LAPSE:2023.10890
Published Article

LAPSE:2023.10890
Energy Loss Reduction for Distribution Networks with Energy Storage Systems via Loss Sensitive Factor Method
February 27, 2023
Abstract
The loss of distribution networks caused by various electrical motors including transformers and generators can significantly affect the efficiency and economical operation of the power grid, especially for new power systems with high penetration of renewable energies. In this paper, the potential of using an energy storage system (ESS) for loss reduction is investigated, where a novel two-stage method for key-bus selection and ESS scheduling is proposed. At the first stage, the most sensitive key buses to the variation of load are selected by using the loss sensitive factors (LSF) method. At the second stage, ESS scheduling is conducted by solving an optimization problem with uncertainties caused by high penetration of renewable energies, where the uncertainties are characterized by confidence levels. The optimal scheduling of ESS including locations, capacities, and working modes are obtained at the second stage. The effectiveness of the proposed method is demonstrated via numerical simulations. The influences of capacities of ESS and confidence levels with respect to uncertainties are also analyzed. It is demonstrated that the loss-reduction performances can be improved if the ESSs are deployed on the buses selected by the LSF method and operated under the developed optimal scheduling method.
The loss of distribution networks caused by various electrical motors including transformers and generators can significantly affect the efficiency and economical operation of the power grid, especially for new power systems with high penetration of renewable energies. In this paper, the potential of using an energy storage system (ESS) for loss reduction is investigated, where a novel two-stage method for key-bus selection and ESS scheduling is proposed. At the first stage, the most sensitive key buses to the variation of load are selected by using the loss sensitive factors (LSF) method. At the second stage, ESS scheduling is conducted by solving an optimization problem with uncertainties caused by high penetration of renewable energies, where the uncertainties are characterized by confidence levels. The optimal scheduling of ESS including locations, capacities, and working modes are obtained at the second stage. The effectiveness of the proposed method is demonstrated via numerical simulations. The influences of capacities of ESS and confidence levels with respect to uncertainties are also analyzed. It is demonstrated that the loss-reduction performances can be improved if the ESSs are deployed on the buses selected by the LSF method and operated under the developed optimal scheduling method.
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Keywords
chance constraint, energy storage system, loss reduction, loss sensitivity factors, Renewable and Sustainable Energy
Subject
Suggested Citation
Wu X, Yang C, Han G, Ye Z, Hu Y. Energy Loss Reduction for Distribution Networks with Energy Storage Systems via Loss Sensitive Factor Method. (2023). LAPSE:2023.10890
Author Affiliations
Wu X: State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050021, China
Yang C: State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050021, China
Han G: State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050021, China
Ye Z: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Hu Y: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Yang C: State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050021, China
Han G: State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050021, China
Ye Z: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Hu Y: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Journal Name
Energies
Volume
15
Issue
15
First Page
5453
Year
2022
Publication Date
2022-07-27
ISSN
1996-1073
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Original Submission
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PII: en15155453, Publication Type: Journal Article
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LAPSE:2023.10890
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https://doi.org/10.3390/en15155453
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Feb 27, 2023
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