![Artificial Intelligence and Internet of Things for Renewable Energy Systems](/uploads/posts/2021-12/1639584004_2401_artificial_int_llig_nc__and_int_rn_t_of_things_for_r_n_wabl___n_rgy_syst_ms.jpg)
Автор: Neeraj Priyadarshi, Sanjeevikumar Padmanaban, Kamal Kant Hiran
Издательство: De Gruyter
Серия: De Gruyter Frontiers in Computational Intelligence
Год: 2022
Страниц: 320
Язык: английский
Формат: pdf (true)
Размер: 349.0 MB
This book explains the application of Artificial Intelligence (AI) and Internet of Things (IoT) on green energy systems. The design of smart grids and intelligent networks enhances energy efficiency, while the collection of environmental data through sensors and their prediction through Machine Learning (ML) models improve the reliability of green energy systems.
The Machine Learning models with respect to solar energy storage system predictions are analyzed in Chapter 1. The fourth component of the Internet of things (IoT) system is the user interface; this helps the users to control IoT. Chapter 2 highlights the study and implementation of various types of fuzzy structures using rule-based interfaces for steady-state and transient analysis. Chapter 3 provides a survey of the role, impact, and challenges, and recommended solutions of IoT for smart buildings. Chapter 4 presents a comprehensive design of a low-cost smart single-phase energy meter monitoring system. Chapter 5 explains the IoT-based smart grid. Chapter 6 presents maximum power point tracking control using particle swarm optimization algorithm for photovoltaic (PV) panel affected by partial shading due to shadow casting. Partial shading casted on a PV panel will produce multiple peaks’ power characteristic curve, thus tracking the global peak becomes a challenge especially under dynamic changing partial shading condition. Chapter 7 discusses a wireless system for monitoring and controlling of an electrical substation using NodeMCU (Wi-Fi module), Arduino Uno (microcontroller), ThingSpeak server, and Blynk. The different parameters of the substation such as current, voltage, power factor, frequency, and temperature are monitored using various sensors and electronic components. Smart grid-based Big Data analytics using Machine Learning and Artificial Intelligence has been discussed in Chapter 8. Chapter 9 presents the IoT-based intelligent solar energy-harvesting technique with improved efficiency.
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