Numerical Simulation and Performance Assessment of ANN-INC Improved Maximum Power Point Tracking System for Solar Photovoltaic System Under Changing Irradiation Operation

Abstract

The Government of India has set itself the ambitious target of meeting the country's rapidly rising demand, which is mainly met by coal and oil.  Government has targeted to produce 40 percent of total energy generation through renewable energy by 2030. New Delhi works hard to produce 175 GW (GW) of renewable energy by 2022 with prevailing solar power, with a goal of 100GW, and wind power. Increasing environmental concerns, declining fuel supplies, and increased energy requirements have directed our focus towards an aspirational future based entirely on energy supply technologies for renewable sources and non-polluting sources. Power generation via photovoltaic (PV), due to their benefits such as ease of available, low cost, negligible environmental pollution and lower maintenance tariff, is increasingly becoming popular in comparison with other renewable resources. To minimise the effects of changing environmental conditions and improve the power provided by the PV system, the Maximum Power Point Tracking (MPPT) technique was used. It keeps track of the panel's maximum power output in order to increase energy generation. Easy design, low cost, good performance characteristics with minimal output power variability, and the ability to monitor in changing conditions easily and quickly are all features of MPPT controllers. In the current study, an MPPT system based on an improved neural network was created. As compared to existing software computing technologies and conventional power point monitoring methods, the proposed system has a lower transient and steady state response. On a standalone solar photovoltaic system, extensive research has been conducted and a model for system analysis has been created. The proposed system displayed less transient and a steady state response as compared to conventional power point monitoring methods.