Editors:
- Collects original contributions from various researchers to provide a review of the main assessment tools/methods/approaches connected to sustainable energy
- Covers both methods and applications of multi-criteria, fuzzy-sets, algorithm genetics and neural nets (artificial intelligence) and simulations using Monte Carlo analysis, linear programming (LP) and others approaches for energy systems
- Guides the reader to the main tools used for the assessment and simulation procedure task in the energy sector
- Includes supplementary material: sn.pub/extras
Part of the book series: Green Energy and Technology (GREEN, volume 129)
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (19 chapters)
-
Front Matter
-
Multi-Criteria Foundations and Applications
-
Front Matter
-
-
Fuzzy Inference, Artificial Neural Net, Algorithm Genetics
-
Front Matter
-
-
Simulation Models and Approaches
-
Front Matter
-
About this book
In recent years, the concept of energy has been revised and a new model based on the principle of sustainability has become more and more pervasive. The appraisal of energy technologies and projects is complex and uncertain as the related decision making has to encompass environmental, technical, economic and social factors and information sources. The scientific procedure of assessment has a vital role as it can supply the right tools to evaluate the actual situation and make realistic forecasts of the effects and outcomes of any actions undertaken. Assessment and Simulation Tools for Sustainable Energy Systems offers reviews of the main assessment and simulation methods used for effective energy assessment.
Divided across three sections, Assessment and Simulation Tools for Sustainable Energy Systems develops the reader’s ability to select suitable tools to support decision making and implementation of sustainable energy projects. The first is dedicated to the analysis of theoretical foundations and applications of multi-criteria decision making. This is followed by chapters concentrating on the theory and practice of fuzzy inference, neural nets and algorithms genetics. Finally, simulation methods such as Monte Carlo analysis, mathematical programming and others are detailed.
This comprehensive illustration of these tools and their application makes Assessment and Simulation Tools for Sustainable Energy Systems a key guide for researchers, scientists, managers, politicians and industry professionals developing the field of sustainable energy systems. It may also prompt further advancements in soft computing and simulation issues for students and researchers.
Editors and Affiliations
-
Department of Economics, Management and Society and Institutions, University of Molise, Campobasso, Italy
Fausto Cavallaro
About the editor
Fausto Cavallaro holds an M.Sc in Environmental Management and a PhD in Technology and Economics of Processes for Safeguarding the Environment. He is associate professor of “Energy and Environmental Resources” and “Environmental Management Systems” at the University of Molise (Italy). His main fields of research are the following: renewable energy sources; technology assessment; modelling decision support system and fuzzy multicriteria analysis for renewable and conventional energy systems; life cycle assessment (LCA) and environmental management systems (EMS).
Bibliographic Information
Book Title: Assessment and Simulation Tools for Sustainable Energy Systems
Book Subtitle: Theory and Applications
Editors: Fausto Cavallaro
Series Title: Green Energy and Technology
DOI: https://doi.org/10.1007/978-1-4471-5143-2
Publisher: Springer London
eBook Packages: Energy, Energy (R0)
Copyright Information: Springer-Verlag London 2013
Hardcover ISBN: 978-1-4471-5142-5Published: 20 August 2013
Softcover ISBN: 978-1-4471-5796-0Published: 18 August 2015
eBook ISBN: 978-1-4471-5143-2Published: 13 August 2013
Series ISSN: 1865-3529
Series E-ISSN: 1865-3537
Edition Number: 1
Number of Pages: XXV, 427
Topics: Renewable and Green Energy, Renewable and Green Energy, Simulation and Modeling