Parameter identification of solar cell model using Levenberg–Marquardt algorithm combined with simulated annealing

Modeling of photovoltaic system for uniform and non-uniform irradiance: A critical review

“…A LMA in combination with SA is presented in [36]. An objective function is formulated and LM curve fitting is used to find the five equivalent circuit parameters.…”

Metaheuristic Algorithm for Photovoltaic Parameters: Comparative Study and Prediction with a Firefly Algorithm

“…To verify the performance of the proposed approach and the quality of the obtained results, statistical analyses are carried out to measure the accuracy of the calculated parameters and model suitability. The results obtained are compared with recent techniques such as the Biogeography-Based Optimization algorithm with Mutation strategies (BBO-M) [68], Levenberg-Marquardt algorithm combined with Simulated Annealing (LMSA) [47], Artificial Bee Swarm Optimization algorithm [48], Artificial Bee Colony optimization (ABC) [49], hybrid Nelder-Mead and Modified Particle Swarm Optimization (NM-MPSO) [50], Repaired Adaptive Differential Evolution (RADE) [59], Chaotic Asexual Reproduction Optimization (CARO) [69] for solar cell single and double diodes. For organic flexible hydrogenated amorphous silicon, a-Si:H solar cell will be compared with the Quasi-Newton (Q-N) method and Self-Organizing Migrating Algorithm (SOMA) [54].…”

“…The solar cell can be modelled by using the single diode model, double diode or multi-diode models. The objective function is defined from Equations (1) and (3), several research papers use different functions, for example, [48][49][50]59,68,69] use the root mean square error (RMSE), [47] use the sum of squared error (SSE). In [55,58] the individual absolute error (IAE) is used and [79] use the mean absolute errors (MAE).…”

“…The proposed algorithm is applied first to extract the electrical intrinsic parameters values for single and double diode models of a 57-mm-diameter commercial (RTC France) silicon solar cell under 1000 W/m 2 at 33 • C. The extracted parameters are compared with those found by: Biogeography-Based Optimization algorithm with Mutation strategies (BBO-M) [68], Levenberg-Marquardt algorithm combined with Simulated Annealing (LMSA) [47], Artificial Bee Swarm Optimization algorithm [48], Artificial Bee Colony optimization (ABC) [49], hybrid Nelder-Mead and Modified Particle Swarm Optimization (NM-MPSO) [50], Repaired Adaptive Differential Evolution (RADE) [59], Chaotic Asexual Reproduction Optimization (CARO) [69], and the results for each model are reported in Tables 3 and 4. To confirm the accuracy of the extracted optimal values found by the Firefly algorithm, the calculated currents for the single and double diode model by optimized parameters are summarized in Tables 5 and 6 compared with individual absolute error (IAE).…”

Improved Disturbance Observer of Maximum Power Point Tracking in PV Cells

“…Solar energy resources are renewable energy, clean and pollution-free, the use of solar energy has been the focus of researchers [1][2][3], the intensity of photoelectric conversion efficiency is of great influence affecting the development of PV power generation, in order to make the PV panels strong illumination, scholars have taken a large number of studies on it, such as the biaxial solar automatic tracking system can be achieved on different sun angle tracking, which improved PV panels light efficiency [4,5], however, when it is fixed in the light intensity, the maximum photoelectric conversion efficiency is the most important parameter, in order to achieve a high conversion efficiency, the MPPT of PV is commonly used research method, now commonly methods are disturbance observation and incremental conductance [6,7].…”