Renewable and Sustainable Energy Reviews 146 (2021) 111135 1364-0321/© 2021 Published by Elsevier Ltd. A novel musical chairs algorithm applied for MPPT of PV systems Ali M. Eltamaly a, b, c, * a Sustainable Energy Technologies Center, King Saud University, Riyadh, 11421, Saudi Arabia b Electrical Engineering Department, Mansoura University, Mansoura, Egypt c Saudi Electricity Company Chair in Power System Reliability and Security, King Saud University, Saudi Arabia A R T I C L E INFO Keywords: Musical chairs algorithm Optimization Photovoltaic Maximum power point tracker Partial shading ABSTRACT Due to the multiple peaks generated in the power to voltage characteristics of partially shaded photovoltaic (PV) arrays there is an urgent need for an effective optimization algorithm to capture its global peak instead of the local peaks. The required optimization algorithm should converge very fast and accurately capture the global peak. Many metaheuristic optimization algorithms have been introduced to tackle this problem and balance exploration and exploitation performances. These algorithms use a constant number of searching agents (swarm size) through all iterations. The maximum power point tracker (MPPT) of the PV system requires high numbers of searching agents in the initial steps of optimization to enhance explorations, whereas the fnal stage of opti- mization requires lower numbers of searching agents to enhance exploitations, which are conditions that are currently unavailable in optimization algorithms. This was the research gap that was the main motive of creating the new algorithm introduced in this paper, where a high number of searching agents is used at the beginning of the optimization steps to enhance exploration and reduce the convergence failure. The number of searching agents should be reduced gradually to have a lower number of search agents at the end of searching steps to enhance exploitation. This need is inspired by the well-known musical chairs game in which the players and chairs start with high numbers and are reduced one by one in each round which enhances the exploration at the start of the search and exploitation at the end of the search steps. For this reason, a novel optimization algorithm called the musical chairs algorithm (MCA) is introduced in this paper. Using the MCA for MPPT of PV systems considerably provided lower convergence times and failure rates than other optimization algorithms. The convergence time and failure rate are the crucial factors in assessing the MPPT because they should be minimized as much as possible to improve the PV system effciency and assure its stability especially in the high dynamic change of shading conditions. The convergence time was reduced to 20%–50% of those obtained using fve benchmark optimization algorithms. Moreover, the oscillations at steady state is reduced to 20%–30% of the values associated the benchmark optimization algorithms. These results prove the superiority of the newly proposed MCA in the MPPTs of the PV system. 1. Introduction The photovoltaic (PV) energy system is gaining substantial interest worldwide, and it will gain more interest shortly, as its cost is dropping very fast, which makes it a competitor to most of the conventional power plants. The power generated by a PV array is a function of its terminal voltage with nonlinear characteristics, which need an effective maximum power point tracker (MPPT) to follow the maximum power point (MPP) during different operating conditions. The MPPT is working online and for this reason it should be very fast to capture the global peak (GP) to avoid instability of the PV systems especially in fast changing shading conditions. The MPPT needs a DC-DC converter to control the PV array terminal voltage which can be controlled to work at the MPP, as shown in Fig. 1. In this fgure the PV array is connected with a boost converter and the output terminals of the boost converter is connected to single phase inverter via DC-link capacitor to be suitably connected to the utility grid. The power-voltage relation is called the P–V characteristics. In the case of uniform irradiance (UI), the P–V characteristics have only one peak, which can easily be captured even by traditional techniques like hill-climbing (HC) [1], or incremental conductance (InCond) [2]. Meanwhile, under partial shading conditions (PSC), the P–V characteristics have multiple peaks, where the peak with * Saudi Electricity Company Chair in Power System Reliability and Security, King Saud University, Saudi Arabia. E-mail address: eltamaly@ksu.edu.sa. Contents lists available at ScienceDirect Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser https://doi.org/10.1016/j.rser.2021.111135 Received 29 December 2020; Received in revised form 24 March 2021; Accepted 18 April 2021