A Comprehensive Review and Application of Metaheuristics in Solving the Optimal Parameter Identification Problems

Abstract

For many electrical systems, such as renewable energy sources, their internal parameters are exposed to degradation due to the operating conditions. Since the model’s accuracy is required for establishing proper control and management plans, identifying their parameters is a critical and prominent task. Various techniques have been developed to identify these parameters. However, metaheuristic algorithms have received much attention for their use in tackling a wide range of optimization issues relating to parameter extraction. This work provides an exhaustive literature review on solving parameter extraction utilizing recently developed metaheuristic algorithms. This paper includes newly published articles in each studied context and its discussion. It aims to approve the applicability of these algorithms and make understanding their deployment easier. However, there are not any exact optimization algorithms that can offer a satisfactory performance to all optimization issues, especially for problems that have large search space dimensions. As a result, metaheuristic algorithms capable of searching very large spaces of possible solutions have been thoroughly investigated in the literature review. Furthermore, depending on their behavior, metaheuristic algorithms have been divided into four types. These types and their details are included in this paper. Then, the basics of the identification process are presented and discussed. Fuel cells, electrochemical batteries, and photovoltaic panel parameters identification are investigated and analyzed.

An efficient, fast, and robust algorithm for single diode model parameters estimation of photovoltaic solar cells

“…The unknown parameters for the mathematical model equation for SDM should be estimated. A solution vector X for the SDM is formulated as shown in (7).…”

“…It resistance, and n 1 denotes the diode ideality factor. The double diode model (DDM), three diode model (TDM), and other modified models can provide more accurate models; however, they are limited in practice due to their considerable complexities [6,7]. Consequently, in this paper, SDM has been focused and considered.…”

“…Here, $${I}_{PV}$$ denotes the generated photocurrent, $${I}_{S1}$$ denotes the diode reverse saturation current, $${R}_S$$ denotes series resistance, $${R}_P$$ denotes parallel resistance, and $${n}_1$$ denotes the diode ideality factor. The double diode model (DDM), three diode model (TDM), and other modified models can provide more accurate models; however, they are limited in practice due to their considerable complexities [6, 7]. Consequently, in this paper, SDM has been focused and considered.…”

“…However, these methods are limited in practice because of the poor accuracy provided by simplifying the assumptions. In addition, the systems are usually described by transcendental equations that require arbitrary initial values to solve the equations, which affect their accuracy [7, 8]. Metaheuristic optimization algorithms have been used instead of analytical methods to overcome complex and non‐linear problems.…”

Internet of Robotic Things (IoRT) and Metaheuristic Optimization Techniques Applied for Wheel-Legged Robot

“…This leads to subsequent improvements and modifications of existing methods. The efficiency of different approaches can be synthetically tested with benchmark functions or directly with engineering problems- [21] provides a review of the chosen algorithms, and ref. [22] provides the efficiency results and shows the popularity and development of metaheuristic algorithms (more than 500 optimizers are listed).…”