User-side Cloud Energy Storage Locating and Capacity Configuration

Under the background of new power system, economic and effective utilization of energy storage to realize power storage and controllable transfer is an effective way to enhance the new energy consumption and maintain the stability of power system. In this paper, a cloud energy storage(CES) model is...

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Vydáno v:2023 IEEE 7th Conference on Energy Internet and Energy System Integration (EI2) s. 2980 - 2985
Hlavní autoři: Ma, Yongji, Cao, Fen, Zhou, Zhihang, Yang, Anyuan, Wang, Huifang
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 15.12.2023
Témata:
Analytical models
Cloud computing
cloud energy storage (CES)
configuration
Energy resources
Power system stability
Scheduling
sharing model
Time series analysis
user-side
Voltage
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Abstract Under the background of new power system, economic and effective utilization of energy storage to realize power storage and controllable transfer is an effective way to enhance the new energy consumption and maintain the stability of power system. In this paper, a cloud energy storage(CES) model is proposed, which firstly establishes a wind- PV -load time series model based LHS and K-medoids to complete the scenario generation and reduction. MOPSO algorithm is used to achieve the centralized energy storage configuration with voltage, load volatility, and the total cost of social energy use as the indexes. Afterwards, a segmented model is suggested on this basis to realize CES day-ahead scheduling. Eventually, based on the Shapley value, the revenue settlement of users within the cloud is accomplished. The simulated CES model enables the cooperative call of multiple energy storage, which is sufficiently organized and balances the benefits of each subject to ensure the sustainable development of the model.
AbstractList Under the background of new power system, economic and effective utilization of energy storage to realize power storage and controllable transfer is an effective way to enhance the new energy consumption and maintain the stability of power system. In this paper, a cloud energy storage(CES) model is proposed, which firstly establishes a wind- PV -load time series model based LHS and K-medoids to complete the scenario generation and reduction. MOPSO algorithm is used to achieve the centralized energy storage configuration with voltage, load volatility, and the total cost of social energy use as the indexes. Afterwards, a segmented model is suggested on this basis to realize CES day-ahead scheduling. Eventually, based on the Shapley value, the revenue settlement of users within the cloud is accomplished. The simulated CES model enables the cooperative call of multiple energy storage, which is sufficiently organized and balances the benefits of each subject to ensure the sustainable development of the model.
Author Ma, Yongji
Wang, Huifang
Cao, Fen
Zhou, Zhihang
Yang, Anyuan
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  surname: Ma
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  givenname: Fen
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  givenname: Zhihang
  surname: Zhou
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  organization: Hubei Electric Power Co., Ltd,State Grid,Wuhan,China
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  givenname: Anyuan
  surname: Yang
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  organization: Hubei Electric Power Co., Ltd,State Grid,Wuhan,China
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  givenname: Huifang
  surname: Wang
  fullname: Wang, Huifang
  email: huifangwang@zju.edu.cn
  organization: College of Electrical Engineering, Zhejiang University,Hangzhou,China
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SubjectTerms Analytical models
Cloud computing
cloud energy storage (CES)
configuration
Energy resources
Power system stability
Scheduling
sharing model
Time series analysis
user-side
Voltage
Title User-side Cloud Energy Storage Locating and Capacity Configuration
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