Energy production and management in the 21st century V : the quest for sustainable energy
著者
書誌事項
Energy production and management in the 21st century V : the quest for sustainable energy
(WIT transactions on ecology and the environment, 255)
WIT Press , Computational Mechanics International, c2022
- タイトル別名
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Fifth international conference on energy production and management : the quest for sustainable energy
Energy Production and Management 2022
Energy production and management in the 21st century 5
5th international conference on energy production and management
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注記
Includes bibliographical references and author index
"This book contains a selection of papers among those presented at the 5th International Conference on Energy Production and Management: the Quest for Sustainable Energy, organized by the Wessex Institute of Technology, UK"--Pref
Other title from added t.p. verso
内容説明・目次
内容説明
目次
- Section 1: Energy production and economics Lower limits of coupling physical properties of shale oil reservoirs for the application of CO2 huff-n-puff
- Evaluation of the state of the region's energy cogeneration systems based on the reliability of power supply in conditions of high economic risks
- Adoption of technology platforms in the electric power industry: New opportunities
- Regulations for efficiency assessment of investment projects in the energy sector: Brief overview and comparative analysis
- Artificial intelligence-based demand-side response management of renewable energy
- Financial tools for biogas project implementation at wastewater treatment plants: A case study of the Russian Federation Section 2: Energy and sustainability Analysis of the water-energy-food nexus and its contribution to energy development
- Water-energy-food nexus tool selection and application of tools to a regional case study
- Energy efficiency through water-use efficiency in leisure centres Section 3: Energy and the built environment Choreographing network-based influences on the homeowners' decision journey about energy-related renovations
- Machine learning approach for predictive maintenance in an advanced building management system
- Integrated scalable framework for smart energy management
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