Open AccessReal‐time active power dispatch of virtual power plant based on distributed model predictive control
Author(s) -
Feng Shuai,
Yang Dongsheng,
Zhou Bowen,
Luo Yanhong,
Li Guangdi
Publication year - 2022
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/ell2.12640
Subject(s) - virtual power plant , scheduling (production processes) , computer science , distributed generation , renewable energy , distributed computing , power station , distributed power , grid , economic dispatch , virtual machine , model predictive control , electric power system , real time computing , power (physics) , engineering , control (management) , artificial intelligence , physics , quantum mechanics , electrical engineering , operations management , geometry , mathematics , operating system
With the increasing penetration of renewable energy, virtual power plants (VPP) reduce the impact on the power grid by integrating massive distributed resources for unified management. However, the optimal scheduling of a large number of distributed resources in VPP has become a new problem in recent years. Therefore, aiming at the real‐time optimal scheduling problem in the optimal scheduling of virtual power plant, this letter regards the virtual power plant as a multi‐agent system and proposes a novel real‐time active power dispatch scheme of virtual power plant based on distributed model predictive control (DMPC), so that each agent can not only calculate its own optimization function relatively independently, but also fully refer to the neighbour information. Simulation results show the feasibility and effectiveness of the proposed method.