Development of an optimization method for a heat source and a chart for operational design using a genetic algorithm and Lagrange multiplier

Abstract

Abstract Various optimization methods for heat sources and operational designs have been studied to reduce energy consumption in the building sector. Some problems, however, remain to be improved. Furthermore, some designers plan building services considering empirical laws in general buildings. Even if they plan on using the optimum design, the plans are not necessarily the most suitable for people who operate heat sources at operation centers. This study developed an optimization method for a heat source using a genetic algorithm and Lagrange multiplier as an improvement of previous methods. Furthermore, a chart for an operational design was also generated. The genetic algorithm was used to determine the capacity of heat source machines and the Lagrange multiplier method was used to determine the optimal operating schedules of available heat source machines. The results show that the proposed method can provide optimization solutions under the condition of continuous load rates, the calculation is faster than those of previous methods, and the chart is convenient for workers at operation centers. Using the chart, operators can easily understand which heat sources to operate and how much output they will provide.

Keywords

• genetic algorithm
• Lagrange multiplier
• optimal design
• optimization