eprintid: 10194877
rev_number: 7
eprint_status: archive
userid: 699
dir: disk0/10/19/48/77
datestamp: 2024-07-22 09:51:26
lastmod: 2024-07-22 09:51:26
status_changed: 2024-07-22 09:51:26
type: article
metadata_visibility: show
sword_depositor: 699
creators_name: Cheng, Xiaoyuan
creators_name: Yao, Ruiqiu
creators_name: Postnikov, Andrey
creators_name: Hu, Yukun
creators_name: Varga, Liz
title: Decentralized intelligent multi-party competitive aggregation framework for electricity prosumers
ispublished: pub
divisions: UCL
divisions: B04
divisions: F44
keywords: Intelligent aggregation, 
Prosumers, 
Energy transition, 
Edge computing, 
Distributed energy resources, 
Graph-based consensus algorithm
note: © 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/).
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.
date: 2024-11
date_type: published
publisher: Elsevier BV
official_url: https://doi.org/10.1016/j.apenergy.2024.123860
oa_status: green
full_text_type: pub
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 2298373
doi: 10.1016/j.apenergy.2024.123860
lyricists_name: Hu, Yukun
lyricists_id: YHUDX81
actors_name: Hu, Yukun
actors_id: YHUDX81
actors_role: owner
full_text_status: public
publication: Applied Energy
volume: 373
article_number: 123860
issn: 0306-2619
citation:        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 <https://doi.org/10.1016/j.apenergy.2024.123860>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10194877/1/Decentralized%20intelligent%20multi-party%20competitive%20aggregation%20framework%20for%20electricity%20prosumers.pdf