LAPSE:2023.8842
Published Article

LAPSE:2023.8842
An Optimal Allocation Method of Distributed PV and Energy Storage Considering Moderate Curtailment Measure
February 24, 2023
Abstract
Increasing distributed generations (DGs) are integrated into the distribution network. The risk of not satisfying operation constraints caused by the uncertainty of renewable energy output is increasing. The energy storage (ES) could stabilize the fluctuation of renewable energy generation output. Therefore, it can promote the consumption of renewable energy. A distributed photovoltaic (PV) and ES optimal allocation method based on the security region is proposed. Firstly, a bi-level optimal allocation model of PV and ES is established. The outer layer is a nonlinear optimization model, taking the maximum power supply benefit as the objective function. The inner layer is a day-ahead economic dispatching model. Then, a quick model solving method based on the steady-state security region is proposed. An initial allocation scheme of PV and ES is determined with the redundancy capacity. In addition, the linear hyperplane coefficient of the security region is used to convert the nonlinear day-ahead economic dispatching model into a linear one. Finally, the proposed method is used to analyze the improved IEEE 33-node system. It is found that a moderate curtailment measure of distributed PV peak output and the allocation of energy storage have a significant effect on the power supply benefit of the distribution system. The optimal quota capacity of DG exceeds the sum of the maximum load and the branch capacity. In addition, the optimal allocation scheme is closely related to the cost and technical parameters of distributed PV and ES. Dynamic allocation schemes should be formulated for distribution network.
Increasing distributed generations (DGs) are integrated into the distribution network. The risk of not satisfying operation constraints caused by the uncertainty of renewable energy output is increasing. The energy storage (ES) could stabilize the fluctuation of renewable energy generation output. Therefore, it can promote the consumption of renewable energy. A distributed photovoltaic (PV) and ES optimal allocation method based on the security region is proposed. Firstly, a bi-level optimal allocation model of PV and ES is established. The outer layer is a nonlinear optimization model, taking the maximum power supply benefit as the objective function. The inner layer is a day-ahead economic dispatching model. Then, a quick model solving method based on the steady-state security region is proposed. An initial allocation scheme of PV and ES is determined with the redundancy capacity. In addition, the linear hyperplane coefficient of the security region is used to convert the nonlinear day-ahead economic dispatching model into a linear one. Finally, the proposed method is used to analyze the improved IEEE 33-node system. It is found that a moderate curtailment measure of distributed PV peak output and the allocation of energy storage have a significant effect on the power supply benefit of the distribution system. The optimal quota capacity of DG exceeds the sum of the maximum load and the branch capacity. In addition, the optimal allocation scheme is closely related to the cost and technical parameters of distributed PV and ES. Dynamic allocation schemes should be formulated for distribution network.
Record ID
Keywords
day-ahead economic dispatching, distribution system planning, optimal allocation method, power supply benefit, redundancy capacity, steady-state security region
Subject
Suggested Citation
Liang G, Sun B, Zeng Y, Ge L, Li Y, Wang Y. An Optimal Allocation Method of Distributed PV and Energy Storage Considering Moderate Curtailment Measure. (2023). LAPSE:2023.8842
Author Affiliations
Liang G: School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
Sun B: School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China [ORCID]
Zeng Y: School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China [ORCID]
Ge L: School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China [ORCID]
Li Y: State Grid Tianjin Electric Power Co., Ltd., Tianjin 300300, China
Wang Y: State Grid Tianjin Electric Power Co., Ltd., Tianjin 300300, China
Sun B: School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China [ORCID]
Zeng Y: School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China [ORCID]
Ge L: School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China [ORCID]
Li Y: State Grid Tianjin Electric Power Co., Ltd., Tianjin 300300, China
Wang Y: State Grid Tianjin Electric Power Co., Ltd., Tianjin 300300, China
Journal Name
Energies
Volume
15
Issue
20
First Page
7690
Year
2022
Publication Date
2022-10-18
ISSN
1996-1073
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Original Submission
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PII: en15207690, Publication Type: Journal Article
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LAPSE:2023.8842
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https://doi.org/10.3390/en15207690
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Feb 24, 2023
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