Internet of Things and Machine Learning for Improving Solar-PV Plant Efficiency: Forecasting Aspects

The Internet of Things (IoT) and machine learning (ML) are one of the technology combinations that can help real-time power generation issues as reflected by the existing loads. The renewable energy contribution in the global power sector has made tremendous progress in 2019 with an installed power capacity of 200 Gigawatts (GW). Presently, solar-PV based renewable energy sources increased by 12% in 2019 to a record 115 GW (direct current), for a total of 627 GW. This chapter explains the forecasting methods used in the literature and factors affecting and challenges associated with the solar-PV forecasting. The basics of the Internet of Things and machine learning techniques and their applications are described. The chapter elaborates on forecasting and efficiency improvement. Real-time application of the solar-PV system and explanation of SRRA data collection are also presented.