TY - GEN
T1 - Optimal energy management in community micro-grids
AU - Zhu, Jianmin
AU - Jafari, Mohsen
AU - Lu, Yan
PY - 2012
Y1 - 2012
N2 - In this article we present a simulation environment for energy management within community micro-grids. The ultimate objective is to optimally regulate the supply and demand within the micro-grid while ensuring that individual preferences are met and the overall energy consumption is minimized. This article will only focus on the demand management within the community. A simulation environment is developed using GridLAB-D for a baseline and an improved community model. The residential end uses, including electric vehicle charging, are modeled as stochastic and controllable demands. Energy storage capacity is also included. The improved model is used to evaluate different operational alternatives on the basis of individual residential units. Experimental operating conditions are established for the optimization of energy consumption. We show that with properly designed control strategy we are able to reduce the peak load by 8% and hedge against increased EV usage within the community.
AB - In this article we present a simulation environment for energy management within community micro-grids. The ultimate objective is to optimally regulate the supply and demand within the micro-grid while ensuring that individual preferences are met and the overall energy consumption is minimized. This article will only focus on the demand management within the community. A simulation environment is developed using GridLAB-D for a baseline and an improved community model. The residential end uses, including electric vehicle charging, are modeled as stochastic and controllable demands. Energy storage capacity is also included. The improved model is used to evaluate different operational alternatives on the basis of individual residential units. Experimental operating conditions are established for the optimization of energy consumption. We show that with properly designed control strategy we are able to reduce the peak load by 8% and hedge against increased EV usage within the community.
KW - Community micro-grid
KW - Power demand
KW - Power system simulation
UR - https://www.scopus.com/pages/publications/84868516513
UR - https://www.scopus.com/pages/publications/84868516513#tab=citedBy
U2 - 10.1109/ISGT-Asia.2012.6303202
DO - 10.1109/ISGT-Asia.2012.6303202
M3 - Conference contribution
AN - SCOPUS:84868516513
SN - 9781467312219
T3 - 2012 IEEE Innovative Smart Grid Technologies - Asia, ISGT Asia 2012
BT - 2012 IEEE Innovative Smart Grid Technologies - Asia, ISGT Asia 2012
T2 - 2012 IEEE Innovative Smart Grid Technologies - Asia, ISGT Asia
Y2 - 21 May 2012 through 24 May 2012
ER -