Peer-to-Peer Transactive Computation–Electricity Trading for Interconnected Virtual Power Plant Buildings

Author:

Gao Zhiping1,Kang Wenwen1,Chen Xinghua1,Ding Sheng1,Xu Wei1,He Degang2,Chen Wenhu3,Xu Da3

Affiliation:

1. Hubei Branch of State Power Investment Group Co., Ltd., Wuhan 430062, China

2. Institute of New Energy, Wuhan 430206, China

3. School of Automation, China University of Geosciences, Wuhan 430074, China

Abstract

Advancements of the virtual power plant (VPP) concept have aggregated buildings as their power plants and/or service providers. This paper proposes a peer-to-peer transactive computation–electricity trading framework for multiple-building virtual power plants (BVPPs). In this framework, the interconnected BVPPs can proactively trade their available computation–electricity with each other. Multiple BVPP trading is an intractable optimization problem due to its strong computation–electricity decision-making couplings. Thus, the original problem is described as a game theoretic problem and resolved into the sequential subproblems of social computation–electricity allocation and payoff allocation. By considering the local decision-making of heterogeneous BVPPs, a fully distributed algorithm is further designed to optimize the trading problem by sharing only limited trading information. Finally, a three-BVPP system is used to verify the merits of system resource utilization and operational economy.

Funder

China Postdoctoral Science Foundation

Publisher

MDPI AG

Subject

Building and Construction,Civil and Structural Engineering,Architecture

Reference28 articles.

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