國立虎尾科技大學 |

AI and IOT in Renewable Energy

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	AI and IOT in Renewable Energy/ edited by Rabindra Nath Shaw, Nishad Mendis, Saad Mekhilef, Ankush Ghosh.
其他作者:	Ghosh, Ankush.
面頁冊數:	XII, 109 p. 70 illus., 55 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Renewable and Green Energy. -
電子資源:	https://doi.org/10.1007/978-981-16-1011-0
ISBN:	9789811610110

AI and IOT in Renewable Energy
AI and IOT in Renewable Energy[electronic resource] /edited by Rabindra Nath Shaw, Nishad Mendis, Saad Mekhilef, Ankush Ghosh. - 1st ed. 2021. - XII, 109 p. 70 illus., 55 illus. in color.online resource. - Studies in Infrastructure and Control,2730-6461. - Studies in Infrastructure and Control,.

A Day Ahead Power Output Forecasting of three PV Systems using Regression, Machine Learning and Deep Learning Techniques -- Internet of Things and Internet of Drones in the Renewable Energy Infrastructure Towards Energy Optimization -- Reinforcement Learning Algorithm to Reduce Energy Consumption in Electric Vehicles -- Spotted Hyena Optimization (SHO) Algorithm based Novel Control Approach for Buck DC-DC Converter Fed PMBLDC Motor -- Simulation and Performance Analysis of Standalone Photovoltaic System with Boost Converter Under Irradiation and Temperature -- Analysis of Variation in Locational Marginal Pricing under Influence of Stochastic Wind Generation -- Optimal Integration of Plug-In Electric Vehicles Within a Distribution Network Using Genetic Algorithm -- Frequency Control of 5kW Self-Excited Induction Generator Using Gravitational Search Algorithm and Genetic Algorithm -- Cloud Based Real-time Vibration and Temperature Monitoring System for Wind Turbine -- Smart Solar-Powered Smart Agricultural Monitoring System Using Internet of Things Devices.

This book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions. Intelligence allows the system to optimize the power, thereby making it a power efficient system; whereas, Internet of Things makes the system independent of wire and flexibility in operation. As a result, intelligent and IOT paradigms are finding increasing applications in the study of renewable energy systems. This book presents advanced applications of artificial intelligence and the internet of things in renewable energy systems development. It covers such topics as solar energy systems, electric vehicles etc. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities engaged in the study and performance prediction of renewable energy systems. .

ISBN: 9789811610110

Standard No.: 10.1007/978-981-16-1011-0doiSubjects--Topical Terms:

683875
Renewable and Green Energy.

LC Class. No.: TK7885-7895

Dewey Class. No.: 621.38

AI and IOT in Renewable Energy
LDR:03806nam a22004335i 4500 001 1054146
003 DE-He213
005 20210812193902.0
007 cr nn 008mamaa
008 220103s2021 si | s |||| 0|eng d
020 $a 9789811610110 $9 978-981-16-1011-0
024 7 $a 10.1007/978-981-16-1011-0 $2 doi
035 $a 978-981-16-1011-0
050 4 $a TK7885-7895
050 4 $a TK5105.8857
072 7 $a THR $2 bicssc
072 7 $a TEC007000 $2 bisacsh
072 7 $a THR $2 thema
072 7 $a GPFC $2 thema
082 0 4 $a 621.38 $2 23
245 1 0 $a AI and IOT in Renewable Energy $h [electronic resource] / $c edited by Rabindra Nath Shaw, Nishad Mendis, Saad Mekhilef, Ankush Ghosh.
250 $a 1st ed. 2021.
264 1 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2021.
300 $a XII, 109 p. 70 illus., 55 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Studies in Infrastructure and Control, $x 2730-6461
505 0 $a A Day Ahead Power Output Forecasting of three PV Systems using Regression, Machine Learning and Deep Learning Techniques -- Internet of Things and Internet of Drones in the Renewable Energy Infrastructure Towards Energy Optimization -- Reinforcement Learning Algorithm to Reduce Energy Consumption in Electric Vehicles -- Spotted Hyena Optimization (SHO) Algorithm based Novel Control Approach for Buck DC-DC Converter Fed PMBLDC Motor -- Simulation and Performance Analysis of Standalone Photovoltaic System with Boost Converter Under Irradiation and Temperature -- Analysis of Variation in Locational Marginal Pricing under Influence of Stochastic Wind Generation -- Optimal Integration of Plug-In Electric Vehicles Within a Distribution Network Using Genetic Algorithm -- Frequency Control of 5kW Self-Excited Induction Generator Using Gravitational Search Algorithm and Genetic Algorithm -- Cloud Based Real-time Vibration and Temperature Monitoring System for Wind Turbine -- Smart Solar-Powered Smart Agricultural Monitoring System Using Internet of Things Devices.
520 $a This book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions. Intelligence allows the system to optimize the power, thereby making it a power efficient system; whereas, Internet of Things makes the system independent of wire and flexibility in operation. As a result, intelligent and IOT paradigms are finding increasing applications in the study of renewable energy systems. This book presents advanced applications of artificial intelligence and the internet of things in renewable energy systems development. It covers such topics as solar energy systems, electric vehicles etc. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities engaged in the study and performance prediction of renewable energy systems. .
650 2 4 $a Renewable and Green Energy. $3 683875
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Professional Computing. $3 1115983
650 1 4 $a Cyber-physical systems, IoT. $3 1226036
650 0 $a Renewable energy resources. $3 563364
650 0 $a Artificial intelligence. $3 559380
650 0 $a Computer software. $3 528062
650 0 $a Embedded computer systems. $3 562313
650 0 $a Internet of things. $3 1023130
650 0 $a Computer engineering. $3 569006
700 1 $a Ghosh, Ankush. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1356083
700 1 $a Mekhilef, Saad. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1355741
700 1 $a Mendis, Nishad. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1359153
700 1 $a Shaw, Rabindra Nath. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1357271
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789811610103
776 0 8 $i Printed edition: $z 9789811610127
776 0 8 $i Printed edition: $z 9789811610134
830 0 $a Studies in Infrastructure and Control, $x 2730-6461 $3 1359154
856 4 0 $u https://doi.org/10.1007/978-981-16-1011-0
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)