Grasshopper optimization algorithm tuned maximum power point tracking for solar photovoltaic systems
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ORIGINAL RESEARCH
Grasshopper optimization algorithm tuned maximum power point tracking for solar photovoltaic systems Annapoorani Subramanian1 · Jayaparvathy Raman2 Received: 3 June 2020 / Accepted: 3 October 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Solar Photovoltaic (PV) system is an excellent renewable energy solution in today’s scenario. Harvesting maximum power from the solar PV system under dynamic meteorological conditions is a challenging task. Numerous bio-inspired Maximum Power Point Tracking (MPPT) strategies have been proposed in the literature. The conventional methods of MPPT control are easy and simple to implement, but has drawbacks such as steady state oscillations and inability to track the maximum power under swiftly varying irradiances and partial shading conditions. This paper proposes a Grasshopper Optimization Algorithm (GOA) tuned MPPT technique with the objective of obtaining optimal duty cycle, D, to control a DC–DC boost converter. The efficacy of the proposed system under start up transients, line disturbances, load disturbances, servo conditions and partial shading conditions are evaluated and compared with the conventional Perturb and Observe (P&O) based MPPT and the familiar Particle Swarm Optimization (PSO) based MPPT algorithm using MATLAB Simulink platform. It is observed that the proposed GOA tuned MPPT technique gives good steady state and dynamic response compared to P&O and PSO based MPPT algorithms, verified in terms of rise time, settling time, percentage maximum overshoot, Integral Squared Error and Integral Absolute Error. Keywords Photovoltaic systems · Maximum power point tracking · Perturb and observe · Particle swarm optimization · Grasshopper optimization algorithm
1 Introduction Nowadays, solar PV systems are extensively used for remote standalone and grid-connected renewable energy systems. Solar energy is inexhaustible, available abundant in nature, and moreover, it is clean and green energy, free from greenhouse gases, thereby reduces the impact on the environment. The estimated value of installed capacity cumulative value is to be more than what is expected by the year 2020 (Anurag et al. 2018). But the drawback of solar PV power generation is the dependence on climatic conditions. The PV module output power is a function of junction temperature and intensity of sunlight which vary with respect to time. * Annapoorani Subramanian [email protected] 1
Department of Electrical and Electronics Engineering, Agni College of Technology, Thalambur, Chennai 600130, India
Department of Electronics and Communication Engineering, SSN College of Engineering, Kalavakkam, Chennai 603110, India
2
The variation in solar insolation is more on a cloudy day. Therefore, it necessitates the use of special algorithms for extraction of maximum power from photovoltaic module under any environmental condition, which is termed as Maximum Power Point Tracking (MPPT). The MPPT algorithms are incorporated in power conditioners, which convert
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