TY - GEN
T1 - Accelerated Distributed Energy Management for Microgrids
AU - Du, Wen
AU - Yao, Lisha
AU - Wu, Di
AU - Li, Xinrong
AU - Liu, Guodong
AU - Yang, Tao
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/21
Y1 - 2018/12/21
N2 - This paper considers the optimal energy management for a microgrid. The goal of optimal energy management is to minimize the total generation cost while meeting total demand and satisfying individual generator output limits. To achieve this goal, we develop a distributed algorithm based on the consensus theory and gradient estimation technique. Compared to the existing algorithms with diminishing step-sizes, the proposed algorithm enjoys a faster convergence speed due to the fixed step-size, and thus increases the computation speed, and reduces the computation and communication burden. The proposed distributed algorithm is applicable to both fixed and time-varying directed communication networks. We show that the convergence of the proposed distributed algorithm is achieved if the fixed communication network is strongly connected, or if the time-varying communication network is uniformly jointly strongly connected. Numerical simulation results are used to illustrate and demonstrate the effectiveness of the proposed algorithm.
AB - This paper considers the optimal energy management for a microgrid. The goal of optimal energy management is to minimize the total generation cost while meeting total demand and satisfying individual generator output limits. To achieve this goal, we develop a distributed algorithm based on the consensus theory and gradient estimation technique. Compared to the existing algorithms with diminishing step-sizes, the proposed algorithm enjoys a faster convergence speed due to the fixed step-size, and thus increases the computation speed, and reduces the computation and communication burden. The proposed distributed algorithm is applicable to both fixed and time-varying directed communication networks. We show that the convergence of the proposed distributed algorithm is achieved if the fixed communication network is strongly connected, or if the time-varying communication network is uniformly jointly strongly connected. Numerical simulation results are used to illustrate and demonstrate the effectiveness of the proposed algorithm.
KW - Distributed energy resources
KW - Distributed opti-mization
KW - Energy management
KW - Microgrid
UR - http://www.scopus.com/inward/record.url?scp=85060796502&partnerID=8YFLogxK
U2 - 10.1109/PESGM.2018.8586094
DO - 10.1109/PESGM.2018.8586094
M3 - Conference contribution
AN - SCOPUS:85060796502
T3 - IEEE Power and Energy Society General Meeting
BT - 2018 IEEE Power and Energy Society General Meeting, PESGM 2018
PB - IEEE Computer Society
T2 - 2018 IEEE Power and Energy Society General Meeting, PESGM 2018
Y2 - 5 August 2018 through 10 August 2018
ER -