Bøger af Chuzo Ninagawa

This book describes new energy service controls of VRF (Variable Refrigerant Flow) air-conditioners, i.e., distributed-type air-conditioners for commercial buildings in the near future, in the context of the energy savings for CO2 reduction and the reform of the electric power system. In other words, this book introduces the state-of-the-art technology of the next-generation distributed building air-conditioning energy service system, from IoT cloud control to AI optimal control, as well as standards for the smart grid supply and demand adjustment market. Rather than simple saving energy by On Off operations or shifting set- temperatures, the author proposes technology that sends numerical commands for the air-conditioner inverters directly from the cloud. By using this innovative IoT method, this book describes how to realizes the AI optimal cloud control as a cluster of air-conditioners while machine-learning of each air conditioner's situation.

This book deals with analysis techniques for TCP, UDP, Web, and SOAP data transmission performance on the IoT cloud side, CSMA-type, and multi-hop data transmission performance on the IoT edge side, as well as gateway receives buffer and transmit packet assembly data transmission performance.As mathematical tools for the analysis of communication performance, universal analysis methods such as stochastic processes, queues, Markov processes, and communication traffic simulators are applied to actual examples, and their usage is described in detail. This book aims to provide lifelong skills for analyzing communication performance that will serve as the basis for the future evolution of the IoT.

This book focuses on building air conditioning demand response and power storage batteries as the resources that make up the virtual power plant. The research and its outcomes presented in this book provide an overview of virtual power plant technology. The contents focus on both fundamentals and advanced topics such as role of central power supply control office, battery charge and discharge control system, power system simulation, system design for practical application, etc. This is a highly informative and carefully presented book, providing insight to students, engineers, and researchers in the field of power systems

This book describes the practical application of artificial intelligence (AI) methods using time series data in system control. This book consistently discusses the application of machine learning to the analysis and modelling of time series data of physical quantities to be controlled in the field of system control.Since dynamic systems are not stable steady states but changing transient states, the changing transient states depend on the state history before the change. In other words, it is essential to predict the change from the present to the future based on the time history of each variable in the target system, and to manipulate the system to achieve the desired change. In short, time series is the key to the application of AI machine learning to system control. This is the philosophy of this book: "e;time series data"e; + "e;AI machine learning"e; = "e;new practical control methods"e;.This book can give my helps to undergradate or graduate students, institute researchers and senior engineers whose scientific background are engineering, mathematics, physics and other natural sciences.

This book deals with analysis techniques for TCP, UDP, Web, and SOAP data transmission performance on the IoT cloud side, CSMA-type, and multi-hop data transmission performance on the IoT edge side, as well as gateway receives buffer and transmit packet assembly data transmission performance.As mathematical tools for the analysis of communication performance, universal analysis methods such as stochastic processes, queues, Markov processes, and communication traffic simulators are applied to actual examples, and their usage is described in detail. This book aims to provide lifelong skills for analyzing communication performance that will serve as the basis for the future evolution of the IoT.

This book focuses on building air conditioning demand response and power storage batteries as the resources that make up the virtual power plant.