Energy Iot Architecture From Theory To Practice
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Energy IoT Architecture
Author: Stuart McCafferty
language: en
Publisher: Artech House Publishers
Release Date: 2022-12-31
This book provides a very common-sense approach to transforming the Electricity Industry to meet clean energy goals and simplifying coordination with DER at scale with plug and play interoperability over time. It shows you a new way to architect solutions using a modern, event-driven, standards-based, elastic, cloud-based, distributed architecture to simplify and abstract communications with utility, customer, and third-party owned clean energy assets. The book describes the architectural and technological problems of our 20th Century centralized model and provides a pragmatic alternative architecture with examples of how to seamlessly integrate large numbers of Distributed Energy Resources (DER) with centralized systems that take advantage of intelligent edge devices through coordination instead of direct command and control. It also includes references to DOE's Laminar Grid Architecture philosophy and shows how the Energy IoT Reference Architecture is aligned to solve today's biggest Electricity Industry problems. You'll find detailed explanations of common energy IoT reference architecture; understand integration of utility, customer, and third party distributed grid assets to support grid services and market opportunities, and master the elastic scalability solution which is considered by many to be the biggest problem in utility systems for DER. This is a must-have resource for architects, engineers, software developers, government officials, undergraduate students, and professors
Energy IoT Architecture: From Theory to Practice
This book provides a very common-sense approach to transforming the Electricity Industry to meet clean energy goals and simplifying coordination with DER at scale with plug and play interoperability over time. It shows you a new way to architect solutions using a modern, event-driven, standards-based, elastic, cloud-based, distributed architecture to simplify and abstract communications with utility, customer, and third-party owned clean energy assets. The book describes the architectural and technological problems of our 20th Century centralized model and provides a pragmatic alternative architecture with examples of how to seamlessly integrate large numbers of Distributed Energy Resources (DER) with centralized systems that take advantage of intelligent edge devices through coordination instead of direct command and control. It also includes references to DOE’s Laminar Grid Architecture philosophy and shows how the Energy IoT Reference Architecture is aligned to solve today’s biggest Electricity Industry problems. You’ll find detailed explanations of common energy IoT reference architecture; understand integration of utility, customer, and third party distributed grid assets to support grid services and market opportunities, and master the elastic scalability solution which is considered by many to be the biggest problem in utility systems for DER. This is a must-have resource for architects, engineers, software developers, government officials, undergraduate students, and professors.
Robust Battery Management System Design With MATLAB
This book introduces several battery management problems and provides solutions using model-based approaches. It provides detailed coverage of battery management problems, including battery impedance estimation, battery capacity estimation, state of charge estimation, state of health estimation, battery thermal management, and optimal charging algorithms. The book introduces important battery management problems in a modularized fashion, decoupling each battery management problem from others as much as possible, allowing you to focus on understanding a particular topic rather than having to understand all aspects of a battery management system. You will get the necessary background to understand, implement and improve battery fuel gauges in electric vehicles, and general state of health of the battery; use proven models and algorithms to estimate the thermal properties of a battery; and know the basics of smart battery charger design. You will also be equipped to accurately estimate battery features of vehicles, such as state of charge, expected charging time, and state of health, to make customized charging waveforms for each vehicle. The book teaches you how to create simulation environments to test and validate algorithms against model uncertainty and measurement noise. In addition, the importance of benchmarking battery management algorithms is covered, and several bench marking metrics are presented. Included MATLAB codes give you an easy way to test the algorithms using realistic data and to develop and test alternative solutions. This is a useful and timely guide for battery engineers at all levels, as well as research scientists and advanced students working in this robust and rapidly advancing area.