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Modeling, Assessment, and Optimization of Energy Systems
- 1st Edition - September 18, 2020
- Author: Hoseyn Sayyaadi
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 1 6 6 5 6 - 7
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 1 6 6 5 7 - 4
Modelling, Assessment, and Optimization of Energy Systems provides comprehensive methodologies for the thermal modelling of energy systems based on thermodynamic, exergoeco… Read more
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Request a sales quoteModelling, 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 of energy engineering, mechanical, chemical engineering and researchers in the field of analysis and optimization of energy systems
1. Introduction
2. Thermal modeling and analysis2.1 Introduction 2.2 Chapter’s outline 2.3 Review of thermodynamic principles2.4 Fundamental of exergetic analysis 2.5 Thermal assessment of energy system based on the exergy concepts2.6 Precise exergetic evaluation2.7 Case study 2.8 Summary2.9 ExercisesReferences
3. Advanced Thermal Models 3.1 Introduction3.2 Chapter’s outline3.3 Finite-time thermodynamics3.4 Finite-speed thermodynamics3.5 Combined finite-time/finite-speed models3.6 Quasi-steady models (case study: Stirling engines) 3.7 Comprehensive combined thermal models (case study: Stirling engines)3.8 Summary3.9 ExercisesReferences
4. Combined thermal, economic, and environmental models4.1 Introduction 4.2 Chapter’s outline4.3 Exergoeconomic modeling4.4 Exergoenvironmental modeling4.5 Exergoenvironomic modeling4.6 Case studies4.7 Summary4.8 Exercises References
5. Soft computing and statistical tools for developing analytical models5.1 Preface 5.2 Outline 5.3 Artificial neural network (ANN) 5.4 Group method of data handling (GMDH) type neural network 5.5 Genetic programming (GP)5.6 Stepwise regression method (SRM)5.7 Multiple linear regression (MLR) 5.8 Using computer codes and toolboxes to develop statistical models5.9 Case studies5.10 Summary 5.11 ExercisesReferences
6. Optimization basics6.1 Preface6.2 Outline6.3 General definition6.4 Theory of optimization 6.5 Mathematical optimization 6.6 Metaheuristic optimization approaches 6.7 Hybrid optimization approaches 6.8 Multiobjective optimization 6.9 Optimization toolbox of the MATLAB software 6.10 Dynamic optimization of energy systems 6.11 Optimization of large energy systems 6.12 Case studies 6.13 Results 6.14 Summary 6.15 Exercises References
7. Decision-making in optimization and assessment of energy systems7.1 Preface 7.2 Outline 7.3 LINMAP method 7.4 TOPSIS method 7.5 Fuzzy Bellman-Zadeh method 7.6 AHP and fuzzy-AHP methods7.7 Decision-making software 7.8 Case studies 7.9 Summary 7.10 Exercises References
8. Real-time optimization of energy systems using the soft-computing approaches 8.1 Introduction 8.2 Outline of this chapter 8.3 Iterative exergoeconomic optimization 8.4 Fuzzy inference system, FIS, for real-time optimization 8.5 Case studies for real-time optimization using the FIS 8.6 Assessment of the FIS for real-time optimization of energy systems 8.7 Adaptive neuro-fuzzy inference system, ANFIS, for real-time optimization 8.8 Case studies for real-time optimization using the ANFIS 8.9 Assessment of the ANFIS for real-time optimization of energy systems 8.10 Comparing FIS, ANFIS, and conventional optimization methods 8.11 Summary 8.12 Exercise References
9. Conclusion
Appendix
Index
- No. of pages: 558
- Language: English
- Edition: 1
- Published: September 18, 2020
- Imprint: Academic Press
- Paperback ISBN: 9780128166567
- eBook ISBN: 9780128166574
HS
Hoseyn Sayyaadi
Dr Sayyaadi is 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 79 journal articles and 98 conference papers up to Aug. 2020.
His research interests are exergy and exergoeconomic analyses, modelling and optimization of energy systems, multi-objective optimization and decision making, machine learning tools for modelling and optimization of energy systems including soft-computing and statistical tools (SCST), fuzzy inference system (FIS), and artificial neuro-fuzzy inference system (ANFIS), hydrogen production, heat exchangers, Stirling engines, power generation systems, and HVAC and refrigeration systems.
Affiliations and expertise
Professor of Mechanical Engineering, Faculty of Mechanical Engineering-Energy Division, K.N. Toosi University of Technology, Tehran, IranRead Modeling, Assessment, and Optimization of Energy Systems on ScienceDirect