TY - JOUR
T1 - Moth-Flame-Optimization Based Parameter Estimation for FCS-MPC Controlled Grid-Connected Converter With LCL-Filter
AU - Long, Bo
AU - Di Yang, Wan
AU - Hu, Qing Hua
AU - Guerrero, Josep M.
AU - Garcia, Cristian
AU - Rodriguez, Jose
AU - Chong, Kil to
N1 - Publisher Copyright:
IEEE
PY - 2022/8/1
Y1 - 2022/8/1
N2 - The ability to model a system with high accuracy plays an important role in finite-control-set model-predictive-control (FCS-MPC)-controlled LCL-interfaced grid-connected converters (LCL-GCCs). However, the effect of aging, unmeasured noise, and temperature change on LCL-GCCs may result in parameter perturbations between the prediction model and the actual system. A model mismatch may occur, which may lead to violations of constraints, worsen the power quality of the grid current, and even threaten the system stability. This article presents a novel nature-inspired optimization paradigm named moth-flame-optimization (MFO), which applies the spiral logarithmic function to simulate the flight of a moth approaching a flame. The method is designed to efficiently identify and update the model parameters, and the fitness function for the state variables is designed and solved iteratively to minimize mismatches with the model. The advantages of the proposed method are its fast convergence and ability to determine parameters with high accuracy. These advantages effectively prevent the algorithm from converging to local optima. To achieve the harmonic rejection capability, a sliding discrete Fourier transform (SDFT) algorithm is also proposed to predict the harmonic at each sampling interval; thus, the harmonics are considered in the cost function. Experimental comparisons under different scenarios validate the effectiveness of the proposed SDFT-based MFO-MPC method.
AB - The ability to model a system with high accuracy plays an important role in finite-control-set model-predictive-control (FCS-MPC)-controlled LCL-interfaced grid-connected converters (LCL-GCCs). However, the effect of aging, unmeasured noise, and temperature change on LCL-GCCs may result in parameter perturbations between the prediction model and the actual system. A model mismatch may occur, which may lead to violations of constraints, worsen the power quality of the grid current, and even threaten the system stability. This article presents a novel nature-inspired optimization paradigm named moth-flame-optimization (MFO), which applies the spiral logarithmic function to simulate the flight of a moth approaching a flame. The method is designed to efficiently identify and update the model parameters, and the fitness function for the state variables is designed and solved iteratively to minimize mismatches with the model. The advantages of the proposed method are its fast convergence and ability to determine parameters with high accuracy. These advantages effectively prevent the algorithm from converging to local optima. To achieve the harmonic rejection capability, a sliding discrete Fourier transform (SDFT) algorithm is also proposed to predict the harmonic at each sampling interval; thus, the harmonics are considered in the cost function. Experimental comparisons under different scenarios validate the effectiveness of the proposed SDFT-based MFO-MPC method.
KW - Cost function
KW - Grid-connected converter
KW - Harmonic analysis
KW - Mathematical models
KW - modelpredictive-control
KW - moth-flame optimization (MFO)
KW - Parameter estimation
KW - parameter mismatch
KW - Power electronics
KW - Power harmonic filters
KW - power quality
KW - Predictive models
KW - model-predictive-control
UR - http://www.scopus.com/inward/record.url?scp=85122571360&partnerID=8YFLogxK
U2 - 10.1109/JESTPE.2022.3140228
DO - 10.1109/JESTPE.2022.3140228
M3 - Journal article
AN - SCOPUS:85122571360
SN - 2168-6777
VL - 10
SP - 4102
EP - 4114
JO - IEEE Journal of Emerging and Selected Topics in Power Electronics
JF - IEEE Journal of Emerging and Selected Topics in Power Electronics
IS - 4
ER -