A Modified Triple-Diode Model Parameters Identification for Perovskite Solar Cells via Nature-Inspired Search Optimization Algorithms

Abstract

Recently, perovskite solar cells (PSCs) have been widely investigated as an efficient alternative for silicon solar cells. In this work, a proposed modified triple-diode model (MTDM) for PSCs modeling and simulation was used. The Bald Eagle Search (BES) algorithm, which is a novel nature-inspired search optimizer, was suggested for solving the model and estimating the PSCs device parameters because of the complex nature of determining the model parameters. Two PSC architectures, namely control and modified devices, were experimentally fabricated, characterized and tested in the lab. The I–V datasets of the fabricated devices were recorded at standard conditions. The decision variables in the proposed optimization process are the nine and ten unknown parameters of triple-diode model (TDM) and MTDM, respectively. The direct comparison with a number of modern optimization techniques including grey wolf (GWO), particle swarm (PSO) and moth flame (MFO) optimizers, as well as sine cosine (SCA) and slap swarm (SSA) algorithms, confirmed the superiority of the proposed BES approach, where the Root Mean Square Error (RMSE) objective function between the experimental data and estimated characteristics achieves the least value.

Modeling and Simulation of Simplified Quadruple Diode Solar PV Module Under Influence of Environmental Conditions and Parasitic Resistance

“…The TDM is presented in Equation 3. It incorporates three diodes within the model [27], [28]. Nine parameters are required by the triple model to fully characterize its I-V characteristic, which are: I rs2 , I rs3 , I ph , I rs1 , n 1 , n 2 , n 3 , G pa and R se .…”

Fuzzy-Energy-Management-Based Intelligent Direct Torque Control for a Battery—Supercapacitor Electric Vehicle

“…The basic steps of the GA algorithm are highlighted in Figure 2, and the GA parameters used are shown in Table 2. It is worth noting that the convergence of the GA algorithm used was tested using the benchmark test function [32][33][34][35] shown in Figure 3, whose expression is given by Equation ( 15). This benchmark function is full of local minima and has a unique global optimum, which may trap the algorithm if it is not well conceived.…”

Suivi Du Point De Puissance Maximum Dans Un Système De Pompage Solaire Perovskite Avec Un Moteur À Induction Six Phase

“…The main drawbacks of this type of solar cell are the hysteresis phenomenon and the stability problem of perovskite [11]. Interface engineering approaches are suitable solutions for overcoming hysteresis and stability problems and increasing power conversion efficiency [12].…”