Integrating Peer-to-Peer Energy Trading of Microgrids into Deregulated Electricity Market by Cascaded Model Predictive Control

Lyu，Cheng1; Jia，Youwei2; Shi，Mengge2; Xu，Zhao1,3

10.1109/EI252483.2021.9713576

2021

978-1-6654-3426-3

5th IEEE Conference on Energy Internet and Energy System Integration: Energy Internet for Carbon Neutrality, EI2 2021

114-118

22-24 Oct. 2021

Taiyuan, China

Peer-to-peer (P2P) energy trading of microgrids is considered as a promising solution in reducing the carbon emission of renewable-embedded energy systems. This paper proposes a novel energy market framework for enabling the P2P local transactions under the deregulated market environment. The proposed market model is aimed to provide a practical mechanism design to incentivize optimal P2P energy trading in the existing electricity market. A cascaded model predictive control (MPC) problem formulation is devised for both the day-ahead market and adjustment markets. Finally, numerical results demonstrate the effectiveness of the proposed framework in integrating microgrid P2P trading into the electricity market.

electricity market microgrids model predictive control Peer-to-peer energy trading

其他

英语

EI

Department of Education of Guangdong Province[2018KQNCX223];

20221611979221

Deregulation ; Model predictive control ; Predictive control systems

Control Systems:731.1 ; Social Sciences:971

2-s2.0-85128197113

Scopus

1.Department of Electrical Engineering,The Hong Kong Polytechnic University,Hong Kong
2.Department ofEletrical and Electronic Engineering,Southern University of Science and Technology,Shenzhen,China
3.Shenzhen Research Institute,Research Institute for Smart Energy,Hong Kong

Lyu，Cheng,Jia，Youwei,Shi，Mengge,et al. Integrating Peer-to-Peer Energy Trading of Microgrids into Deregulated Electricity Market by Cascaded Model Predictive Control[C],2021:114-118.