Journal of Power and Energy Engineering, 2015, 3, 282-288 Published Online April 2015 in SciRes. http://www.scirp.org/journal/jpee http://dx.doi.org/10.4236/jpee.2015.34038 How to cite this paper: Choi, H.D., Rhee, S.W., Ahn, C.K. and Lim, M.T. (2015) AC Scheduling Based on Thermodynamics of Indoor for On-Campus Small Data. Journal of Power and Energy Engineering, 3, 282-288. http://dx.doi.org/10.4236/jpee.2015.34038 AC Scheduling Based on Thermodynamics of Indoor for On-Campus Small Data Hyun Duck Choi, Soon Woo Rhee, Choon Ki Ahn, Myo Taeg Lim School of Electrical Engineering, Korea University, Seoul, Republic of Korea Email: chlgusejr87@korea.ac.kr , swrhee@korea.ac.kr , hironaka@korea.ac.kr , mlim@korea.ac.kr Received January 2015 Abstract This paper proposes a new day-ahead control scheme of an air conditioning (AC) based on ther- modynamic 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. Keywords Home Energy Management System (HEMS), Least-Square, Convex Optimization, Demand Response (DR), Air-Conditioning (AC) 1. Introduction Through the smart grid project offering a two-way communication frame, a home energy management system (HEMS) is able to manage residential load control based on measurement for the home environment, the user’s comfort, and electricity bills [1]-[3]. The main issue concerning the design of HEMS is how to provide the intel- ligent solution for energy consumption that reflects the customer’s specific lifestyle. The suitable HEMS should have the capabilities to schedule the load demands to minimize the expenditure on electricity bills and user’s uncomfortable sense simultaneously. Accurate load forecast for residential appliance is essential for efficient consumption of the electrical energy [4] [5]. In order to maintain balance between electricity production and demand on the network, accurate fore- cast for appliance load is one of the important issues in smart grid. However, residential load forecasting is usually difficult, due to its random nature of turning on/off. Many researches for residential load forecasting have been proposed over the years and still remains an important issue. Air conditioning (AC) unit is the representative appliance which belongs to the category of thermostatically controlled appliance [6]. Thus, the analysis of thermodynamic model of indoor-temperature with AC is required