TY - JOUR
T1 - An MPC-based power management of standalone DC microgrid with energy storage
AU - Batiyah, Salem
AU - Sharma, Roshan
AU - Abdelwahed, Sherif
AU - Zohrabi, Nasibeh
N1 - Funding Information:
This material is based upon work supported in part by the National Science Foundation (NSF) under Grant No. 1711449 .
Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/9
Y1 - 2020/9
N2 - Standalone dc microgrid faces a significant reliability risk due to continuous variation in power from renewable energy generation and the load demand. Usually, the output power from the renewable generators fluctuates with the weather conditions. The load is also varying all the time. This leads to a continuous risk of power mismatch in the system. Thus, a complementary generation or a storage system is required for maintaining the power balance in the system. This paper introduces a supervisory power management strategy (PMS) for a standalone dc microgrid with multiple distributed generations, load, and a battery energy storage system. The PMS is designed based on the model predictive control (MPC) approach. The complete mathematical model of the system has been developed, and it has been utilized in the MPC controller to solve an optimization problem with operating constraints. A forecasting technique is also incorporated in the proposed MPC to predict the environmental and load demand parameters. Simulation results illustrate the effectiveness of the presented MPC-based power management approach. Accordingly, the proposed approach effectively manages the power among the generators, load, and the battery and stabilizes the dc voltage. The paper also evaluates the effects of various prediction methods on the controller performance.
AB - Standalone dc microgrid faces a significant reliability risk due to continuous variation in power from renewable energy generation and the load demand. Usually, the output power from the renewable generators fluctuates with the weather conditions. The load is also varying all the time. This leads to a continuous risk of power mismatch in the system. Thus, a complementary generation or a storage system is required for maintaining the power balance in the system. This paper introduces a supervisory power management strategy (PMS) for a standalone dc microgrid with multiple distributed generations, load, and a battery energy storage system. The PMS is designed based on the model predictive control (MPC) approach. The complete mathematical model of the system has been developed, and it has been utilized in the MPC controller to solve an optimization problem with operating constraints. A forecasting technique is also incorporated in the proposed MPC to predict the environmental and load demand parameters. Simulation results illustrate the effectiveness of the presented MPC-based power management approach. Accordingly, the proposed approach effectively manages the power among the generators, load, and the battery and stabilizes the dc voltage. The paper also evaluates the effects of various prediction methods on the controller performance.
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U2 - 10.1016/j.ijepes.2020.105949
DO - 10.1016/j.ijepes.2020.105949
M3 - Article
AN - SCOPUS:85081009838
VL - 120
JO - International Journal of Electrical Power and Energy Systems
JF - International Journal of Electrical Power and Energy Systems
SN - 0142-0615
M1 - 105949
ER -