Process Design and Modeling of Low-Carbon Energy Systems

This reprint addresses the urgent global challenge of decarbonizing energy systems while ensuring reliability, affordability, and sustainability. Curating 14 interdisciplinary studies, it bridges engineering, economics, and policy to advance renewable integration, carbon market mechanisms, energy st...

Olles dieđut

Furkejuvvon:
Bibliográfalaš dieđut
Materiálatiipa: Online
Giella:eaŋgalasgiella
Almmustuhtton: MDPI - Multidisciplinary Digital Publishing Institute 2025
Fáttát:
Liŋkkat:ONIX_20250812T110751_9783725841257_340
Fáddágilkorat: Lasit fáddágilkoriid
Eai fáddágilkorat, Lasit vuosttaš fáddágilkora!
_version_ 1869523055998402560
collection Directory of Open Access Books
description This reprint addresses the urgent global challenge of decarbonizing energy systems while ensuring reliability, affordability, and sustainability. Curating 14 interdisciplinary studies, it bridges engineering, economics, and policy to advance renewable integration, carbon market mechanisms, energy storage, and socio-technical solutions. Key innovations include AI-driven prediction models like the IAO-LSTM for solar forecasting and the VMD-AOA-GRU hybrid model for wind power optimization, alongside robust dispatch frameworks leveraging pumped hydro storage and reinforcement learning. The issue also explores carbon-internalized thermoeconomic models, resilient multi-energy network planning, and nanomaterials such as nanoporous alumina sheets for anti-frosting applications. Contributions emphasize cross-sector integration (electricity–hydrogen–thermal networks), scalable technology deployment, and adaptive policy frameworks to align with sustainability goals. By synthesizing cutting-edge research, this collection provides actionable insights for policymakers, industry stakeholders, and researchers, highlighting pathways to overcome technical, economic, and regulatory barriers in the energy transition. Future directions call for deeper system coupling, industrial scalability of lab innovations, and equitable policy design to accelerate global decarbonization efforts.
format Online
id doab-20.500.12854ir-165585
institution Directory of Open Access Books
language eng
publishDate 2025
publishDateRange 2025
publishDateSort 2025
publisher MDPI - Multidisciplinary Digital Publishing Institute
publisherStr MDPI - Multidisciplinary Digital Publishing Institute
record_format ojs
spelling doab-20.500.12854ir-1655852025-08-12T09:57:29Z Process Design and Modeling of Low-Carbon Energy Systems Wu, Chenyu Yi, Zhongkai Lin, Chenhui integrated energy system wind power reinforcement learning stochastic optimization resilient planning thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities This reprint addresses the urgent global challenge of decarbonizing energy systems while ensuring reliability, affordability, and sustainability. Curating 14 interdisciplinary studies, it bridges engineering, economics, and policy to advance renewable integration, carbon market mechanisms, energy storage, and socio-technical solutions. Key innovations include AI-driven prediction models like the IAO-LSTM for solar forecasting and the VMD-AOA-GRU hybrid model for wind power optimization, alongside robust dispatch frameworks leveraging pumped hydro storage and reinforcement learning. The issue also explores carbon-internalized thermoeconomic models, resilient multi-energy network planning, and nanomaterials such as nanoporous alumina sheets for anti-frosting applications. Contributions emphasize cross-sector integration (electricity–hydrogen–thermal networks), scalable technology deployment, and adaptive policy frameworks to align with sustainability goals. By synthesizing cutting-edge research, this collection provides actionable insights for policymakers, industry stakeholders, and researchers, highlighting pathways to overcome technical, economic, and regulatory barriers in the energy transition. Future directions call for deeper system coupling, industrial scalability of lab innovations, and equitable policy design to accelerate global decarbonization efforts. 2025-08-12T09:57:27Z 2025-08-12T09:57:27Z 2025 book ONIX_20250812T110751_9783725841257_340 9783725841257 9783725841264 https://directory.doabooks.org/handle/20.500.12854/165585 eng image/jpeg Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/book/10976 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-4126-4 10.3390/books978-3-7258-4126-4 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725841257 9783725841264 270 open access
spellingShingle integrated energy system
wind power
reinforcement learning
stochastic optimization
resilient planning
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities
Process Design and Modeling of Low-Carbon Energy Systems
title Process Design and Modeling of Low-Carbon Energy Systems
title_full Process Design and Modeling of Low-Carbon Energy Systems
title_fullStr Process Design and Modeling of Low-Carbon Energy Systems
title_full_unstemmed Process Design and Modeling of Low-Carbon Energy Systems
title_short Process Design and Modeling of Low-Carbon Energy Systems
title_sort process design and modeling of low carbon energy systems
topic integrated energy system
wind power
reinforcement learning
stochastic optimization
resilient planning
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities
topic_facet integrated energy system
wind power
reinforcement learning
stochastic optimization
resilient planning
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities
url ONIX_20250812T110751_9783725841257_340