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Applied Soft Computing and Embedded System Applications in Solar
Energy deals with energy systems and soft computing methods from a
wide range of approaches and application perspectives. The authors
examine how embedded system applications can deal with the smart
monitoring and controlling of stand-alone and grid-connected solar
photovoltaic (PV) systems for increased efficiency. Growth in the
area of artificial intelligence with embedded system applications
has led to a new era in computing, impacting almost all fields of
science and engineering. Soft computing methods implemented to
energy-related problems regularly face data-driven issues such as
problems of optimization, classification, clustering, or
prediction. The authors offer real-time implementation of soft
computing and embedded system in the area of solar energy to
address the issues with microgrid and smart grid projects (both
renewable and non-renewable generations), energy management, and
power regulation. They also discuss and examine alternative
solutions for energy capacity assessment, energy efficiency systems
design, as well as other specific smart grid energy system
applications. The book is intended for students, professionals, and
researchers in electrical and computer engineering fields, working
on renewable energy resources, microgrids, and smart grid projects.
Examines the integration of hardware with stand-alone PV panels and
real-time monitoring of factors affecting the efficiency of the PV
panels Offers real-time implementation of soft computing and
embedded system in the area of solar energy Discusses how soft
computing plays a huge role in the prediction of efficiency of
stand-alone and grid-connected solar PV systems Discusses how
embedded system applications with smart monitoring can control and
enhance the efficiency of stand-alone and grid-connected solar PV
systems Explores swarm intelligence techniques for solar PV
parameter estimation Dr. Rupendra Kumar Pachauri is Assistant
Professor – Selection Grade in the Department of Electrical and
Electronics Engineering, University of Petroleum and Energy Studies
(UPES), Dehradun, India. Dr. Jitendra Kumar Pandey is Professor
& Head of R&D in the University of Petroleum and Energy
Studies (UPES), Dehradun, India. Mr. Abhishek Sharma is working as
a research scientist in the research and development department
(UPES, India). Dr. Om Prakash Nautiyal is working as a scientist in
Uttarakhand Science Education & Research Centre (USERC),
Department of Information and Science Technology, Govt. of
Uttarakhand, Dehradun, India. Prof. Mangey Ram is working as a
Research Professor at Graphic Era Deemed to be University,
Dehradun, India.
Applied Soft Computing and Embedded System Applications in Solar
Energy deals with energy systems and soft computing methods from a
wide range of approaches and application perspectives. The authors
examine how embedded system applications can deal with the smart
monitoring and controlling of stand-alone and grid-connected solar
photovoltaic (PV) systems for increased efficiency. Growth in the
area of artificial intelligence with embedded system applications
has led to a new era in computing, impacting almost all fields of
science and engineering. Soft computing methods implemented to
energy-related problems regularly face data-driven issues such as
problems of optimization, classification, clustering, or
prediction. The authors offer real-time implementation of soft
computing and embedded system in the area of solar energy to
address the issues with microgrid and smart grid projects (both
renewable and non-renewable generations), energy management, and
power regulation. They also discuss and examine alternative
solutions for energy capacity assessment, energy efficiency systems
design, as well as other specific smart grid energy system
applications. The book is intended for students, professionals, and
researchers in electrical and computer engineering fields, working
on renewable energy resources, microgrids, and smart grid projects.
Examines the integration of hardware with stand-alone PV panels and
real-time monitoring of factors affecting the efficiency of the PV
panels Offers real-time implementation of soft computing and
embedded system in the area of solar energy Discusses how soft
computing plays a huge role in the prediction of efficiency of
stand-alone and grid-connected solar PV systems Discusses how
embedded system applications with smart monitoring can control and
enhance the efficiency of stand-alone and grid-connected solar PV
systems Explores swarm intelligence techniques for solar PV
parameter estimation Dr. Rupendra Kumar Pachauri is Assistant
Professor - Selection Grade in the Department of Electrical and
Electronics Engineering, University of Petroleum and Energy Studies
(UPES), Dehradun, India. Dr. Jitendra Kumar Pandey is Professor
& Head of R&D in the University of Petroleum and Energy
Studies (UPES), Dehradun, India. Mr. Abhishek Sharma is working as
a research scientist in the research and development department
(UPES, India). Dr. Om Prakash Nautiyal is working as a scientist in
Uttarakhand Science Education & Research Centre (USERC),
Department of Information and Science Technology, Govt. of
Uttarakhand, Dehradun, India. Prof. Mangey Ram is working as a
Research Professor at Graphic Era Deemed to be University,
Dehradun, India.
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