AC Scheduling Based on Thermodynamics of Indoor for On-Campus Small Data

Abstract

This paper proposes a new day-ahead control scheme of an air conditioning (AC) based on thermodynamic model of indoor-temperature. The thermodynamic model of indoor-temperature can be achieved by modified first-order thermal dynamic equation. For the practical verification of proposed model, we implemented the home energy management system (HEMS) in the laboratory and used real experiment data sets. The proposed model can be represented by a state-space model of indoor-temperature and its parameters are obtained by least square algorithm. Through the proposed thermodynamic model, indoor-temperature can be predicted closely, and a behavior pattern of AC can also be achieved. This research involves the experimental verification of the proposed approach and communication architecture between the aggregator and a system user in a laboratory environment.

Share and Cite:

Choi, H. , Rhee, S. , Ahn, C. and Lim, M. (2015) AC Scheduling Based on Thermodynamics of Indoor for On-Campus Small Data. Journal of Power and Energy Engineering, 3, 282-288. doi: 10.4236/jpee.2015.34038.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Han, D.-M. and Lim, J.-H. (2010) Design and Implementation of Smart Home Energy Management Systems Based on Zigbee. IEEE Transactions on Consumer Electronics, 56, 1417-1425. http://dx.doi.org/10.1109/TCE.2010.5606278
[2] Costanzo, G.T., Zhu, G., Anjos, M.F. and Savard, G. (2012) A System Architecture for Autonomous Demand Side Load Management in Smart Buildings. IEEE Transactions on Smart Grid, 3.
[3] Mohsenian-Rad, A. and Leon-Garcia, A. (2010) Optimal Residential Load Control with Price Prediction in Real-Time Electricity Pricing Environments. IEEE Transactions on Smart Grid, 1, 120-133. http://dx.doi.org/10.1109/TSG.2010.2055903
[4] Areekul, P., Senjyu, T., Toyama, H. and Yona, A. (2010) A Hybrid ARIMA and Neural Network Model for Short- Term Forecasting in Deregulated Market. IEEE Transactions on Power Systems, 25.
[5] Chen, Y., Luh, P.B., Guan, C., Zhao, Y., Michel, L.D., Coolbeth, M.A., Friedland, P.B. and Rourke, S.J. (2010) Short- Term Load Forecasting: Similar Day-Based Wavelet Neural Networks. IEEE Transactions on Power Systems, 25, 322- 330. http://dx.doi.org/10.1109/TPWRS.2009.2030426
[6] Li, B. and Alleyne, A.G. (2010) Optimal On-Off Control of an Air Conditioning and Refrigeration System. Proc. Amer. Control Conf., July, 5892-5897.
[7] Yu, Z., McLaughlin, L., Jia, L., Murphy-Hoye, M.C., Pratt, A. and Tong, L. (2012) Modeling and Stochastic Control for Home Energy Management. Proc. IEEE PES Gen. Meet., July.
[8] McLaughlin, L., Jia, L., Yu, Z. and Tong, L. (2011) Thermal Dynamic for Home Energy Management: A Case Study. Cornell Univ., Ithaca, NY, USA, Tech. Rep. ACSP-TR-10-11-01.
[9] Quiroga, A., Yu, Z. and Tong, L. (2012) Home Energy Management System Thermal Dynamic Model Fitting. Cornell Univ., Ithaca, NY, USA, Tech. Rep. ACSP-TR-09-11-01.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.