Chapter 3 Optimal design of process energy systems integrating sustainable considerations
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Luis Fernando Lira-Barragán
Abstract
This chapter presents a novel approach for designing sustainable trigeneration systems (i.e., heating, cooling, and power generation cycles) integrated with heat exchanger networks and accounting simultaneously for economic, environmental, and social objectives. The trigeneration system comprises steam and organic Rankine cycles and an absorption refrigeration cycle. Multiple sustainable energy sources such as solar energy, biofuels, and fossil fuels are considered to drive the steam Rankine cycle. The model aims to select the optimal working fluid to operate the organic Rankine cycle and to determine the optimal system to drive the absorption refrigeration cycle. The residual energy available in the steam Rankine cycle and/or the process excess heat can be employed to run both the organic Rankine cycle and the absorption refrigeration cycle to produce electricity and refrigeration below the ambient temperature, respectively. Two example problems are presented to show the applicability of the proposed methodology.
Abstract
This chapter presents a novel approach for designing sustainable trigeneration systems (i.e., heating, cooling, and power generation cycles) integrated with heat exchanger networks and accounting simultaneously for economic, environmental, and social objectives. The trigeneration system comprises steam and organic Rankine cycles and an absorption refrigeration cycle. Multiple sustainable energy sources such as solar energy, biofuels, and fossil fuels are considered to drive the steam Rankine cycle. The model aims to select the optimal working fluid to operate the organic Rankine cycle and to determine the optimal system to drive the absorption refrigeration cycle. The residual energy available in the steam Rankine cycle and/or the process excess heat can be employed to run both the organic Rankine cycle and the absorption refrigeration cycle to produce electricity and refrigeration below the ambient temperature, respectively. Two example problems are presented to show the applicability of the proposed methodology.
Kapitel in diesem Buch
- Frontmatter I
- Contents V
- List of contributing authors VII
- Chapter 1 Optimization and its importance for chemical engineers: challenges, opportunities, and innovations 1
- Chapter 2 Deterministic optimization of distillation processes 25
- Chapter 3 Optimal design of process energy systems integrating sustainable considerations 79
- Chapter 4 Metaheuristics for the optimization of chemical processes 113
- Chapter 5 Surrogate-based optimization techniques for process systems engineering 159
- Chapter 6 Data-driven techniques for optimal and sustainable process integration of chemical and manufacturing systems 215
- Chapter 7 Applications of Bayesian optimization in chemical engineering 255
- Chapter 8 Sensitivity assessment of multi-criteria decision-making methods in chemical engineering optimization applications 283
- Chapter 9 Hybrid optimization methodologies for the design of chemical processes 305
- Chapter 10 Optimization under uncertainty in process systems engineering 343
- Chapter 11 Optimal control of batch processes in the continuous time domain 379
- Chapter 12 Supply chain optimization for chemical and biochemical processes 401
- Chapter 13 Future insights for optimization in chemical engineering 425
- Index 445
Kapitel in diesem Buch
- Frontmatter I
- Contents V
- List of contributing authors VII
- Chapter 1 Optimization and its importance for chemical engineers: challenges, opportunities, and innovations 1
- Chapter 2 Deterministic optimization of distillation processes 25
- Chapter 3 Optimal design of process energy systems integrating sustainable considerations 79
- Chapter 4 Metaheuristics for the optimization of chemical processes 113
- Chapter 5 Surrogate-based optimization techniques for process systems engineering 159
- Chapter 6 Data-driven techniques for optimal and sustainable process integration of chemical and manufacturing systems 215
- Chapter 7 Applications of Bayesian optimization in chemical engineering 255
- Chapter 8 Sensitivity assessment of multi-criteria decision-making methods in chemical engineering optimization applications 283
- Chapter 9 Hybrid optimization methodologies for the design of chemical processes 305
- Chapter 10 Optimization under uncertainty in process systems engineering 343
- Chapter 11 Optimal control of batch processes in the continuous time domain 379
- Chapter 12 Supply chain optimization for chemical and biochemical processes 401
- Chapter 13 Future insights for optimization in chemical engineering 425
- Index 445
