TY - GEN
T1 - Optimal energy trading for building microgrid with electric vehicles and renewable energy resources
AU - Nguyen, Duong Tung
AU - Le, Long Bao
PY - 2014
Y1 - 2014
N2 - In this paper, we study an optimal power bidding and scheduling problem for a microgrid (MG), which consists of distributed generators (DGs), battery storage units, a large garage with many charging stations for electric vehicles (EVs), MG local load, and renewable energy sources (RESs).We propose to utilize EVs as a dynamic energy storage facility to accommodate the variability of RESs in a realistic economic model for the electricity market. The power scheduling and bidding problem is formulated as a two-stage stochastic programming problem considering the uncertainties of RESs and electricity price. Specifically, a multi-objective function is introduced to balance the tradeoff between maximizing the MG revenue and minimizing the MG operating cost. Importantly, appropriate penalty metrics capturing involuntary load shedding, renewable energy curtailment, and bid deviation are integrated into the objective function. Numerical results confirm the effectiveness of the proposed optimization framework in enhancing the operation efficiency of the MG, reducing curtailment of renewable energy resources compared to the conventional scheme and flexibility of the proposed framework in balancing different design objectives.
AB - In this paper, we study an optimal power bidding and scheduling problem for a microgrid (MG), which consists of distributed generators (DGs), battery storage units, a large garage with many charging stations for electric vehicles (EVs), MG local load, and renewable energy sources (RESs).We propose to utilize EVs as a dynamic energy storage facility to accommodate the variability of RESs in a realistic economic model for the electricity market. The power scheduling and bidding problem is formulated as a two-stage stochastic programming problem considering the uncertainties of RESs and electricity price. Specifically, a multi-objective function is introduced to balance the tradeoff between maximizing the MG revenue and minimizing the MG operating cost. Importantly, appropriate penalty metrics capturing involuntary load shedding, renewable energy curtailment, and bid deviation are integrated into the objective function. Numerical results confirm the effectiveness of the proposed optimization framework in enhancing the operation efficiency of the MG, reducing curtailment of renewable energy resources compared to the conventional scheme and flexibility of the proposed framework in balancing different design objectives.
KW - battery
KW - electric vehicle
KW - Renewable energy
UR - http://www.scopus.com/inward/record.url?scp=84901922324&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84901922324&partnerID=8YFLogxK
U2 - 10.1109/ISGT.2014.6816461
DO - 10.1109/ISGT.2014.6816461
M3 - Conference contribution
AN - SCOPUS:84901922324
SN - 9781479936526
T3 - 2014 IEEE PES Innovative Smart Grid Technologies Conference, ISGT 2014
BT - 2014 IEEE PES Innovative Smart Grid Technologies Conference, ISGT 2014
PB - IEEE Computer Society
T2 - 2014 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2014
Y2 - 19 February 2014 through 22 February 2014
ER -