운전비 절감을 위한 빙축열시스템 냉동기 운전기법 평가

An Evaluation of Chiller Control Strategy in Ice Storage System for Cost-Saving Operation

  • 발행 : 2008.02.10

초록

This paper presents simulated and experimental test results of optimal control algorithm for an encapsulated ice thermal storage system with full capacity chiller operation. The algorithm finds an optimal combination of a chiller and/or a storage tank operation for the minimum total operation cost through a cycle of charging and discharging. Dynamic programming is used to find the optimal control schedule. The conventional control strategy of chiller-priority is the baseline case for comparing with the optimal control strategy through simulation and experimental test. Simulation shows that operating cost for the optimal control with chiller on-off operation is not so different from that with chiller part load capacity control. As a result from the experimental test, the optimal control operation according to the simulated operation schedule showed about 14 % of cost saving compared with the chiller-priority control.

키워드

참고문헌

  1. Demand response, Lawrence Berkeley Laboratory, http://eetd.lbl.gov/ea/drlm-pubs.html
  2. Braun, J. E., 1992, A comparison of chiller- priority, storage-priority, and optimal control of an ice-storage system, ASHRAE Transactions, Vol. 98, Pt. 1, pp. 893-902
  3. 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 Refrigerating Engineering-Journal of the SAREK, Vol. 12, No. 2, pp. 140-149
  4. Lee, K. H., Joo, Y. J., Choi, B. Y. and Kim, S. J., 2000, Model of encapsulated ice storage tanks using charge and discharge characteristics of single ice capsule, Korean Journal of Air-conditioning and Refrigeration Engineering-Journal of SAREK, Vol. 12, No. 4, pp. 333-344
  5. 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 Refrigerating and Air-Conditioning Engineering-Journal of the SAREK, Vol. 12, No. 11, pp. 982-994
  6. Han, D. and Lee, J., 2005, Optimal control algorithms for the full storage ice cooling system, Korean Journal of Air-conditioning and Refrigeration Engineering-Journal of SAREK, Vol. 14, No. 4, pp. 350-358
  7. Ahn, Y. H., Kang, B. H., Kim, S. and Lee, D. Y., 2005, The operation characteristics and cost analysis of an ice thermal storage system, Korean Journal of Air-conditioning and Refrigeration Engineering-Journal of SAREK, Vol. 17, No. 2, pp. 156-164
  8. Shin, K. W. and Lee, Y. S., 2002, The study on cooling load forecasting using neural networks, Korean Journal of Air-conditioning and Refrigeration Engineering-Journal of SAREK, Vol. 14, No. 8, pp. 626-633
  9. Yoo, S. Y., Lee, J. M, Han, K. H. and Han, S. H., 2007, A study on prediction of temperature and humidity for estimation of cooling load, Vol. 19, No. 5, pp. 394-402