Commenced in January 2007
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Edition: International
Paper Count: 30576
Prediction-Based Midterm Operation Planning for Energy Management of Exhibition Hall

Authors: Kwang Ryel Ryu, Jeongmin Kim, Doseong Eom

Abstract:

Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.

Keywords: Machine Learning, Operation Planning, Building Energy Management, simulation-based optimization

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1340210

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References:


[1] Braun, J. E., Reducing energy costs and peak electrical demand through optimal control of building thermal storage. ASHRAE transactions, 96 (2), 1990, pp. 876-888.
[2] L. Pérez-Lombard, J. Ortiz, C. Pout, A review on buildings energy consumption information, Energy Build. 40 (3) 2008, pp. 394–398.
[3] Salsbury, T., Mhaskar, P., & Qin, S. J., Predictive control methods to improve energy efficiency and reduce demand in buildings. Computers & Chemical Engineering, 51, 2013, pp. 77-85.
[4] Garnier, A., Eynard, J., Caussanel, M., & Grieu, S., Predictive control of multizone heating, ventilation and air-conditioning systems in non-residential buildings. Applied Soft Computing, 37, 2015, pp. 847-862.
[5] Drury B. Crawley, Linda K. Lawrie, Frederick C. Winkelmann, EnergyPlus: Creating a new-generation building energy simulation program, Energy and Buildings 33, 2001, pp. 319-331.