{"product_id":"applied-soft-computing-and-embedded-system-applications-in-solar-energy-9780367639020","title":"Applied Soft Computing and Embedded System Applications in Solar Energy","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003eApplied Soft Computing and Embedded System Applications in Solar Energy explores how embedded system applications can improve the efficiency of solar photovoltaic (PV) systems by smart monitoring and controlling. It discusses the growth of artificial intelligence in computing and the data-driven issues faced by soft computing methods in energy-related problems. The book offers real-time implementation of soft computing and embedded systems in solar energy, addressing microgrid and smart grid projects, energy management, and power regulation. It is intended for students, professionals, and researchers in electrical and computer engineering fields. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 236 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 25 September 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Taylor \u0026amp; Francis Ltd\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eApplied Soft Computing and Embedded System Applications in Solar Energy delves into the realm of energy systems and soft computing methodologies, encompassing a diverse range of approaches and application perspectives. The authors explore how embedded system applications can effectively handle the intelligent monitoring and control of standalone and grid-connected solar photovoltaic (PV) systems, aiming to enhance their efficiency. The growth of artificial intelligence with embedded system applications has ushered systems, impacting nearly all fields of science and engineering. Soft computing methods employed in energy-related problems frequently encounter data-driven challenges, such as optimization, classification, clustering, or prediction. The authors present real-time implementations of soft computing and embedded systems in the field of solar energy to address issues related to 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, and other specific smart grid energy system applications. The book is designed for students, professionals, and researchers in electrical and computer engineering fields, engaged in renewable energy resources, microgrids, and smart grid projects.\u003cbr\u003e\u003cbr\u003eIntegration of hardware with standalone PV panels and real-time monitoring of factors affecting the efficiency of the PV panels\u003cbr\u003e\u003cbr\u003eOffers real-time implementation of soft computing and embedded systems in the field of solar energy\u003cbr\u003e\u003cbr\u003eDiscusses how soft computing plays a crucial role in predicting the efficiency of standalone and grid-connected solar PV systems\u003cbr\u003e\u003cbr\u003eDiscusses how embedded system applications can effectively handle the intelligent monitoring and control of standalone and grid-connected solar photovoltaic (PV) systems, aiming to enhance their efficiency.\u003cbr\u003e\u003cbr\u003eThe growth of artificial intelligence with embedded system applications has ushered systems, impacting nearly all fields of science and engineering. Soft computing methods employed in energy-related problems frequently encounter data-driven challenges, such as optimization, classification, clustering, or prediction. The authors present real-time implementations of soft computing and embedded systems in the field of solar energy to address issues related to 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, and other specific smart grid energy system applications. The book is designed for students, professionals, and researchers in electrical and computer engineering fields, engaged in renewable energy resources, microgrids, and smart grid projects.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 453g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 234 x 156 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9780367639020\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":44641986904314,"sku":"9780367639020","price":50.44,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1697218849646_book.jpg?v=1697483482","url":"https:\/\/shulphink.com\/products\/applied-soft-computing-and-embedded-system-applications-in-solar-energy-9780367639020","provider":"Shulph Ink","version":"1.0","type":"link"}