TY - JOUR
T1 - A Novel Cooperative Control for SMES/Battery Hybrid Energy Storage in PV Grid-Connected System
AU - Wang, Pengfei
AU - Lu, Jing
AU - Wu, Yanan
AU - Xu, Liuwei
AU - Li, Jun
AU - Mao, Huafeng
AU - Tian, Yunxiang
AU - Xu, Bin
AU - Huang, Jianfeng
N1 - Publisher Copyright:
© 2002-2011 IEEE.
PY - 2024/11
Y1 - 2024/11
N2 - With the ever-growing integration of renewable energy sources (RESs) into the power grid to meet escalating power demand, the intermittent and volatile nature of these sources poses significant challenges to the stability of power grid. To address the unstable output power resulting from the inherent randomness and fluctuation of RES, this paper introduces a novel cooperative control strategy designed for a photovoltaic-based grid-connected system. This proposed strategy leverages both battery energy storage system (BESS) and superconducting magnetic energy storage (SMES) within the hybrid energy storage system (HESS) framework. At top-level control (TLC), the control strategy employs a fuzzy control-based low-pass filter (LPF) to dynamically regulate filtration coefficient and realize transient power allocation optimization. Simultaneously, at the underlayer level control (ULC), a fast Model Predictive Control (MPC) method is implemented to maintain DC bus voltage by one-step prediction horizon. The feasibility and superiority of the proposed control strategy are systematically validated under diverse operating conditions, demonstrating its efficacy in enhancing the stability and performance of the grid-connected system.
AB - With the ever-growing integration of renewable energy sources (RESs) into the power grid to meet escalating power demand, the intermittent and volatile nature of these sources poses significant challenges to the stability of power grid. To address the unstable output power resulting from the inherent randomness and fluctuation of RES, this paper introduces a novel cooperative control strategy designed for a photovoltaic-based grid-connected system. This proposed strategy leverages both battery energy storage system (BESS) and superconducting magnetic energy storage (SMES) within the hybrid energy storage system (HESS) framework. At top-level control (TLC), the control strategy employs a fuzzy control-based low-pass filter (LPF) to dynamically regulate filtration coefficient and realize transient power allocation optimization. Simultaneously, at the underlayer level control (ULC), a fast Model Predictive Control (MPC) method is implemented to maintain DC bus voltage by one-step prediction horizon. The feasibility and superiority of the proposed control strategy are systematically validated under diverse operating conditions, demonstrating its efficacy in enhancing the stability and performance of the grid-connected system.
KW - n/a OA procedure
KW - Hybrid energy storage system (HESS)
KW - Model predictive control (MPC)
KW - Superconducting magnet energy storage (SMES)
KW - Fuzzy low pass filter (FLPF)
UR - https://www.scopus.com/pages/publications/85197043720
U2 - 10.1109/TASC.2024.3420310
DO - 10.1109/TASC.2024.3420310
M3 - Article
AN - SCOPUS:85197043720
SN - 1051-8223
VL - 34
JO - IEEE transactions on applied superconductivity
JF - IEEE transactions on applied superconductivity
IS - 8
M1 - 5401605
ER -