Economic optimization scheduling of microgrid group based on chaotic mapping optimization BOA algorithm
Abstract Due to the intermittency and volatility of distributed power sources, the microgrid system has poor stability and high operation cost. Therefore, the study proposes an economic optimization scheduling strategy based on the chaotic mapping butterfly optimization algorithm and the mathematica...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2024-12-01
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| Series: | Energy Informatics |
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| Online Access: | https://doi.org/10.1186/s42162-024-00422-3 |
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| _version_ | 1846136791131750400 |
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| author | Milu Zhou Yu Wang Tingting Li Tian Yang Xi Luo |
| author_facet | Milu Zhou Yu Wang Tingting Li Tian Yang Xi Luo |
| author_sort | Milu Zhou |
| collection | DOAJ |
| description | Abstract Due to the intermittency and volatility of distributed power sources, the microgrid system has poor stability and high operation cost. Therefore, the study proposes an economic optimization scheduling strategy based on the chaotic mapping butterfly optimization algorithm and the mathematical model of microgrid group system. The study creates simulation trials of function poles and microgrid group operation to confirm the strategy’s efficacy. According to the experimental findings, the multimodal function of the enhanced butterfly optimization method had a variance of 0.0000E + 00, and the function’s optimal value was less than 10–30, and the calculation time is 4.5s. The variance on the fixed dimensional function was 0.0000E + 00 and the optimal value of the function was 10 − 3.5,and the calculation time is 4.7s. The algorithmic curve all digging depth was maximum and convergence speed was fastest. The microgrid group system had the lowest economic cost of 4029.32 yuan in the grid-connected mode and 3343.39 yuan in the off-grid mode. The study proves that the energy coordination and economic management of this strategy are greatly optimized, which can effectively protect the energy storage equipment and guarantee the smooth power consumption of the system. This provides an innovative theoretical basis for optimization scheduling of microgrid group. |
| format | Article |
| id | doaj-art-b541f0f24938422d8be2419768d5d40b |
| institution | Kabale University |
| issn | 2520-8942 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Energy Informatics |
| spelling | doaj-art-b541f0f24938422d8be2419768d5d40b2024-12-08T12:47:21ZengSpringerOpenEnergy Informatics2520-89422024-12-017111710.1186/s42162-024-00422-3Economic optimization scheduling of microgrid group based on chaotic mapping optimization BOA algorithmMilu Zhou0Yu Wang1Tingting Li2Tian Yang3Xi Luo4Nanning Power Supply Bureau of Guangxi Power Grid Co. LtdNanning Power Supply Bureau of Guangxi Power Grid Co. LtdNanning Power Supply Bureau of Guangxi Power Grid Co. LtdNanning Power Supply Bureau of Guangxi Power Grid Co. LtdNanning Power Supply Bureau of Guangxi Power Grid Co. LtdAbstract Due to the intermittency and volatility of distributed power sources, the microgrid system has poor stability and high operation cost. Therefore, the study proposes an economic optimization scheduling strategy based on the chaotic mapping butterfly optimization algorithm and the mathematical model of microgrid group system. The study creates simulation trials of function poles and microgrid group operation to confirm the strategy’s efficacy. According to the experimental findings, the multimodal function of the enhanced butterfly optimization method had a variance of 0.0000E + 00, and the function’s optimal value was less than 10–30, and the calculation time is 4.5s. The variance on the fixed dimensional function was 0.0000E + 00 and the optimal value of the function was 10 − 3.5,and the calculation time is 4.7s. The algorithmic curve all digging depth was maximum and convergence speed was fastest. The microgrid group system had the lowest economic cost of 4029.32 yuan in the grid-connected mode and 3343.39 yuan in the off-grid mode. The study proves that the energy coordination and economic management of this strategy are greatly optimized, which can effectively protect the energy storage equipment and guarantee the smooth power consumption of the system. This provides an innovative theoretical basis for optimization scheduling of microgrid group.https://doi.org/10.1186/s42162-024-00422-3Butterfly optimization algorithmMicrogrid swarmChaotic mappingSimplex form methodOptimization scheduling |
| spellingShingle | Milu Zhou Yu Wang Tingting Li Tian Yang Xi Luo Economic optimization scheduling of microgrid group based on chaotic mapping optimization BOA algorithm Energy Informatics Butterfly optimization algorithm Microgrid swarm Chaotic mapping Simplex form method Optimization scheduling |
| title | Economic optimization scheduling of microgrid group based on chaotic mapping optimization BOA algorithm |
| title_full | Economic optimization scheduling of microgrid group based on chaotic mapping optimization BOA algorithm |
| title_fullStr | Economic optimization scheduling of microgrid group based on chaotic mapping optimization BOA algorithm |
| title_full_unstemmed | Economic optimization scheduling of microgrid group based on chaotic mapping optimization BOA algorithm |
| title_short | Economic optimization scheduling of microgrid group based on chaotic mapping optimization BOA algorithm |
| title_sort | economic optimization scheduling of microgrid group based on chaotic mapping optimization boa algorithm |
| topic | Butterfly optimization algorithm Microgrid swarm Chaotic mapping Simplex form method Optimization scheduling |
| url | https://doi.org/10.1186/s42162-024-00422-3 |
| work_keys_str_mv | AT miluzhou economicoptimizationschedulingofmicrogridgroupbasedonchaoticmappingoptimizationboaalgorithm AT yuwang economicoptimizationschedulingofmicrogridgroupbasedonchaoticmappingoptimizationboaalgorithm AT tingtingli economicoptimizationschedulingofmicrogridgroupbasedonchaoticmappingoptimizationboaalgorithm AT tianyang economicoptimizationschedulingofmicrogridgroupbasedonchaoticmappingoptimizationboaalgorithm AT xiluo economicoptimizationschedulingofmicrogridgroupbasedonchaoticmappingoptimizationboaalgorithm |