Smart IoT System for Renewable Energy Resource

Renewable energy resources are used as distributed generation (DG) units and installed near to where the energy is converted and consumed. Further, the integration of renewable energy sources at home is very important. IoT helps smart grids to support various network functions throughout the generat...

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Detaylı Bibliyografya
Diğer Yazarlar: Cano-Ortega, Antonio (Editör), Sánchez-Sutil, Francisco (Editör)
Materyal Türü: Elektronik Kitap Bölümü
Dil:İngilizce
Baskı/Yayın Bilgisi: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
Konular:
Online Erişim:DOAB: download the publication
DOAB: description of the publication
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245 1 0 |a Smart IoT System for Renewable Energy Resource 
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300 |a 1 electronic resource (282 p.) 
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520 |a Renewable energy resources are used as distributed generation (DG) units and installed near to where the energy is converted and consumed. Further, the integration of renewable energy sources at home is very important. IoT helps smart grids to support various network functions throughout the generation, distribution, and consumption of energy by incorporating IoT devices (such as sensors, actuators, and smart meters), as well as by providing connectivity, automation, and tracking for such devices. For these applications, the use of low-power long-range wireless networks (LPWAN) is fundamental to facilitate all the necessary tasks in the smart grids in City 4.0 and Industry 4.0. The integration of renewable energies (photovoltaic solar, wind energy, biomass energy, hydroelectric energy, and other sources) in smart grids implies the monitoring of households, cities, industries, and electric vehicles at all times. In this sense, the development of monitoring and control applications using mobile devices is a fundamental tool in this type of system, which complements all the possibilities offered by the IoT. Smart energy meters are used to allow for communication between consumers and utility command centers to exchange messages about electrical consumption. Thus, it is essential to have access from any location and instant access to information using mobile devices or computers. 
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546 |a English 
650 7 |a Research & information: general  |2 bicssc 
650 7 |a Physics  |2 bicssc 
653 |a knowledge-based sensor 
653 |a Internet of Things 
653 |a high-concentration photovoltaic systems 
653 |a sun tracker 
653 |a buildings energy management 
653 |a deep learning 
653 |a energy consumption prediction 
653 |a LSTM 
653 |a autoencoder 
653 |a load forecasting 
653 |a smart sensors 
653 |a smart meter 
653 |a temporal data granularity 
653 |a electric load profile 
653 |a time slices 
653 |a time series 
653 |a advanced metering infrastructure 
653 |a monitoring 
653 |a data acquisition systems 
653 |a renewable energy 
653 |a multi-objective optimization 
653 |a reactive power (RP) planning 
653 |a hybrid algorithm 
653 |a virus colony search 
653 |a particle swarm optimization 
653 |a LoRaWAN 
653 |a smart irrigation systems 
653 |a smart energy 
653 |a IoT 
653 |a renewable energy sources 
653 |a photovoltaic energy 
653 |a I-V curve 
653 |a monitoring and data acquisition 
653 |a microgrid 
653 |a open-source 
653 |a communication protocols 
653 |a DC interrupting 
653 |a digitization 
653 |a remote control 
653 |a electric energy measurement 
653 |a miniature circuit breaker 
653 |a power meter 
653 |a internet of things 
653 |a load control 
653 |a energy meter 
653 |a smart socket 
653 |a intelligent campus 
653 |a smart building 
653 |a internet of things platform 
653 |a remote monitoring and control 
653 |a classification 
653 |a data anomalies 
653 |a data imputation 
653 |a energy consumption data 
653 |a ensemble classifiers 
653 |a machine learning 
653 |a smart home data 
653 |a smart meter data 
653 |a tracebase dataset 
653 |a home energy management system 
653 |a smart home 
653 |a cloud infrastructure 
653 |a distributed PV 
653 |a energy management system 
653 |a energy storage units 
653 |a charging piles 
653 |a smart grid 
653 |a redundancy 
653 |a Home Assistant 
653 |a low-carbon island 
653 |a Kinmen 
856 4 0 |a www.oapen.org  |u https://mdpi.com/books/pdfview/book/8251  |7 0  |z DOAB: download the publication 
856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/128785  |7 0  |z DOAB: description of the publication