P2P energy trading of multi-energy prosumers: An electricity-heat coupling double auction market
Abstract The double auction market is an effective way to realize P2P energy trading in the local multi-energy system. However, in the double auction market, the electricity and heat trading are often auctioned separately, which brings the difficulty of energy decoupling to multi-energy prosumers (MEPs) and increases their trading risk. Therefore, this paper designs an electricity-heat coupling double auction market (EHC-DAM), where the electricity-heat combination is regarded as a single commodity. Firstly, it introduces the local multi-energy system framework and the operation mode of EHC-DAM. Then, it proposes an “electricity-heat-price” three-dimensional supply (demand) surface for MEPs to participate in the market bidding. The bidding form of the 3D surface fully reflects the energy supply capacity and the expected economic benefit of MEP. After that, it establishes an electricity-heat coupling market clearing model aimed at maximizing social welfare, which determines the trading quantity and price of electricity and heat. And for its constrained discrete nonlinear characteristic, an improved Parallel Artificial Protozoa Optimizer (PAPO) is proposed to solve it. Finally, case studies demonstrate that the proposed EHC-DAM reduces the total energy cost of the local multi-energy system. Moreover, compared with PSO , GA and APO, the improved PAPO has stronger competitiveness. • An electricity-heat coupling double auction market is designed for P2P energy trading. • The electricity-heat combination is regarded as a single commodity. • A bidding form of the “electricity-heat-price” three-dimensional supply (demand) surface is presented. • An electricity-heat coupling market clearing model aimed at maximizing social welfare is established. • An improved Parallel Artificial Protozoa Optimizer (PAPO) is proposed to solve the proposed model.
Authors
- Zhenkun Li (ORCID: https://orcid.org/0000-0002-6512-4528)
- Jeng‐Shyang Pan (ORCID: https://orcid.org/0000-0002-3128-9025)
- Yang Fu (ORCID: https://orcid.org/0000-0002-0224-9016)
- Jie Shan
Institutions
- Nanjing University of Information Science and Technology (CN)
- Shanghai University of Electric Power (CN)
Publication Details
- Journal
- Applied Energy
- Published
- 2025-04-06
- DOI
- https://doi.org/10.1016/j.apenergy.2025.125804
- Citations
- 6
- Primary Topic
- Smart Grid Energy Management
- Type
- article
- Field-Weighted Citation Impact
- 4.38
Funders
- National Natural Science Foundation of China