Clinical Insights about Mental Difference

Self-actualization is sought by all people. Experience with mental difference, both as a patient and as a staff member in a mental hospital leads to a greater understanding of the meaning and nature of this difference. It arises from variations in biographical experience, social interactions, personal frame and self-choice. Providing the mentally different with the responsibility of at least limited choice empowers them while affirming their human dignity and worth

Multi-variable Extremum Seeking Control for Mini-split Air-conditioning System

In this study, a multi-variable extremum seeking control (ESC) scheme is proposed for a variable-speed mini-split air-conditioning system. The control inputs are the evaporator and condenser fan speeds, respectively, while the total power consumption is used as the feedback. As accurate model is hard and expensive to obtain for the AC system of interest in real time, nearly model-free self-optimizing control methods such as ESC is considered a more feasible solution to practical deployment. Recent development in ESC, and especially the Newton based multi-variable ESC method with online Hessian estimation provides the capability for real-time decoupling among the input channels (Ghaffari et al. 2012). Different from gradient based multi-variable ESC method, the Newton based multi-variable ESC provides uniform convergence characteristics for all the control inputs. Therefore, the Newton based multi-variable ESC is suitable for multi-input real-time optimization, especially for the case with large gain variation and coupling for different control input channels. An experimental setup is developed with a 9000 BTU variable-speed mini-split AC system (Mitsubishi MSZ-GE09NA & MUY-GE09NA). A 2000 Watts electrical heater works as the heat load. The indoor unit of the mini-split system and the heater are installed in a 4’x8’x6’ insulated chamber. A Watt Node Pulse WNB-3D-240-P power meter is utilized to measure the power consumption of the mini-split system. To achieve the speed control of the evaporator fan motor and condenser fan, a TMS320F28035 based customized motor controller is used. Three RTD temperature sensors are deployed to measure the indoor temperature, the outdoor temperature and the condenser coil temperature, respectively. The data acquisition and control algorithms are implemented on a National Instruments CompactRIO platform. During the system operation, the CompactRIO reads the power consumption sent from the power meter, which will be fed into the ESC control algorithm to get the speed reference for both the evaporator fan and the condenser fan. Then, the speed reference will be applied to the motor controllers for each motor. Meanwhile, some other measurements such as indoor temperature, outdoor temperature, the speed feedback for both the motors, etc. are also monitored by the CompactRIO. The experimental study is planned to include three scenarios of ESC implementation: 1) single-input ESC with evaporator fan speed input only; 2) single-input ESC with condenser fan speed input only; and 3) multi-variable ESC with both evaporator and condenser fan speed inputs. Experimental study has performed for the first scenario. Under the ambient temperature of 75F and indoor room temperature set-point of 68F, the ESC control results in an energy saving of 20%. The work under way includes the other two scenarios and in particular the multi-variable ESC. More experiments will be performed under various weather conditions

Experimental Study on Extremum Seeking Control for Efficient Operation of Air-side Economizer

The air-side economizers are a major class of energy-saving devices for ventilation and air conditioning systems by taking advantage of outdoor air during cool or cold weather. Typical rule based control cannot justify energy optimal operation, while model based optimization of air-side economizer operation depends on the accurate knowledge of system model and enthalpy sensing of the ambient and return-air. Such optimal operation is hard to achieve in practice due to inaccurate model and degradation/failure of temperature and relative humidity (RH) sensors. As pointed out by Seem and House (2010), under certain indoor/outdoor air conditions, there exists a convex map between damper position and energy consumption of an air handling unit (AHU), which implies an optimal damper opening minimizing the cooling-coil load. Such convexity guarantees the use of gradient-search type of real-time optimization methods. An Extremum Seeking Control (ESC) was proposed by Li et al. (2009), where the chilled water flow rate of the cooling coil (equivalently the energy consumption) is minimized by tuning the damper opening. The proposed framework was validated with a Modelica based dynamic simulation model of an air-side economizer. This study is conducted to perform experimental evaluation of the ESC control of air-side economizer. The experimental setup is anchored on a Lennox XC25 variable-speed air conditioner. The Lennox, CBX40UHV indoor air handler unit is equipped with duct work to form an air-side economizer, connected to a foam based 16\u27X8\u27X8\u27 test chamber. The Lasko 751320 electrical heaters are used as heat source. The Honeywell HCM-890 humidifiers and Soleus Air SG-DEH-70EIP-6 dehumidifiers are used to regulate the indoor air humidity. A National Instruments CompactRIO-9024 platform is used for data acquisition and control. Major measurements include temperature, relative humidity (RH) and power consumption. A Watt Node Pulse WNB-3D-240-P electric power meter is used for power measurement. The Omega P-L-1/10-1/8-6-0-T-3 temperature sensors and Veris Industries HN3XVSX RH sensors are installed to monitor the indoor and outdoor air conditions. The Omega HHT13 speed sensors are used to measure fan speeds, while Fluke 80i-110s current sensors are used to measure the compressor motor current. The ESC controller is implemented with the damper opening as input and the total power consumption as feedback. Two experiments have been performed under different indoor/outdoor air conditions. The first experiment was performed under outdoor air temperature 23°C and RH 65%, a heat load of 6000 W and indoor temperature setpoint 28°C. The ESC turned on the outdoor damper 100% automatically to allow maximal outdoor air resulting in indoor RH 50%. The total power consumption was reduced from 540 W to 450 W with an energy saving of 16.67%. The second experiment was performed under same conditions with indoor RH regulated to 40%.The ESC turned off the outdoor damper to allow minimal outdoor air. The power consumption was reduced from 620 W to 600 W with an energy saving of 3.33%. More experiments will be performed in warmer weather in February and March to further validate the performance of the ESC controller

