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学者姓名:陈昌铭

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Stochastic Distributionally Robust Optimization Scheduling of High-Proportion New Energy Distribution Network Considering Detailed Modeling of Energy Storage SCIE
期刊论文 | 2025 , 13 (7) | PROCESSES
WoS CC Cited Count: 1
Abstract&Keyword Cite Version(2)

Abstract :

In the context of building a new type of power system, the optimal operation of high-proportion new-energy distribution networks (HNEDNs) is a current hot topic. In this paper, a stochastic distribution robust optimization method for HNEDNs that considers energy-storage refinement modeling is proposed. First, an energy-storage lifetime loss model based on the rainfall-counting method is constructed, and then an optimal operation model of an HNEDN considering energy storage refinement modeling is constructed, aiming to minimize the total operation cost while taking into account the energy cost and the penalty cost of abandoning wind and solar power. Then, a source-load uncertainty model of HNEDN is constructed based on the Wasserstein distance and conditional value at risk (CvaR) theory, and the HNEDN optimization model is reconstructed based on the stochastic distribution robust optimization method; based on this, the multiple linearization technique is introduced to approximate the reconstructed model, which aims to both reduce the difficulty in solving the model and ensure the quality of the solution. Finally, the modified IEEE 33-bus power distribution system is used as an example for case analysis, and the simulation results show that the method presented in this paper, through reducing the loss of life in the battery storage device, can reduce the average daily energy storage depreciation cost compared to an HNEDN optimization method that does not take the energy storage life loss into account; this, in turn, reduces the total operating cost of the system. In addition, the stochastic distribution robust optimization method used in this paper can adaptively adjust the economy and robustness of the HNEDN operation strategy according to the confidence level and the available historical sample data on new energy-output prediction errors to obtain the optimal HNEDN operation strategy when compared with other uncertainty treatment methods.

Keyword :

distribution network distribution network energy storage energy storage high-proportion new energy high-proportion new energy optimal operation optimal operation stochastic distributionally robust optimization stochastic distributionally robust optimization

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GB/T 7714 Lin, Bin , Huang, Yan , Yu, Dingwen et al. Stochastic Distributionally Robust Optimization Scheduling of High-Proportion New Energy Distribution Network Considering Detailed Modeling of Energy Storage [J]. | PROCESSES , 2025 , 13 (7) .
MLA Lin, Bin et al. "Stochastic Distributionally Robust Optimization Scheduling of High-Proportion New Energy Distribution Network Considering Detailed Modeling of Energy Storage" . | PROCESSES 13 . 7 (2025) .
APA Lin, Bin , Huang, Yan , Yu, Dingwen , Fu, Chenjie , Chen, Changming . Stochastic Distributionally Robust Optimization Scheduling of High-Proportion New Energy Distribution Network Considering Detailed Modeling of Energy Storage . | PROCESSES , 2025 , 13 (7) .
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Stochastic Distributionally Robust Optimization Scheduling of High-Proportion New Energy Distribution Network Considering Detailed Modeling of Energy Storage EI
期刊论文 | 2025 , 13 (7) | Processes
Stochastic Distributionally Robust Optimization Scheduling of High-Proportion New Energy Distribution Network Considering Detailed Modeling of Energy Storage Scopus
期刊论文 | 2025 , 13 (7) | Processes
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