TY - GEN
T1 - Model Predictive Control Based Improved Techno-Economic Control Strategy for Photovoltaic-Battery Microgrids
AU - Selim, Fatma
AU - Megahed, Tamer F.
AU - Aly, Mokhtar
AU - Shoyama, Masahito
AU - Abdelkader, Sobhy M.
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This paper presents an improved model predictive control (MPC) based control method for photovoltaic (PV)-Battery microgrid (MG) system. The proposed control method represents a techno-economical control strategy for controlling PV-battery microgrid systems based on the MG status and feed-in-tariff (FiT). During normal operating mode, the reference d-q currents are calculated based on the economic operation of the MG system to reduce the operational costs of the MG system. Whereas during faulty conditions of large voltage sag, high voltage swell, and grid unbalance, the references are generated to rapidly recover the MG system and clear the existing faults to enhance the low voltage ride through (LVRT) and high voltage ride through (HVRT) capability. Moreover, the utilization of MPC facilitates the digital control actions, fast response of the system, and elimination of the cascaded conventional loops through using multiple objective cost functions. Simulation results are provided in the paper for the PV-battery MG system and the proposed controller, which showed the techno-economic feasibility of the new proposed MPC-based control method.
AB - This paper presents an improved model predictive control (MPC) based control method for photovoltaic (PV)-Battery microgrid (MG) system. The proposed control method represents a techno-economical control strategy for controlling PV-battery microgrid systems based on the MG status and feed-in-tariff (FiT). During normal operating mode, the reference d-q currents are calculated based on the economic operation of the MG system to reduce the operational costs of the MG system. Whereas during faulty conditions of large voltage sag, high voltage swell, and grid unbalance, the references are generated to rapidly recover the MG system and clear the existing faults to enhance the low voltage ride through (LVRT) and high voltage ride through (HVRT) capability. Moreover, the utilization of MPC facilitates the digital control actions, fast response of the system, and elimination of the cascaded conventional loops through using multiple objective cost functions. Simulation results are provided in the paper for the PV-battery MG system and the proposed controller, which showed the techno-economic feasibility of the new proposed MPC-based control method.
UR - http://www.scopus.com/inward/record.url?scp=85142009346&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85142009346&partnerID=8YFLogxK
U2 - 10.1109/ICRERA55966.2022.9922814
DO - 10.1109/ICRERA55966.2022.9922814
M3 - Conference contribution
AN - SCOPUS:85142009346
T3 - 11th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2022
SP - 230
EP - 235
BT - 11th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2022
Y2 - 18 September 2022 through 21 September 2022
ER -