Model Selection for Predicting the Return Time from Night Setback

Night setback is a common strategy used to reduce energy use in buildings. It involves increasing the cooling setpoint and decreasing the heating setpoint in a zone during unoccupied periods. To ensure occupant comfort and maximize energy savings, the zone temperature must be returned to the range defined by the occupied cooling and heating setpoints at occupancy, but not before. The time required to cool down or warm up a zone from a night setback condition is referred to as the return time and algorithms for predicting return time are commonly referred to as optimal start algorithms. Optimal start algorithms generally employ a model for predicting return time. This study describes the selection of separate return time models for cooling (i.e., a model for predicting the return time when cooling is required) and heating from 57 candidates. The following model forms were considered: τ = f (Tf - Ti), τ = f ((Tf - Ti), u), τ = f ((Tf - Ti), Tout), and τ = f ((Tf - Ti), u, Tout) where τ is the return time, Tf is the zone temperature at the end of the optimal start period, Ti is the zone temperature at the beginning of the optimal start period, u is exponentially weighted moving average (EWMA) of the zone cooling or heating demand at the beginning of the optimal start period, and Tout is the outdoor air temperature at the beginning of the optimal start period. Computer simulations were used to generate year-long data sets relating return time to the model inputs. The simulations considered the influence of climate, building mass, controller tuning, zone orientation, and the unoccupied control strategy on the return time. In all, 140 cooling data sets and 104 heating data sets were generated. For each data set, least squares regression was performed to determine the parameters for each of the 57 models considered. The performance of each model was quantified using the average root mean square prediction error across all simulations. The study revealed that the best models for predicting return time use the zone temperature change and the EWMA of the zone cooling or heating demand as inputs. The EWMA of the zone cooling or heating demand provides an indication of the recent history of the cooling or heating load on a zone and can account for intermittent cooling or heating that is required to keep the zone temperature within the bounds of the unoccupied setpoints. Notably, outdoor air temperature, a common input in optimal start algorithms, is not used. To the best of the authors\u27 knowledge, zone cooling and heating demand have not been previously used as an input in an optimal start algorithm. The full paper will provide a detailed description of the simulations and model comparison undertaken in this study

Self-optimizing Control of Cooling Tower for Efficient Operation of Chilled Water Systems

The chilled-water systems, mainly consisting of electric chillers and cooling towers, are crucial for the ventilating and air conditioning systems in commercial buildings. Energy efficient operation of such systems is thus important for the energy saving of commercial buildings. This paper presents an extremum seeking control (ESC) scheme for energy efficient operation of the chilled-water system, and presents a Modelica based dynamic simulation model for demonstrating the effectiveness of the proposed control strategy. The simulated plant consists of a water-cooled screw chiller and a mechanical-draft counter-flow wet cooling tower. The ESC scheme takes the total power consumption of the chiller compressor and the tower fan as feedback, and uses the fan speed setting as the control input. The inner-loop controllers for the chiller operation include two proportional-integral (PI) control loops for regulating the evaporator superheat and the chilled water temperature. Simulation was conducted on the dynamic simulation model of the whole plant including the screw chiller and the cooling tower for different scenarios. The simulation results demonstrated the effectiveness of the proposed ESC strategy in searching for the optimal tower fan speed set-point under tested circumstances, and the potential for energy saving is also evaluated

