Study on the Optimum Design Method of Heat Source Systems with Heat Storage Using a Genetic Algorithm

Min Yu, Yujin Nam
2016 Energies  
Recently, a heat source system utilizing a heat storage tank for energy savings in buildings was designed. A heat storage tank is an effective system for solving the qualitative and quantitative differences in the required building energy. On the other hand, the existing design process of a heat storage system is difficult to determine if the air-conditioning time is unclear, and the design in a real-working level is too inaccurate, causing oversizing and a high initial investment cost. This
more » ... ults in inefficient operation despite the introduction of an efficient system. Therefore, this study proposes an optimal design method of a heat source system using a thermal storage tank. To demonstrate the usefulness of the proposed design method, feasibility studies were conducted with the existing system designs. As a result, the optimal solution could reduce the initial cost by approximately 25.6% when following the conventional design process and it was approximately 40% lower than the real-working method. In conclusion, the conventional designs are inefficiently over-designed and the optimal design solution is superior. In this regard, the suggested optimal design method is efficient when designing a heat source system using a thermal storage tank. Energies 2016, 9, 849 2 of 17 source system idle through the use of a heat storage tank as a buffer station. In addition, it can save operation costs with a heat storage system by utilizing the electricity tariff effectively, which is called "nighttime electricity service" offered from the Korea Electric Power Corporation [5] . The building can take advantage of the low rates if a building operates systems to store heat and power during the night for the next day load. Furthermore, according to the tariff of electricity offered from the Korea Electric Power Corporation, the electricity price is classified according to the load time (light, medium, heavy) and season. On the other hand, enormous design variables are generated to use energy efficiently by applying not only a heat storage system, but also many design elements, such as renewable heat sources, complex system combinations, and multiple unit application. Accordingly, the design process becomes increasingly more complex to optimize. Even if considering only a heat storage system, the initial construction costs would be increased by the storage tank and control system. Moreover, heat losses occur by the difference between the heat storage and heat rejection time highlighting the need for an optimal design and strategy for energy efficient and economical operation. Many studies of the heat storage systems on the heat storage materials and storage methods have been carried out, such as ice storage system, thermally activated building system, and using phase change material (PCM) [6] [7] [8] . In addition, several studies on the economic and efficient design method have been carried out in recent years. Yu et al. [9] examined the design capacity of a heat storage system through cases and derived the best combination considering the system performance and energy consumption. As for optimization using an algorithm, Sun et al. [10] reviewed the optimal operation method of a heat storage system, particularly for peak load shifting. According to the manuscript, the method can be configured according to the type of thermal storage system, such as the thermally activated building system or using PCM. Despite that, most studies focused on the day for optimization; hence, it is necessary to consider a more extended period of time for the design days. Ikeda and Ooka [11] examined the optimal operation method of an energy storage system and suggested the economic optimal operation in accordance with the rates. In the United Kingdom, a study of the optimal design and operation of the system combined with a storage tank was conducted for district heating by considering three standard electricity tariffs. On the other hand, there is a limit on the decision of the system capacities at a constant value [12] . Shirazi et al. [13] optimized the ice thermal energy storage system considering the compressor ratio and temperature as the design parameter and the optimal solution could improve both the exergetic efficiency and total costs. Wu et al. [14] evaluated an optimal system combination, including a thermal storage system considering the size of each system, operation schedule and pipelines to establish an energy network. They considered several system combinations for a case study but the design parameters of each system were limited. Unlike previous studies performed on the optimization of a thermal storage system, it was insufficient according to the decision of the system capacity in the design process. For more optimization in design and operation, it is necessary to develop an optimal design method including capacity decision. In this study, to propose the optimal design method of the heat source system including a thermal storage tank, the conventional design process of a thermal storage system was considered and an optimal method was developed utilizing a genetic algorithm. The optimization process of this study integrates a variety of input data, such as weather conditions, building, heat sources, system efficiency, economy, and operational conditions. In this paper, an optimization model is constructed based on the iSIGHT (Dassault Systèms Simulia Corp., Providence, RI, USA) tool to validate the proposed method and the optimization results are developed according to the representative load patterns of the daytime, nighttime, and 24 h to evaluate the usefulness of the method. In addition, a feasibility study was carried out with the conventional designs.
doi:10.3390/en9100849 fatcat:myiilee2lzcm7ohf2cuklqo7qe