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Optimal design method for building energy systems using genetic algorithms
AbstractIn this paper, a new optimal design method for building energy systems is proposed. This method provides the most efficient energy system, best combination of equipment capacity and best operational planning for cooling, heating, and power simultaneously with respect to certain criteria such as energy consumption, CO2 emission, etc. Specifically for this paper, the authors apply this method to a sample building as a case study. The “Genetic Algorithms (GA)” optimization method, which can resolve nonlinear optimization problems, is adopted for this optimization analysis. Also its applicability is analyzed in a case study. In order to validate the accuracy of this method, the correct optimum solution based on comprehensive inquiries is also calculated. A comparison of the GA solution with the correct solution demonstrates fairly good agreement. The results show that the proposed method is sufficiently capable of determining the optimal design and has the potential to be applied to very complex energy systems with appropriate modifications.
Optimal design method for building energy systems using genetic algorithms
AbstractIn this paper, a new optimal design method for building energy systems is proposed. This method provides the most efficient energy system, best combination of equipment capacity and best operational planning for cooling, heating, and power simultaneously with respect to certain criteria such as energy consumption, CO2 emission, etc. Specifically for this paper, the authors apply this method to a sample building as a case study. The “Genetic Algorithms (GA)” optimization method, which can resolve nonlinear optimization problems, is adopted for this optimization analysis. Also its applicability is analyzed in a case study. In order to validate the accuracy of this method, the correct optimum solution based on comprehensive inquiries is also calculated. A comparison of the GA solution with the correct solution demonstrates fairly good agreement. The results show that the proposed method is sufficiently capable of determining the optimal design and has the potential to be applied to very complex energy systems with appropriate modifications.
Optimal design method for building energy systems using genetic algorithms
Ooka, Ryozo (Autor:in) / Komamura, Kazuhiko (Autor:in)
Building and Environment ; 44 ; 1538-1544
16.07.2008
7 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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