenario-based AOA modelling. Optimal reactive power dispatch (ORPD) is essential for addressing power system challenges related to distributed generation (DG), particularly from renewable energy (RE) sources such as wind and solar. The intermittent nature and uncertainty of these energy sources, influenced by varying wind speeds and solar irradiation, complicate their integration into power systems. This paper proposes a solution to the ORPD problem in systems with RE-DG integration using the Archimedes Optimization Algorithm (AOA). The uncertainties of wind and solar power generation were modelled using Weibull and lognormal probability density functions (PDFs), respectively, and the optimization model was tested using a scenario-based method. The AOA was applied to the IEEE 57 bus system to minimize power loss, voltage deviation, and voltage stability index (VSI). The results demonstrated that AOA contributed to a 15.7% reduction in power loss, and an 83.9% enhancement in VSI compared to the base case. In the multi-objective optimization scenario, AOA achieved a 7.1% reduction in power loss, with an additional 11.6% improvement upon the integration of DGs. The performance of AOA was also compared with other metaheuristic algorithms, demonstrating superior results in terms of tracking accuracy and convergence speed. AOA outperformed the multi-objective ant lion optimization (MOALO) and the Levy-based Interior Search Algorithm (LISA) in terms of power loss reduction and voltage stability. AOA achieved a 1.83% lower power loss and a 29.67% lower VSI compared to MOALO. When compared to LISA, AOA achieved a 1.68% lower power loss, demonstrating its superior optimization capabilities. These findings confirm that AOA is a highly effective method for solving the ORPD problem, accounting for renewable energy uncertainties and improving overall system performance. |
| ArticleNumber | 110676 |
| Author | Megantoro, Prisma Rosli, Hazwani Mohd Mohamed, Ramizi Halim, Syahirah Abd Mohamed Kamari, Nor Azwan Awalin, Lilik Jamilatul |
| Author_xml | – sequence: 1 givenname: Prisma surname: Megantoro fullname: Megantoro, Prisma organization: Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan, Malaysia – sequence: 2 givenname: Syahirah Abd surname: Halim fullname: Halim, Syahirah Abd email: syahirah_h@ukm.edu.my organization: Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan, Malaysia – sequence: 3 givenname: Nor Azwan surname: Mohamed Kamari fullname: Mohamed Kamari, Nor Azwan organization: Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan, Malaysia – sequence: 4 givenname: Lilik Jamilatul surname: Awalin fullname: Awalin, Lilik Jamilatul organization: Faculty of Advanced Technology and Multidicipline, Universitas Airlangga, Gedung Kuliah Bersama, Kampus C Unair, Jl. Mulyorejo, Surabaya 60155, Indonesia – sequence: 5 givenname: Ramizi surname: Mohamed fullname: Mohamed, Ramizi organization: Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan, Malaysia – sequence: 6 givenname: Hazwani Mohd surname: Rosli fullname: Rosli, Hazwani Mohd organization: School of Engineering, Asia Pacific University of Technology and Innovation, Kuala Lumpur, Malaysia |
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| Keywords | RES DG MOALO Distribution generation PV HHO WF CSA AOA MA PLoss FOA AVOA EA NSA GWO PSA PSH AHOA LISA WOA MW Archimedes optimization algorithm Optimal reactive power dispatch VSI RE-ORPD VD ORPD TF RE Metaheuristics optimization Voltage stability index MCS MWh |
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| Title | An enhanced multi-objective reactive power dispatch for hybrid Wind-Solar power system using Archimedes optimization algorithm |
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