9 IoT-based intelligent solar energyharvesting technique with improved efficiency
-
Emdadul Hoque
Abstract
Due to the immense development of the Internet and artificial intelligence technology, Internet of things (IoT) and machine learning in green energy monitoring has become a topic of interest for researchers. In this chapter, an intelligent solar energy- harvesting technique is presented. The efficiency of the solar power generation is heavily influenced by the surface temperature of the solar photovoltaics (PV). After a certain temperature threshold, the efficiency of solar PV decreases. It can be monitored with the help of a thermal camera operated by a drone. The thermal image captured is sent to a cloud server using a NodeMCU (microcontroller unit) module through IoT. Captured data can be analyzed from a distant location. A drone generally covered a vast region, including the outside boundary of the solar panel. A convolutional neural network can be used to extract accurate surface temperature from the solar panel. Based on these data, an active cooling system can automatically control the solar PV’s surface temperature. The proposed method also includes an automated solar monitoring system to obtain better efficiency. The combination of state-of-the-art cooling, intelligent solar tracking with IoT-based condition monitoring of solar panels has made the proposed method interesting for energy researchers.
Abstract
Due to the immense development of the Internet and artificial intelligence technology, Internet of things (IoT) and machine learning in green energy monitoring has become a topic of interest for researchers. In this chapter, an intelligent solar energy- harvesting technique is presented. The efficiency of the solar power generation is heavily influenced by the surface temperature of the solar photovoltaics (PV). After a certain temperature threshold, the efficiency of solar PV decreases. It can be monitored with the help of a thermal camera operated by a drone. The thermal image captured is sent to a cloud server using a NodeMCU (microcontroller unit) module through IoT. Captured data can be analyzed from a distant location. A drone generally covered a vast region, including the outside boundary of the solar panel. A convolutional neural network can be used to extract accurate surface temperature from the solar panel. Based on these data, an active cooling system can automatically control the solar PV’s surface temperature. The proposed method also includes an automated solar monitoring system to obtain better efficiency. The combination of state-of-the-art cooling, intelligent solar tracking with IoT-based condition monitoring of solar panels has made the proposed method interesting for energy researchers.
Chapters in this book
- Frontmatter I
- Preface V
- Contents VII
- 1 Artificial intelligence and Internet of things for renewable energy systems 1
- 2 Power control of modified type III DFIG-based wind turbine system using four-mode type I fuzzy logic controller 41
- 3 An IoT-based approach for efficient home automation 91
- 4 Design and implementation of IoT-enabled smart single-phase energy meter monitoring system 123
- 5 Internet of things (IoT)-based smart grids 165
- 6 Maximum power point tracking control under partial shading conditions using particle swarm optimization algorithm 185
- 7 Wireless monitoring of substation using IoT 215
- 8 Smart grid–based big data analytics using machine learning and artificial intelligence: a survey 241
- 9 IoT-based intelligent solar energyharvesting technique with improved efficiency 279
- Editor’s Brief Biographies 303
- Index 307
Chapters in this book
- Frontmatter I
- Preface V
- Contents VII
- 1 Artificial intelligence and Internet of things for renewable energy systems 1
- 2 Power control of modified type III DFIG-based wind turbine system using four-mode type I fuzzy logic controller 41
- 3 An IoT-based approach for efficient home automation 91
- 4 Design and implementation of IoT-enabled smart single-phase energy meter monitoring system 123
- 5 Internet of things (IoT)-based smart grids 165
- 6 Maximum power point tracking control under partial shading conditions using particle swarm optimization algorithm 185
- 7 Wireless monitoring of substation using IoT 215
- 8 Smart grid–based big data analytics using machine learning and artificial intelligence: a survey 241
- 9 IoT-based intelligent solar energyharvesting technique with improved efficiency 279
- Editor’s Brief Biographies 303
- Index 307
