Optimization Configuration Method of Energy Storage Considering Photovoltaic Power Consumption and Source-Load Uncertainty
The proposal of a “double carbon” target has resulted in a gradual and continuous increase in the proportion of photovoltaic (PV) access to the distribution network area. To enhance the capability of PV consumption and mitigate the voltage overrun issue stemming from the substa...
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| Format: | Article |
| Language: | English |
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2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10836714/ |
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| author | Junjie Qiao Xiaofang Meng Weigang Zheng Pengxue Huang Tiefeng Xu Yupeng Xu |
| author_facet | Junjie Qiao Xiaofang Meng Weigang Zheng Pengxue Huang Tiefeng Xu Yupeng Xu |
| author_sort | Junjie Qiao |
| collection | DOAJ |
| description | The proposal of a “double carbon” target has resulted in a gradual and continuous increase in the proportion of photovoltaic (PV) access to the distribution network area. To enhance the capability of PV consumption and mitigate the voltage overrun issue stemming from the substantial PV access proportion, this paper presents a multi-objective energy storage optimization allocation methodology. Firstly, a PV and load uncertainty model is established based on Beta and Normal distributions, and the Monte Carlo Method (MC) is used to simulate the annual output. The representative scenarios are obtained after the combination is cut down by the K-means clustering algorithm. The poor operation scenarios are identified by using the variation of the maximum total node voltage deviation. Finally, an energy storage optimization allocation is proposed. Subsequently, the objective function, which seeks to minimize the total daily operating cost of the energy storage system and the PV abandonment rate, is constructed using the evaluation-based function method. The constraints, including node voltage and energy storage device, are considered, and the model is solved using the improved grey wolf optimization algorithm. Finally, a distribution network station system is employed to compare and analyze the capacity allocation results of poor operation scenarios under different schemes, the results showed that after energy storage optimization, the voltage of each scheme decreased from 0.4869kV to 0.42kV, and the curtailment rate decreased by 13.09%, 21.33%, and 23.69% respectively compared to before optimization,which verifies the effectiveness of the models and methods proposed in this paper. |
| format | Article |
| id | doaj-art-fa5f4c1695434e6193571b1ebc8864e4 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-fa5f4c1695434e6193571b1ebc8864e42025-01-24T00:02:08ZengIEEEIEEE Access2169-35362025-01-01139401941210.1109/ACCESS.2025.352805010836714Optimization Configuration Method of Energy Storage Considering Photovoltaic Power Consumption and Source-Load UncertaintyJunjie Qiao0https://orcid.org/0009-0008-7366-4891Xiaofang Meng1Weigang Zheng2Pengxue Huang3Tiefeng Xu4Yupeng Xu5College of Information and Electric Engineering, Shenyang Agricultural University, Shenyang, ChinaCollege of Information and Electric Engineering, Shenyang Agricultural University, Shenyang, ChinaState Grid Liaoning Electric Power Company Ltd. Electric Power Science Research Institute, Shenyang, ChinaCollege of Information and Electric Engineering, Shenyang Agricultural University, Shenyang, ChinaFushun Power Supply Company of State Grid, Fushun, ChinaCollege of Information and Electric Engineering, Shenyang Agricultural University, Shenyang, ChinaThe proposal of a “double carbon” target has resulted in a gradual and continuous increase in the proportion of photovoltaic (PV) access to the distribution network area. To enhance the capability of PV consumption and mitigate the voltage overrun issue stemming from the substantial PV access proportion, this paper presents a multi-objective energy storage optimization allocation methodology. Firstly, a PV and load uncertainty model is established based on Beta and Normal distributions, and the Monte Carlo Method (MC) is used to simulate the annual output. The representative scenarios are obtained after the combination is cut down by the K-means clustering algorithm. The poor operation scenarios are identified by using the variation of the maximum total node voltage deviation. Finally, an energy storage optimization allocation is proposed. Subsequently, the objective function, which seeks to minimize the total daily operating cost of the energy storage system and the PV abandonment rate, is constructed using the evaluation-based function method. The constraints, including node voltage and energy storage device, are considered, and the model is solved using the improved grey wolf optimization algorithm. Finally, a distribution network station system is employed to compare and analyze the capacity allocation results of poor operation scenarios under different schemes, the results showed that after energy storage optimization, the voltage of each scheme decreased from 0.4869kV to 0.42kV, and the curtailment rate decreased by 13.09%, 21.33%, and 23.69% respectively compared to before optimization,which verifies the effectiveness of the models and methods proposed in this paper.https://ieeexplore.ieee.org/document/10836714/Monte Carlo methoddistribution network transformer areasource-load uncertaintyphotovoltaic consumptionscene analysis |
| spellingShingle | Junjie Qiao Xiaofang Meng Weigang Zheng Pengxue Huang Tiefeng Xu Yupeng Xu Optimization Configuration Method of Energy Storage Considering Photovoltaic Power Consumption and Source-Load Uncertainty IEEE Access Monte Carlo method distribution network transformer area source-load uncertainty photovoltaic consumption scene analysis |
| title | Optimization Configuration Method of Energy Storage Considering Photovoltaic Power Consumption and Source-Load Uncertainty |
| title_full | Optimization Configuration Method of Energy Storage Considering Photovoltaic Power Consumption and Source-Load Uncertainty |
| title_fullStr | Optimization Configuration Method of Energy Storage Considering Photovoltaic Power Consumption and Source-Load Uncertainty |
| title_full_unstemmed | Optimization Configuration Method of Energy Storage Considering Photovoltaic Power Consumption and Source-Load Uncertainty |
| title_short | Optimization Configuration Method of Energy Storage Considering Photovoltaic Power Consumption and Source-Load Uncertainty |
| title_sort | optimization configuration method of energy storage considering photovoltaic power consumption and source load uncertainty |
| topic | Monte Carlo method distribution network transformer area source-load uncertainty photovoltaic consumption scene analysis |
| url | https://ieeexplore.ieee.org/document/10836714/ |
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