DOI QR코드

DOI QR Code

A Performance Analysis on a Chiller with Latent Thermal Storage According to Various Control Methods

잠열 축열식 칠러시스템의 제어 방식에 따른 성능 분석

  • Kang, Byung Ha (School of Mechanical Engineering, Kookmin University) ;
  • Kim, Dong Jun (Department of Mechanical Engineering, Graduate School, Kookmin University) ;
  • Lee, Choong Seop (Department of Mechanical Engineering, Graduate School, Kookmin University) ;
  • Chang, Young Soo (School of Mechanical Engineering, Kookmin University)
  • 강병하 (국민대학교 기계공학부) ;
  • 김동준 (국민대학교 대학원 기계공학과) ;
  • 이충섭 (국민대학교 대학원 기계공학과) ;
  • 장영수 (국민대학교 기계공학부)
  • Received : 2017.08.22
  • Accepted : 2017.09.28
  • Published : 2017.11.10

Abstract

A chiller, having a thermal storage system, can contribute to load-leveling and can reduce the cost of electricity by using electricity at night. In this study, the control experiments and simulations are conducted using both conventional and advanced methods for the building cooling system. Advanced approaches, such as the "region control method", divide the control region into five zones according to the size of the building load, and determines the cooling capacities of the chiller and thermal storage. On the other hand, the "dynamic programming method" obtains the optimal cooling capacities of the chiller and thermal storage by selecting the minimum-cost path by carrying out repetitive calculations. The "thermal storage priority method" shows an inferior chiller performance owing to the low-part load operation, whereas the chiller priority method leads to a high electric cost owing to the low utilization of thermal storage and electricity at night. It has been proven that the advanced control methods have advantages over the conventional methods in terms of electricity consumption, as well as cost-effectiveness. According to the simulation results during the winter season, the electric cost when using the dynamic programming method was 6.5% and 8.9% lower than that of the chiller priority and the thermal storage priority methods, respectively. It is therefore concluded that the cost of electricity utilizing the region control method is comparable to that of the dynamic programming method.

Keywords

References

  1. Seo, I. Y., Lee, S. E., and Park, Y. K., 2013, Characteristics of summer load peak in Korea, Proceedings of the CICS, pp. 424-425.
  2. Kintner-Meyer, M. and Emery, A. F., 1995, Cost optimal analysis and load shifting potentials of cold storage equipment, ASHRAE Trans, Vol. 101, No. 2, pp. 539-548.
  3. Spethmann, D. H., 1993, Application considerations in optimal control of cool storage, ASHRAE Trans, pp. 1009-1015.
  4. Braun, J. E., 1992, A comparion of heat pump-priority, storage priority, and optimal control of an ice-storage system, ASHRAE Transactions : Symposia, pp. 893-902.
  5. Lee, D.-Y., Jung, S-H., and Kang, B. H., 1999, Comparative analysis of the minimum capacity of an ice-on-coil thermal storage system for various operation strategies, Korean Journal of Air-Conditioning and Refrigeration Engineering, Vol. 11, No. 3, pp. 401-413.
  6. Henze, G. P., Dodier, R. H., and Krarti, M., 1997, Development of a predictive optimal controller for thermal energy storage systems, HVAC&R Research, Vol. 3, No. 3, pp. 233-264. https://doi.org/10.1080/10789669.1997.10391376
  7. Braun, J. E., 2007, A near-optimal control strategy for cool storage systems with dynamic electric rates, HVAC&R Research, Vol. 13, No. 4, pp. 557-580. https://doi.org/10.1080/10789669.2007.10390972
  8. Jung, S. H., Lee, D. Y., Kang, B. H., and Kim, W. S., 2000, Control strategy for economic operation of an ice-storage system considering cooling load variation, Korean Journal of Air-Conditioning and Refrigeration Engineering, Vol. 12, No. 2, pp. 140-149.
  9. Chen, H.-J., Wnag, D. W. P., and Chen, S.-L., 2005, Optimization of an ice-storage air conditioning system using dynamic programming method, International Journal of Applied Thermal Engineering, Vol. 25, pp. 461-472. https://doi.org/10.1016/j.applthermaleng.2003.12.006
  10. Henze, G. P., Biffar, B., Kohn, D., and Becker, M. P., 2008, Optimal design and operation of a thermal storage system for a chilled water plant serving pharmaceutical buildings, International Journal of Energy and Buildings, Vol. 40, pp. 1004-1019. https://doi.org/10.1016/j.enbuild.2007.08.006
  11. Kirk, H. D. and Braun, J. E., 1996, Development and Evaluation of a rule-based control strategy for ice storage system, HVAC&R Research, Vol. 2, No. 4, pp. 312-336. https://doi.org/10.1080/10789669.1996.10391352
  12. Lee, K. H., Choi, B. Y., Joo, Y. J., Lee, S. R., and Han, S. H., 2000, Optimal scheduling of ice storage system with prediction of cooling loads, Korean Journal of Air-Conditioning and Refrigeration Engineering, Vol. 12, No. 11, pp. 982-993.
  13. Lee, K. H., Choi, B. Y., and Lee, S. R., 2008, An Evaluation of heat pump control strategy in ice storage system for cost-saving operation, Korean Journal of Air-Conditioning and Refrigeration Engineering, Vol. 20, No. 2, pp. 97-105.
  14. Jung, C. S., 1993, Ice storage system, Korean J. of Air-Conditioning and Refrigeration Eng., Vol. 22, No. 2, pp. 101-108.
  15. Lee, C. S., 2015, A study on optimal control methods for cooling of heat pump and latent heat storage system, Ph. M. thesis., Department of Mechanical Engineering, Kookmin University.
  16. LabVIEW 2012 SP1, National Instruments Company.
  17. Kim, D. J., Jung, W. S., Chang, Y. S., and Kang, B. H., 2017, Heating performance analysis of the region control method for heat pump with thermal storage system, Journal of Mechanical Science and Technology(in press).
  18. Seok, H. T. and Kim, K. W., 2001, Thermal performance evaluation of design parameters and development of load prediction equations of office buildings, Korean Journal of Air-Conditioning and Refrigeration Engineering, Vol. 13, No. 9, pp. 914-921.
  19. KSES, 2013, Korean Standard Weather data, The Korean Solar Energy Society.
  20. Korea Electric Power Corporation, 2013, KEPCO Selective Terms of Supply.
  21. Arnold, D., 1991, Heat transfer characteristics of ice capsules for encapsulated cool storage systems, Proceedings of the ASME/JSME Thermal Engineering Conf., Vol. 3, pp. 335-341.
  22. MATLAB 2016b, Mathworks.