Optimal Active-Reactive Power Dispatch for Distribution Network With Carbon Trading Based on Improved Multi-Objective Equilibrium Optimizer Algorithm
In distribution networks with a high proportion of renewable energy, the optimal active-reactive power dispatch problem (OARPD) is increasingly complex due to the volatility and randomness of wind and solar output, as well as variations in grid load. This paper proposes a new low-carbon scheduling m...
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10849554/ |
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| author | Furong Tu Sumei Zheng Kuncan Chen |
| author_facet | Furong Tu Sumei Zheng Kuncan Chen |
| author_sort | Furong Tu |
| collection | DOAJ |
| description | In distribution networks with a high proportion of renewable energy, the optimal active-reactive power dispatch problem (OARPD) is increasingly complex due to the volatility and randomness of wind and solar output, as well as variations in grid load. This paper proposes a new low-carbon scheduling model that incorporates a tiered carbon emission trading (CET) mechanism, minimizes operating costs, and reduces voltage deviations. Additionally, to address constraints on the number of discrete device actions within the scheduling period, a dynamic reactive power optimization strategy based on tiered operating costs is introduced. Then proposed an improved multi-objective equilibrium optimizer (IMOEO) algorithm for solving the OARPD problem with renewable generators. The IMOEO algorithm incorporates a Sobol sequence initialization method, dynamic adjustment factors, and particles that employ various evolutionary strategies based on the crowding distance. These elements are integrated to enhance population diversity and improve global exploration capabilities. Subsequently, the algorithm is applied to an modified IEEE-33 distribution network, followed by a thorough statistical analysis of the results. The findings indicate that IMOEO outperforms other methods in achieving a superior non-dominated Pareto front, effectively addresses the OARPD problem with renewable energy, and delivers high-quality solutions. |
| format | Article |
| id | doaj-art-5780748ffb8b4aadbb808fc9dc25833b |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-5780748ffb8b4aadbb808fc9dc25833b2025-01-31T00:01:10ZengIEEEIEEE Access2169-35362025-01-0113188991891110.1109/ACCESS.2025.353275010849554Optimal Active-Reactive Power Dispatch for Distribution Network With Carbon Trading Based on Improved Multi-Objective Equilibrium Optimizer AlgorithmFurong Tu0https://orcid.org/0009-0007-5923-4986Sumei Zheng1Kuncan Chen2Xiamen Ocean Vocational College, Xiamen, ChinaXiamen Ocean Vocational College, Xiamen, ChinaPower China Fujian Electric Power Survey and Design Institute Company Ltd., Fuzhou, Fujian, ChinaIn distribution networks with a high proportion of renewable energy, the optimal active-reactive power dispatch problem (OARPD) is increasingly complex due to the volatility and randomness of wind and solar output, as well as variations in grid load. This paper proposes a new low-carbon scheduling model that incorporates a tiered carbon emission trading (CET) mechanism, minimizes operating costs, and reduces voltage deviations. Additionally, to address constraints on the number of discrete device actions within the scheduling period, a dynamic reactive power optimization strategy based on tiered operating costs is introduced. Then proposed an improved multi-objective equilibrium optimizer (IMOEO) algorithm for solving the OARPD problem with renewable generators. The IMOEO algorithm incorporates a Sobol sequence initialization method, dynamic adjustment factors, and particles that employ various evolutionary strategies based on the crowding distance. These elements are integrated to enhance population diversity and improve global exploration capabilities. Subsequently, the algorithm is applied to an modified IEEE-33 distribution network, followed by a thorough statistical analysis of the results. The findings indicate that IMOEO outperforms other methods in achieving a superior non-dominated Pareto front, effectively addresses the OARPD problem with renewable energy, and delivers high-quality solutions.https://ieeexplore.ieee.org/document/10849554/Active-reactive power dispatch problemcarbon emissions tradingimproved multi-objective equilibrium optimizer algorithmoptimal power flow |
| spellingShingle | Furong Tu Sumei Zheng Kuncan Chen Optimal Active-Reactive Power Dispatch for Distribution Network With Carbon Trading Based on Improved Multi-Objective Equilibrium Optimizer Algorithm IEEE Access Active-reactive power dispatch problem carbon emissions trading improved multi-objective equilibrium optimizer algorithm optimal power flow |
| title | Optimal Active-Reactive Power Dispatch for Distribution Network With Carbon Trading Based on Improved Multi-Objective Equilibrium Optimizer Algorithm |
| title_full | Optimal Active-Reactive Power Dispatch for Distribution Network With Carbon Trading Based on Improved Multi-Objective Equilibrium Optimizer Algorithm |
| title_fullStr | Optimal Active-Reactive Power Dispatch for Distribution Network With Carbon Trading Based on Improved Multi-Objective Equilibrium Optimizer Algorithm |
| title_full_unstemmed | Optimal Active-Reactive Power Dispatch for Distribution Network With Carbon Trading Based on Improved Multi-Objective Equilibrium Optimizer Algorithm |
| title_short | Optimal Active-Reactive Power Dispatch for Distribution Network With Carbon Trading Based on Improved Multi-Objective Equilibrium Optimizer Algorithm |
| title_sort | optimal active reactive power dispatch for distribution network with carbon trading based on improved multi objective equilibrium optimizer algorithm |
| topic | Active-reactive power dispatch problem carbon emissions trading improved multi-objective equilibrium optimizer algorithm optimal power flow |
| url | https://ieeexplore.ieee.org/document/10849554/ |
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