MPTCS:A Model Predictive Temperature Control System for Smart Homes
In a world that is frantically going eco-friendly, any reduction of energy consumption is helpful, especially in homes. Heating systems consume a major portion of home energy consumption. Hence, improving their efficiency benefits the global environment, not just the consumer alone. Efficiency of the heating system can be increased in two areas: improving the basic energy transfer efficiency of the heater/cooler or optimizing the operation model (on/off) of the heater/cooler to meet the user needs efficiently. This project explores the latter area.
‘Smart Home’ is the growing concept in improving energy savings as well as functionality in homes. While this technology targets many areas of the home, improving heating systems is a top priority due to their high energy consumption. Some implementations involve on-site measurements and extensive customization that are time consuming and/or expensive.
MPTCS is a computer-based Temperature Control System for Smart Homes that provides optimized operation of heating/cooling systems. This software takes into consideration multiple factors such as the effective rates of the heating systems, thermal coefficients of the building, external temperature, and also the weather forecast. It incorporates Model Predictive Control (MPC) techniques to achieve the optimization goals. MPCTS uses System Identification methods to accumulate the necessary model coefficients on its own and hence doesn’t require on-site measurements. Occupancy schedule and personal temperature preferences are the only customer inputs needed by the system. While meeting the customer needs, the system optimizes the heating/cooling times to be minimal , all the time utilizing external temperatures and weather forecast data. An embedded implementation of MPTCS is feasible when there’s no “Smart Home” computer present.
Once you have the MPTCS, you’ll never again go back to a home that is too hot or too cold at the end of an exhausted day!
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