Peer to peer transactive energy for multiple energy hub with the penetration of high-level renewable energy
Release time:2021-08-01
Hits:
- Indexed by:
- Journal paper
- First Author:
- Wei Gan
- Correspondence Author:
- Mingyu Yan
- Co-author:
- Wei Yao,Jinyu Wen
- Journal:
- Applied Energy
- Included Journals:
- SCI
- Place of Publication:
- United Kingdom
- Discipline:
- Engineering
- First-Level Discipline:
- Electrical Engineering
- Document Type:
- J
- Volume:
- 295
- Page Number:
- 117027
- Key Words:
- Energy hub; Renewable energy; Peer-to-peer transaction; Transactive energy; Cooperative game; Column constraints generation
- DOI number:
- 10.1016/j.apenergy.2021.117027
- Date of Publication:
- 2021-08-01
- Impact Factor:
- 11.446
- Abstract:
- Energy hub (EH) has attracted worldwide appeals and shows broad prospects in promoting high-level renewable energy integration as well as supplying various loads with high flexibility. Although the cooperation of multiple EHs will further improve the flexibility and economy, how to allocate the payoff fairly and convincingly remains challenged. To address the above challenge, this paper provides a market mechanism based on EH’s peer-to-peer (P2P) transaction for the operation of multiple EHs. The cooperative game theory is applied to develop a fair and convincing payoff allocation scheme. This paper further proves that the cooperative game of multiple EH operations is a balanced game, demonstrating EHs’ grand coalition's stability. The payoff allocation problem is formulated as a two-stage problem. In the first stage, payoff allocation is determined to minimize the worst-case excess. In the second stage, the coalition with the highest excess is found and returned to the first-stage problem. To solve the two-stage problem, the solution technique utilizing column constraints generation is provided. Numerical results for two test systems show the effectiveness, computation performance, and scalability of the proposed method. In the test system, each EH has its payoff increased, ranging from 4% to 19%. The proposed solution technique avoids the computational burden growing exponentially and computes 4168 s when the number of possible coalitions is up to 4.29e9.
- Links to published journals:
- https://www.sciencedirect.com/science/article/pii/S0306261921004906