Secure CheckoutPersonal information is secured with SSL technology.
Free ShippingFree global shipping
No minimum order.
Modelling, Assessment, and Optimization of Energy Systems provides comprehensive methodologies for the thermal modelling of energy systems based on thermodynamic, exergoeconomic and exergoenviromental approaches. It provides advanced analytical approaches, assessment criteria and the methodologies to obtain analytical expressions from the experimental data. The concept of single-objective and multi-objective optimization with application to energy systems is provided, along with decision-making tools for multi-objective problems, multi-criteria problems, for simplifying the optimization of large energy systems, and for exergoeconomic improvement integrated with a simulator EIS method.
This book provides a comprehensive methodology for modeling, assessment, improvement of any energy system with guidance, and practical examples that provide detailed insights for energy engineering, mechanical engineering, chemical engineering and researchers in the field of analysis and optimization of energy systems.
- Offers comprehensive analytical tools for the modeling and simulation of energy systems with applications for decision-making tools
- Provides methodologies to obtain analytical models of energy systems for experimental data
- Covers decision-making tools in multi-objective problems
Engineers and post-graduates in energy, mechanical, and chemical engineering as well as researchers in the field of analysis and optimization of energy systems
2. Thermodynamic modelling and analysis
2.2. Exergetic model
2.3. Exergetic assessments
2.4. Exergy analysis of processes
2.5. Advance exergetic analysis
3. Exergoeconomic (Thermoeconomic) modelling and analysis
3.2. Fundamental of exergoeconomic analysis
3.3. Economic analysis
3.4. Exergoeconomic assessments
3.5. Advance exergoeconomic analysis
4. Exergoenviromental analysis
4.2. Fundamental of exergoenviromental analysis
4.3. Life cycle assessment
4.4. Exergoenviromental assessment
5. Soft computing and statistical tools for developing analytical models using experimental data
5.2. Artificial neural network (ANN) model
5.3. Group method of data handling (GMDH)
5.4. Multiple-linear regression (MLR) method
5.5. Stepwise regression method (SRM)
6. Optimization basics
6.2. Single-objective optimization
6.3. Multi-objective optimization
7. Decision making in the optimization and assessment of energy systems
7.2. Decision-making methods in multi-objective optimization problems
7.3. Multi-criteria decision-making for selection of the best strategy in utilizing energy systems
8. Exergoeconomic improvement integrated with a simulator, EIS method
9. Real-time optimization methods of energy systems using the soft-computing approaches
9.2. Expert-based Fuzzy inference system, FIS method
9.3. Artificial neuro-fuzzy inference system, ANFIS method
- No. of pages:
- © Academic Press 2021
- 1st October 2020
- Academic Press
- Paperback ISBN:
Dr Sayyaadi is an Associate Professor of Mechanical Engineering at K.N. Toosi University of Technology, focusing on design, modelling, and optimization of energy systems. He has a number of publications in this field with 60 journal articles and 70 conference papers. His research interests are exergy and exergoeconomic analyses, optimization of energy systems, Multi objective optimization and decision making, Hydrogen production, Heat exchangers, Power generation systems and HVAC and refrigeration systems.
Associate Professor of Mechanical Engineering, Faculty of Mechanical Engineering-Energy Division, K.N. Toosi University of Technology, Tehran, Iran
Elsevier.com visitor survey
We are always looking for ways to improve customer experience on Elsevier.com.
We would like to ask you for a moment of your time to fill in a short questionnaire, at the end of your visit.
If you decide to participate, a new browser tab will open so you can complete the survey after you have completed your visit to this website.
Thanks in advance for your time.