Open AccessA Distributed Optimal Scheduling Method Based on Microgrid Cluster of Plug and Play
Author(s) -
Wenjun Tang,
Q Liu,
Peter He,
G F Liu
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/701/1/012058
Subject(s) - microgrid , mathematical optimization , computer science , solver , scheduling (production processes) , optimization problem , matlab , global optimization , distributed computing , control (management) , mathematics , artificial intelligence , operating system
This paper proposes a distributed optimization method to solve the problems of centralized optimization and centralized management of a microgrid. Also, the distributed optimization solution method upgrade to a process of distributed iterative solution and optimization, which can solve the distributed optimization problem of a large microgrid cluster. According to iterative calculation, accord the augmented Lagrange function supports the centralized optimization problem divided into corresponding subproblems, and the penalty factors of interconnected variables considered to adjust the consumption of local resources, to make microgrid cluster (MGC) more flexible. In particular, the framework of multi-verse consistency and model predictive control (MPC) can help the global optimization reach the optimal quickly. In this paper, the simulation is solved by Gurobi commercial solver in MATLAB. The results show that the proposed method needs only a few iterations to achieve global optimization, and the effectiveness of plug and play proved.