energies Article System Parameter Based Performance Optimization of Solar PV Systems with Perturbation Based MPPT Algorithms Sachin Angadi 1,* , Udaykumar R. Yaragatti 2 , Yellasiri Suresh 2 and A. B. Raju 1   Citation: Angadi, S.; Yaragatti, U.R.; Suresh, Y.; Raju, A.B. System Parameter Based Performance Optimization of Solar PV Systems with Perturbation Based MPPT Algorithms. Energies 2021, 14, 2007. https://doi.org/10.3390/en14072007 Academic Editor: Eun-Chel Cho Received: 5 January 2021 Accepted: 24 February 2021 Published: 5 April 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1 Department of Electrical and Electronics Engineering, K.L.E Technological University, Hubli 580031, India; abraju@kletech.ac.in 2 Department of Electrical and Electronics Engineering, National Institute of Technology—Karnataka, Surathkal 575025, India ; udaykumarry@yahoo.com (U.R.Y.); ysuresh.ee@gmail.com (Y.S.) * Correspondence: sachin@kletech.ac.in Abstract: Maximum power point tracking (MPPT) algorithms are invariably employed to utilize solar photovoltaic (PV) systems effectively. Perturbation based MPPT algorithms are popular due to their simplicity and reasonable efficiency. While novel MPPT algorithms claim increased energy utilization over classic perturbation techniques, their performance is governed by the choice of optimal algorithm parameters. Existing guidelines for parameter optimization are mathematically laborious and are not generic. Hence, this paper aims to provide simple and comprehensive guidelines to ensure optimal performance from the perturbation based MPPT technique. For an illustration of proposed claims, a solar PV fed boost converter is investigated to examine the effect of input capacitor, digital filter cut-off frequency, system time constant and sampling time on implementing a classic Perturb and Observe (P and O) algorithm. The readers will be presented with two simple step tests (to determine the effective system time constant) and proposed guidelines to choose the optimal performance sampling time. Necessary laboratory experiments show that an appropriate choice of sampling time could increase efficiency and ensure system stability. This investigation’s learnings can be easily extended to any power electronics converter, loads and all perturbation-based algorithms used in solar PV systems. The results of appropriate tests on the system’s mathematical model and the laboratory prototype are presented in detail to support this research’s claims. Keywords: boost converter; maximum power point tracking (MPPT); perturb and observe algorithm; renewable energy; solar photovoltaic system 1. Introduction To meet growing energy needs, it is inevitable that renewable technology will be adopted for energy decarbonization. Solar photovoltaic (PV) power is foreseen to mature as the world’s largest electricity source by 2050 with the current potential in the range of 1575–49,837 exajoules [1]. The available solar energy can be harnessed in standalone or grid-connected mode. Irrespective of the application of solar PV systems, the maximum power point tracking (MPPT) algorithm is mandatory to ensure optimal power extraction from the solar PV system due to non-linear P-V (power-voltage) characteristics. The Solar PV system’s P-V curve exhibits a non-linear characteristic with only one peak power operating point. The system operates at this Maximum Power Point (MPP) when source impedance matches load impedance [2]. Perturbation techniques are popular for achieving MPP due to factors like minimal sensors and ease of implementation [3]. System variables like duty ratio (D), PV voltage (V pv ) and PV current ( I pv ) are continu- ously perturbed to force the system to operate at MPP against disturbances like changing irradiances and loads [4]. Research in perturbation-based MPPT has evolved in two folds, namely novel algorithms and optimization of system parameters. Novel algorithms include classic algorithms like Perturb and Observe (P and O) method and Incremental Conductance (InC) method. Also, research is fast emerging Energies 2021, 14, 2007. https://doi.org/10.3390/en14072007 https://www.mdpi.com/journal/energies