Research on wind-solar-storage system optimal scheduling based on multi-objective particle swarm algorithm
For the current problems that economic benefit and energy saving can not be considered in the existing optimal scheduling schemes of wind-solar-diesel-storage system, this paper proposes an optimal scheduling scheme of this system based on multi-objective particle swarm optimization. The mathematica...
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| Vydáno v: | Journal of physics. Conference series Ročník 2636; číslo 1; s. 12011 - 12019 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Bristol
IOP Publishing
01.11.2023
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| ISSN: | 1742-6588, 1742-6596 |
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| Abstract | For the current problems that economic benefit and energy saving can not be considered in the existing optimal scheduling schemes of wind-solar-diesel-storage system, this paper proposes an optimal scheduling scheme of this system based on multi-objective particle swarm optimization. The mathematical models of active power output of wind turbines, solar turbines and energy storage units of wind-solar-diesel-storage system are established respectively. According to the historical data of wind power generation and photovoltaic power generation, the power prediction data of corresponding prediction models are adopted respectively On this basis, the objective function is constructed by minimizing the operating cost of the system and maximizing the wind-solar consumption ratio, and the system active power, energy storage battery capacity and diesel generator power are taken as constraints Using multi-objective particle swarm optimization algorithm to solve the output of each unit in the system. Simulation results illustrate the optimization scheme can well achieve the target of taking into account both economic benefits and energy saving in the optimal scheduling of wind-solar-diesel-storage system. |
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| AbstractList | For the current problems that economic benefit and energy saving can not be considered in the existing optimal scheduling schemes of wind-solar-diesel-storage system, this paper proposes an optimal scheduling scheme of this system based on multi-objective particle swarm optimization. The mathematical models of active power output of wind turbines, solar turbines and energy storage units of wind-solar-diesel-storage system are established respectively. According to the historical data of wind power generation and photovoltaic power generation, the power prediction data of corresponding prediction models are adopted respectively On this basis, the objective function is constructed by minimizing the operating cost of the system and maximizing the wind-solar consumption ratio, and the system active power, energy storage battery capacity and diesel generator power are taken as constraints Using multi-objective particle swarm optimization algorithm to solve the output of each unit in the system. Simulation results illustrate the optimization scheme can well achieve the target of taking into account both economic benefits and energy saving in the optimal scheduling of wind-solar-diesel-storage system. |
| Author | Sui, Yi Wang, Bo Chen, Zhouyang Fan, Bo Ru, Huitong Zhao, Jisheng Huang, Zhe |
| Author_xml | – sequence: 1 givenname: Huitong surname: Ru fullname: Ru, Huitong organization: China Three Gorges Renewables (Qingyun) Co., Ltd , China – sequence: 2 givenname: Jisheng surname: Zhao fullname: Zhao, Jisheng organization: China Three Gorges Renewables (Qingyun) Co., Ltd , China – sequence: 3 givenname: Yi surname: Sui fullname: Sui, Yi organization: China Three Gorges Renewables (Qingyun) Co., Ltd , China – sequence: 4 givenname: Zhe surname: Huang fullname: Huang, Zhe organization: China Three Gorges Renewables (Qingyun) Co., Ltd , China – sequence: 5 givenname: Zhouyang surname: Chen fullname: Chen, Zhouyang organization: China Three Gorges Renewables (Qingyun) Co., Ltd , China – sequence: 6 givenname: Bo surname: Fan fullname: Fan, Bo organization: China Three Gorges Renewables (Qingyun) Co., Ltd , China – sequence: 7 givenname: Bo surname: Wang fullname: Wang, Bo organization: China Three Gorges Renewables (Qingyun) Co., Ltd , China |
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| Cites_doi | 10.1109/TIA.2021.3105497 10.1016/j.energy.2018.04.004 |
| ContentType | Journal Article |
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| DOI | 10.1088/1742-6596/2636/1/012011 |
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| References | Wen (JPCS_2636_1_012011bib1) 2022; 43 Kaiyan (JPCS_2636_1_012011bib2) 2022 Lu (JPCS_2636_1_012011bib3) 2022 Shiying (JPCS_2636_1_012011bib6) 2021; 57 Yimin (JPCS_2636_1_012011bib5) 2020; 9 Hemmati (JPCS_2636_1_012011bib4) 2018; 152 |
| References_xml | – start-page: 36 year: 2022 ident: JPCS_2636_1_012011bib2 – volume: 57 start-page: 6547 year: 2021 ident: JPCS_2636_1_012011bib6 article-title: A control strategy based on deep reinforcement learning under the combined wind-solar storage system [J] publication-title: IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS doi: 10.1109/TIA.2021.3105497 – volume: 9 start-page: 918 year: 2020 ident: JPCS_2636_1_012011bib5 article-title: Study on optimal capacity allocation of wind-solar-diesel-storage hybrid power generation system based on longicorn beard search genetic algorithm [J] publication-title: Energy Storage Science and Technology – volume: 152 start-page: 759 year: 2018 ident: JPCS_2636_1_012011bib4 article-title: Power fluctuation smoothing and loss reduction in grid integrated with thermal wind-solar-storage units. [J] publication-title: Energy doi: 10.1016/j.energy.2018.04.004 – start-page: 1283 year: 2022 ident: JPCS_2636_1_012011bib3 – volume: 43 start-page: 453 year: 2022 ident: JPCS_2636_1_012011bib1 article-title: Operation strategy of optimal allocation of wind, solar and diesel storage microgrid capacity. [J] publication-title: Acta Solar Energy Sinica |
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| SubjectTerms | Algorithms Diesel generators Energy storage Mathematical models Multiple objective analysis Optimization Particle swarm optimization Prediction models Scheduling Storage batteries Storage units Wind power generation Wind turbines |
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| Title | Research on wind-solar-storage system optimal scheduling based on multi-objective particle swarm algorithm |
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