Extremum Seeking Control of Hybrid Ground Source Heat Pump System

The ground source heat pump (GSHP) technology is a renewable alternative for space conditioning by rejecting/absorbing heat to/from the ground, which has demonstrated higher energy efficiency for residential and commercial buildings. As the system capacity is limited by the initial cost of construction of ground-loop heat exchanger (GHE), developing the so-called Hybrid GSHP system by utilizing supplemental heat rejecters such as cooling towers has emerged as a cost-effective alternative. In practice, operational efficiency of Hybrid GSHP system mainly depends on 1) the actual characteristics of heat pump, cooling tower, GHE and other equipment; 2) ambient air and ground conditions. In particular, the GHE heat transfer is heavily affected by the ground thermal characteristics which, however, is difficult and expensive in practice to determine due to the complexity of soil type and distribution. In addition, the actual cooling tower characteristics can vary significantly. Such uncertainties bring forth dramatic difficulty for successful application of model based control or optimization methods. In this study, an extremum seeking control (ESC) strategy is proposed for efficient operation of a hybrid GSHP system with cooling tower, which minimizes the total power (i.e. GHE loop water pump, cooling tower fan and pump, and the heat-pump compressor) consumption by tuning the air-flow rate of the cooling tower fan and the GHE loop water flow rate. To evaluate the proposed control method, a Modelica based model of the Hybrid GSHP system is developed by utilizing the Buildings Library developed by the Lawrence Berkeley National Laboratory, which consists of a 20-borehole GHE, a water-to-water heat pump, a counter-flow cooling tower and a plate heat exchanger. The transient conduction model of vertical GHE in the Buildings Library is adopted, which is based on a finite-volume method inside the borehole and cylindrical source model outside the borehole. A variable-flow water pump model is constructed for the GHE water loop, which gives power consumption under different operating scenarios. A cooling tower model in the Buildings Library is adopted, which is a static polynomial model based on a York cooling tower correlation. The relative air flow rate can be regulated to maintain the leaving water temperature at the setpoint, and then the corresponding fan power consumption is obtained. The heat pump model is based on the evaporator temperature, condenser temperature and Carnot efficiency. An inner-loop proportional-integral (PI) controller is implemented to regulate the evaporator leaving water temperature at 7 deg-C. Under the air wet-bulb temperature of 35 deg-C and dry-bulb temperature 23 deg-C, steady-state simulation of the plant model yields the static map of the total power with respect to the cooling tower relative air flow rate and the GHE water flow rate, which indicates about 25% power variation across the adjustable range of inputs. Simulation was conducted in two conditions: change in evaporator inlet water temperature and change in ambient air condition. The simulation study under way is to validate the effectiveness of the proposed ESC strategy, and the potential for energy saving will also be evaluated

Experimental Study on Extremum Seeking Control for Efficient Operation of Air-side Economizer

The air-side economizers are a major class of energy-saving devices for ventilation and air conditioning systems by taking advantage of outdoor air during cool or cold weather. Typical rule based control cannot justify energy optimal operation, while model based optimization of air-side economizer operation depends on the accurate knowledge of system model and enthalpy sensing of the ambient and return-air. Such optimal operation is hard to achieve in practice due to inaccurate model and degradation/failure of temperature and relative humidity (RH) sensors. As pointed out by Seem and House (2010), under certain indoor/outdoor air conditions, there exists a convex map between damper position and energy consumption of an air handling unit (AHU), which implies an optimal damper opening minimizing the cooling-coil load. Such convexity guarantees the use of gradient-search type of real-time optimization methods. An Extremum Seeking Control (ESC) was proposed by Li et al. (2009), where the chilled water flow rate of the cooling coil (equivalently the energy consumption) is minimized by tuning the damper opening. The proposed framework was validated with a Modelica based dynamic simulation model of an air-side economizer. This study is conducted to perform experimental evaluation of the ESC control of air-side economizer. The experimental setup is anchored on a Lennox XC25 variable-speed air conditioner. The Lennox, CBX40UHV indoor air handler unit is equipped with duct work to form an air-side economizer, connected to a foam based 16\u27X8\u27X8\u27 test chamber. The Lasko 751320 electrical heaters are used as heat source. The Honeywell HCM-890 humidifiers and Soleus Air SG-DEH-70EIP-6 dehumidifiers are used to regulate the indoor air humidity. A National Instruments CompactRIO-9024 platform is used for data acquisition and control. Major measurements include temperature, relative humidity (RH) and power consumption. A Watt Node Pulse WNB-3D-240-P electric power meter is used for power measurement. The Omega P-L-1/10-1/8-6-0-T-3 temperature sensors and Veris Industries HN3XVSX RH sensors are installed to monitor the indoor and outdoor air conditions. The Omega HHT13 speed sensors are used to measure fan speeds, while Fluke 80i-110s current sensors are used to measure the compressor motor current. The ESC controller is implemented with the damper opening as input and the total power consumption as feedback. Two experiments have been performed under different indoor/outdoor air conditions. The first experiment was performed under outdoor air temperature 23°C and RH 65%, a heat load of 6000 W and indoor temperature setpoint 28°C. The ESC turned on the outdoor damper 100% automatically to allow maximal outdoor air resulting in indoor RH 50%. The total power consumption was reduced from 540 W to 450 W with an energy saving of 16.67%. The second experiment was performed under same conditions with indoor RH regulated to 40%.The ESC turned off the outdoor damper to allow minimal outdoor air. The power consumption was reduced from 620 W to 600 W with an energy saving of 3.33%. More experiments will be performed in warmer weather in February and March to further validate the performance of the ESC controller