Solar System Array by Fuzzy Logic based on MPPT Algorithm
Mukesh Kumar1, Mohd Asif Ali2, Sanawer Alam3
1Mukesh Kumar*, Dept of Electrical Engg., Azad Institute of engineering & Technology, Lucknow.
2Mohd Asif Ali, Dept of Electrical Engg., Azad Institute of engineering & Technology, Lucknow
3Sanawer Alam, Dept of Electrical Engg., Azad Institute of engineering & Technology, Lucknow
Manuscript received on March 15, 2020. | Revised Manuscript received on March 25, 2020. | Manuscript published on April 10, 2020. | PP: 1132-1139 | Volume-9 Issue-6, April 2020. | Retrieval Number: F3419049620/2020©BEIESP | DOI: 10.35940/ijitee.F3419.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In recent times a huge attention has been given on development of proper planning In this paper we present a top dimension perspective on forefront status of Closed circle ID system the use of PID Controller from explicit creators. The proportional– integral– subsidiary (PID) controller is the most extreme comprehensively ordinary controller inside the business bundles, specifically in strategy enterprises in light of fabulous expense to profit proportion. In this paper we focus on MPPT based solar system performance enhancement by use of fuzzy logic controller’s designs optimized by particle swarm optimization (PSO). We have described about different latest A.I. techniques that has been hybrid with fuzzy logic for improving PV array based solar plants performance in recent time. The artificial intelligence technique applied in this work is the Particle Swarm Optimization (PSO) algorithm and is used to optimize the membership functions for maximum power point tracking rule set of the FLC. By using PSO algorithm, the optimized FLC is able to maximize energy to the system loads while also maintaining a higher stability and speed as compared to P& O based MPPT algorithm.
Keywords: ANN, GHG, Photo Voltaic, Fuzzy
Scope of the Article: Fuzzy logics