Two Optimization Techniques for Optimum Control of Energy Use in Comfort Conditions in an Air Conditioning Room

Yılmaz Akgüney


The purpose of this study is to present two optimization techniques in order to be able to decide the optimal control of energy use by staying within the limits of comfort in an air conditioning chamber. With the optimization techniques presented here optimum control is discussed to minimize the energy expenditure to be made by staying within the limits of comfort zone defined by ASHRAE for temperature, humidity, air velocity and air mixing ratio.  For this two different optimization techniques are presented static and dynamic. These two optimization techniques are discussed for an established test facility. Optimization ensures comfort conditions and minimizes energy use.  Static optimization provides the control point within the comfort zone and returns to the air ratio due to minimum energy usage.  For the given external conditions and mixing ratio the control vector is determined so as to minimize the energy use. For the installed system it is appropriate to perform this operation as a static optimization every 20-40 minutes and to send the control vector quantities to the system by calculating at that time. With dynamic optimization there are optimum control points for the variables and feedback controls allow the desired values to remain at these optimum points.  Feedback control is started and control is performed. Due to disturbans factors the control vector to be replaced is changed to minimize the performance criterion defined around these specified values. This optimization is done every 4-6 minutes and the control vector quantities are calculated at the end of these periods and sent to the system.  The deviation of the control room from the optimum control point is corrected by feedback control and optimization techniques.  The optimization techniques presented here are promising as a good alternative for optimum control.

Keywords - Air conditioning chamber, Optimal control, Static optimization, Dynamic optimization

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ISSN (Paper)2224-3232 ISSN (Online)2225-0573

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