TY - GEN
T1 - Optimal scheduling of home energy management system with plug-in electric vehicles using model predictive control
AU - Zhao, Yue
AU - Chen, Yan
AU - Keel, Brian
N1 - Funding Information:
This research was supported by Conservation and Renewable Energy Collaboratory (CREC): Salt River Project (SRP).
Publisher Copyright:
Copyright © 2018 ASME
PY - 2018
Y1 - 2018
N2 - For a household microgrid with renewable photovoltaic (PV) panel and plug-in electric vehicles (PEVs), a home energy management system (HEMS) using model predictive control (MPC) is designed to achieve optimal PEV charging and energy flow scheduling. Soft electric loads and an energy storage system (ESS) are also considered in the optimization of PEV charging in the MPC framework. The MPC is solved through a mixed-integer linear programming (MILP) by considering the relationship of energy flows in the optimization problem. Through the simulation results, the performance of optimization results under various electricity price plans is evaluated. The influences of PV capacities on the optimization results of electricity cost are also discussed.
AB - For a household microgrid with renewable photovoltaic (PV) panel and plug-in electric vehicles (PEVs), a home energy management system (HEMS) using model predictive control (MPC) is designed to achieve optimal PEV charging and energy flow scheduling. Soft electric loads and an energy storage system (ESS) are also considered in the optimization of PEV charging in the MPC framework. The MPC is solved through a mixed-integer linear programming (MILP) by considering the relationship of energy flows in the optimization problem. Through the simulation results, the performance of optimization results under various electricity price plans is evaluated. The influences of PV capacities on the optimization results of electricity cost are also discussed.
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U2 - 10.1115/DSCC2018-9159
DO - 10.1115/DSCC2018-9159
M3 - Conference contribution
AN - SCOPUS:85057330865
T3 - ASME 2018 Dynamic Systems and Control Conference, DSCC 2018
BT - Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Energy Systems; Estimation and Identification; Intelligent Transportation and Vehicles; Manufacturing; Mechatronics; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Control of IC Engines and Powertrain Systems; Modeling and Management of Power Systems
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2018 Dynamic Systems and Control Conference, DSCC 2018
Y2 - 30 September 2018 through 3 October 2018
ER -