Evolutionary Multi-Objective Optimization Applied to Industrial Refrigeration Systems for Energy Efficiency.
Author(s) : NEDJAH N., MACEDO MOURELLE L. (de), LIZARAZU M. S. D.
Type of article: Periodical article
Summary
Refrigeration systems based on cooling towers and chillers are widely used equipment in industrial buildings, such as shopping centers, gas and oil refineries and power plants, among many others. Cooling towers are used to recover the heat rejected by the refrigeration system. In this work, the refrigeration is composed of cooling towers dotted with ventilators and compression chillers. The growing environmental concerns and the current scenario of scarce water and energy resources have lead to the adoption of actions to obtain the maximum energy efficiency in such refrigeration equipment. This backs up the application of computational intelligence to optimize the operating conditions of the involved equipment and cooling processes. In this context, we utilize multi-objective optimization algorithms to determine the optimal operational setpoints of the cooling system regarding the cooling towers, its fans and the included chillers. We use evolutionary multi-objective optimization to provide the best trade-offs between two conflicting objectives: maximization of the effectiveness of the cooling towers and minimization of the overall power requirement of the refrigeration system. The optimization process respects the constraints to guarantee the correct and safe operation of the equipment when the evolved solution is implemented. In this work, we apply three evolutionary multi-objective algorithms: Non-dominated Sorting Genetic Algorithm (NSGA-II), Micro-Genetic Algorithm (Micro-GA) and Strength Pareto Evolutionary Algorithm (SPEA2). The results obtained are analyzed under different scenarios and models of the cooling system’s equipment, allowing for the selection of the best algorithm and best equipment’s model to achieve energy efficiency of the studied refrigeration system.
Available documents
Format PDF
Pages: 27 p.
Available
Free
Details
- Original title: Evolutionary Multi-Objective Optimization Applied to Industrial Refrigeration Systems for Energy Efficiency.
- Record ID : 30030195
- Languages: English
- Subject: Technology
- Source: Energies - vol. 15 - n. 15
- Publishers: MDPI
- Publication date: 2022/08
- DOI: http://dx.doi.org/10.3390/en15155575
Links
See other articles in this issue (3)
See the source
-
Synthesis of cooling water systems with multipl...
- Author(s) : RUBIO-CASTRO E., SERNA-GONZÁLEZ M., PONCE-ORTEGA J. M., et al.
- Date : 2013/01
- Languages : English
- Source: Applied Thermal Engineering - vol. 50 - n. 1
View record
-
Flow and heat transfer characteristics of indir...
- Author(s) : WU X. P., YANG L. J., DU X. Z., et al.
- Date : 2014/05
- Languages : English
- Source: International Journal of thermal Sciences - vol. 79
View record
-
Energy saving analysis and discussion of coolin...
- Author(s) : WANG R., LUO W., LIU Z., et al.
- Date : 2014/10
- Languages : Chinese
- Source: HV & AC - vol. 44 - n. 295
- Formats : PDF
View record
-
Rotating contacting disk-based improved cooling...
- Author(s) : RANE M., RANE A.
- Date : 2022
- Languages : English
- Source: 2022 Purdue Conferences. 19th International Refrigeration and Air-Conditioning Conference at Purdue.
- Formats : PDF
View record
-
Performance analysis of a low approach low temp...
- Author(s) : NASRABADI M., FINN D. P.
- Date : 2013/06/16
- Languages : English
- Source: Clima 2013. 11th REHVA World Congress and 8th International Conference on Indoor Air Quality, Ventilation and Energy Conservation in Buildings.
- Formats : PDF
View record