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https://hdl.handle.net/10356/180243
Title: | A decentralized approach for time-of-use network utilization pricing in peer-to-peer energy markets | Authors: | Liu, Yun Gao, Yunqiang Borghetti, Alberto Li, Yuanzheng Gooi, Hoay Beng Sun, Chao Wu, Ting Zhu, Jizhong |
Keywords: | Engineering | Issue Date: | 2024 | Source: | Liu, Y., Gao, Y., Borghetti, A., Li, Y., Gooi, H. B., Sun, C., Wu, T. & Zhu, J. (2024). A decentralized approach for time-of-use network utilization pricing in peer-to-peer energy markets. Applied Energy, 361, 122919-. https://dx.doi.org/10.1016/j.apenergy.2024.122919 | Journal: | Applied Energy | Abstract: | In an established peer-to-peer (P2P) energy market, network utilization fees should be charged by the distribution network service provider (DNSP) to sustain the operation and maintenance of active distribution networks. However, the understanding on how to rationally determine appropriate network utilization prices (NUPs) that are sufficient for the development of the power distribution infrastructure is lacking. To fill this gap, a decentralized approach for optimal time-of-use (TOU) NUPs is developed for day-ahead P2P energy markets. First, the interaction between the DNSP and multiple prosumers is modeled as a bi-level Stackelberg-generalized Nash game, with the DNSP acting as the leader to determine the TOU NUPs, while the prosumers follow P2P energy trading. Subsequently, a decentralized joint trading approach is developed in which the DNSP updates the TOU NUPs based on an approximate gradient ascent (AGA) method via gradient sampling, and the prosumers respond with optimal P2P energy trading via price negotiation. These two processes can recursively converge to a market equilibrium. Finally, a directional gradient guidance heuristic module is developed to accelerate the convergence performance of the joint trading process. Various case studies on a standard IEEE test feeder comprising ten prosumers are performed to validate the effectiveness and efficiency of the proposed approach. | URI: | https://hdl.handle.net/10356/180243 | ISSN: | 0306-2619 | DOI: | 10.1016/j.apenergy.2024.122919 | Schools: | School of Electrical and Electronic Engineering | Rights: | © 2024 Elsevier Ltd. All rights reserved. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | EEE Journal Articles |
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