A Benders decomposition approach for solving a two-stage local energy market problem under uncertainty

New consumer-centric electricity market schemes have emerged as an alternative to manage the energy balancing locally in distribution networks with high distributed energy resources (DERs) penetration. Peer-to-peer (P2P) energy trading has become an attractive scheme for reducing user and distributi...

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Vydané v:Applied energy Ročník 329; s. 120226
Hlavní autori: García-Muñoz, Fernando, Dávila, Sebastián, Quezada, Franco
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 01.01.2023
Predmet:
algorithms
batteries
Benders decomposition
electricity
energy
information exchange
Local energy markets
markets
Peer-to-peer energy trading
Strengthened Benders’ cuts
trade
Two-stage stochastic programming
uncertainty
Local energy markets
Strengthened Benders’ cuts
Benders decomposition
Two-stage stochastic programming
Peer-to-peer energy trading
ISSN:0306-2619, 1872-9118
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Popis
Shrnutí:New consumer-centric electricity market schemes have emerged as an alternative to manage the energy balancing locally in distribution networks with high distributed energy resources (DERs) penetration. Peer-to-peer (P2P) energy trading has become an attractive scheme for reducing user and distribution system operators (DSO) costs through the energy surplus exchange between the energy community users, where the uncertainty of DERs and the consumption are challenging issues that require suitable managing for a proper market operation. This article presents a novel two-stage stochastic mixed-integer linear programming model to address the scheduling day-ahead problem of an energy community operating under a P2P energy trading scheme. The formulation proposed minimizes the expected community cost considering the network limitations, ensuring fair trading in the local energy market (LEM), and allowing the prosumers to act as buyers or sellers depending on their load consumption and self-generation. In order to reduce the shared information by consumers/prosumers that trade energy, the proposed model is decomposed into a master problem (MP) and subproblems (SPs) to manage the network constraints and the market requirements, respectively. With this purpose, the Benders decomposition approach is implemented using the recently introduced Strengthened Benders cuts to address the binary variables related to the market and battery operation in the SPs. The model and the algorithm are tested in the 69-bus radial distribution system, considering from 3 to 39 agents trading energy to measure the model scalability. In this analysis, the algorithm convergence shows that the proposed methodology reduces the LEM’s shared information without increasing the energy community cost. •A novel stochastic programming P2P energy trading model is presented.•The Strengthened Benders cuts are used to preserve users’ information.•Relaxing binary variables could overestimate the energy traded in the LEM.•The individual benefit could be affected to maximize the community welfare.•A scalability assessment is developed considering 39 users trading energy.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0306-2619
1872-9118
DOI:10.1016/j.apenergy.2022.120226