Optimization of photovoltaic energy harvesting using artificial neural network

• Main Authors: Min, Keng Tan, Kit, Guan Lim, Norman Lim, Soo, Siang Yang, Nurul Izyan Kamaruddin, Tze, Kenneth Kin Teo
• Format: Proceedings
• Language: English; English
• Published: Institute of Electrical and Electronics Engineers Inc 2021
• Subjects: QA1-43 General; TD1-1066 Environmental technology. Sanitary engineering
• Online Access: https://eprints.ums.edu.my/id/eprint/32501/1/Optimization%20of%20photovoltaic%20energy%20harvesting%20using%20artificial%20neural%20network.ABSTRACT.pdf; https://eprints.ums.edu.my/id/eprint/32501/2/Optimization%20of%20photovoltaic%20energy%20harvesting%20using%20artificial%20neural%20network.pdf; https://eprints.ums.edu.my/id/eprint/32501/; https://ieeexplore.ieee.org/document/9573886

This paper proposes artificial neural network (ANN) based maximum power point tracking (MPPT) controller to maximize the energy harvested by a grid-connected photovoltaic (PV) system under various environmental conditions. Due to the non-linear characteristics, PV system will exhibit multiple peaks...