Experimental Evaluation for an Extremum Seeking Control Strategy based on Input-output Correlation with a Mini-split Air Conditioning System

Extremum Seeking Control (ESC) has emerged as a model-free real-time optimization framework, typically based on dither-demodulation driven gradient estimation. However, such conventional ESC suffers from slow convergence. Salsbury et al. have recently proposed an input-output correlation based ESC (IOC-ESC) strategy anchored on a statistical analysis. The IOC-ESC algorithm is less sensitive to changes in its internal parameters because of the use of a normalized correlation coefficient in the feedback loop. The design goal of the algorithm is to have only two tunable parameters: (1) a time scale parameter that relates to the time open loop time constant of the system; and (2) the amplitude of the dither signal. A suitable set of generic internal parameters is still in the process of being identified as more test data become available from different system types. For the work reported here, the feedback gain (referred to as the tuning factor) with the IOC-ESC was also tuned for optimal performance. This study aims to conduct an experimental evaluation for the IOC-ESC strategy with a ductless mini-split air conditioning system, compared with conventional ESC (CON-ESC). The system features variable-capacity compressor operation and variable-speed operation for the evaporator and condenser fans. In this study, both single-input and two-input ESC scenarios are tested. The manipulated inputs include the evaporator and condenser fan speeds, while the total power consumption is used as feedback for all cases. The experimental setup is developed with a 9000 BTU variable-speed mini-split AC system serving a 4’x8’x6’ insulated chamber, and an electrical fan heater is used to provide an artificial heat load. The data acquisition and control algorithms are implemented on a National Instruments CompactRIO platform. Both IOC-ESC and CON-ESC are tested with the same setup. For single-input scenario, the manipulated input is the condenser fan speed. The testing results of five trials of IOC-ESC are used to evaluate the impact of the two tuning parameters, i.e. dither frequency and tuning factor, on the ESC performance. IOC-ESC#1, IOC-ESC#4 and IOC-ESC#5 have the same dither frequency but different tuning factors, while IOC-ESC#1, IOC-ESC#2 and IOC-ESC#3 have the same tuning factor but different dither frequencies. The testing results of two trials of CON-ESC are then compared with the IOC-ESC results. Both CON-ESC and IOC-ESC can effectively reduce the power consumption of the mini-split system without sacrificing zone temperature regulation. Moreover, the settling time of IOC-ESC ranges from 300 to 600 seconds, while the settling time of CON-ESC ranges from 900 to 1200 seconds. Overall, the IOC-ESC converges faster than the CON-ESC. For two-input scenario, the manipulated inputs are condenser fan speed and evaporator fan speed. The testing results of the two-input IOC-ESC are compared with the result of a two-input CON-ESC trial by Yan et al. with the same system. The settling times for CON-ESC and IOC-ESC are about 1800 and 1200 seconds, respectively. In summary, both CON-ESC and IOC-ESC can optimize the condenser fan speed and evaporator fan speed for energy efficient operation, while the IOC-ESC converges faster and has fewer tuning parameters

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

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

Extremum Seeking for Stefan PDE with Moving Boundary

This paper presents the design and analysis of the extremum seeking for static maps with input passed through a partial differential equation (PDE) of the diffusion type defined on a time-varying spatial domain whose boundary position is governed by an ordinary differential equation (ODE). This is the first effort to pursue an extension of extremum seeking from the heat PDE to the Stefan PDE. We compensate the average-based actuation dynamics by a controller via backstepping transformation for the moving boundary, which is utilized to transform the original coupled PDE-ODE into a target system whose exponential stability of the average equilibrium of the average system is proved. The discussion for the delay-compensated extremum seeking control of the Stefan problem is also presented and illustrated with numerical simulations.Comment: 10 pages and 10 figure

Performance Analysis of Maximum Power Point Tracking Algorithms Under Varying Irradiation

Photovoltaic (PV) system is one of the reliable alternative sources of energy and its contribution in energy sector is growing rapidly. The performance of PV system depends upon the solar insolation, which will be varying throughout the day, season and year. The biggest challenge is to obtain the maximum power from PV array at varying insolation levels. The maximum power point tracking (MPPT) controller, in association with tracking algorithm will act as a principal element in driving the PV system at maximum power point (MPP). In this paper, the simulation model has been developed and the results were compared for perturb and observe, incremental conductance, extremum seeking control and fuzzy logic controller based MPPT algorithms at different irradiation levels on a 10 KW PV array. The results obtained were analysed in terms of convergence rate and their efficiency to track the MPP.Keywords: Photovoltaic system, MPPT algorithms, perturb and observe, incremental conductance, scalar gradient extremum seeking control, fuzzy logic controller.Article History: Received 3rd Oct 2016; Received in revised form 6th January 2017; Accepted 10th February 2017; Available onlineHow to Cite This Article: Naick, B. K., Chatterjee, T. K. & Chatterjee, K. (2017) Performance Analysis of Maximum Power Point Tracking Algorithms Under Varying Irradiation. Int Journal of Renewable Energy Development, 6(1), 65-74.http://dx.doi.org/10.14710/ijred.6.1.65-7