Cheng, Xiaoyuan;
Yao, Ruiqiu;
Postnikov, Andrey;
Hu, Yukun;
Varga, Liz;
(2024)
Decentralized intelligent multi-party competitive aggregation framework for electricity prosumers.
Applied Energy
, 373
, Article 123860. 10.1016/j.apenergy.2024.123860.
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Abstract
Electricity management systems are experiencing significant challenges due to the increased penetration of distributed energy resources. Electricity flows in distribution networks are transforming from unidirectional to bi-directional form. Consumers are transitioning to prosumers with different characteristics, where they take more active roles in electricity generation and consumption. Aggregators are vital financial intermediary agents in the power system transitions, as they could aggregate energy profiles of prosumers. The market competition between aggregators and interactions between prosumers and aggregators are complex and dynamic, which requires a holistic framework to model the market competition. This paper proposes an intelligent aggregation framework with edge computing, enabling decentralized competition for multiple aggregators and prosumers, which can be solved with a graph-based consensus algorithm. This study mathematically proves the proposed algorithm's convergence guarantee and convergence rate. In addition, the proposed framework is applied to an open-source dataset to demonstrate its applicability. Lastly, a benchmark analysis is conducted to show that the proposed algorithm has better communication complexity than the benchmark algorithms.
| Type: | Article |
|---|---|
| Title: | Decentralized intelligent multi-party competitive aggregation framework for electricity prosumers |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.apenergy.2024.123860 |
| Publisher version: | https://doi.org/10.1016/j.apenergy.2024.123860 |
| Language: | English |
| Additional information: | © 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Intelligent aggregation, Prosumers, Energy transition, Edge computing, Distributed energy resources, Graph-based consensus algorithm |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10194877 |
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