Performance Analysis of a Solar Continuous Adsorption Refrigeration System

A study is conducted on the performances of a solar powered continuous-adsorption refrigerator considering two particular days as references cases,namely,the summer solstice(June 21st)and the autumn equinox(September 21st).The cooling capacity,system performance coefficient and the daily rate of available cooling energy are assessed.The main goal is to compare the performances of a solar adsorption chiller equipped with a hot water tank(HWT)with an equivalent system relying on solar collectors with no heat storage module.The daily cooling rates for the solar refrigerator are found to be 102.4 kWh and 74.3 kWh,respectively,on June 21st and on September 21st,using a total collector’s area of 43.47 m2.The corresponding values for the adsorption chiller equipped with a hot water tank of 2 m3(and using a total collector’s area of 72.45 m2),are 127.1 kWh and 106.13 kWh,respectively.

An Application of Nonlinear Autoregressive(NARX)Model to Predict Adsorbent Bed Temperature of Solar Adsorption Refrigeration System

In any solar adsorption refrigeration system,there are three major components:a solar collector adsorbent bed,a condenser and an evaporator.All of those components operate at different temperature levels.A solar collector with a tubular adsorbent configuration is proposed and numerically investigated.In this study,a nonlinear auto-regressive model with exogenous input is applied for the prediction of adsorbent bed temperature during the heating and desorption period.The developed neuronal model uses the MATLAB Network toolbox to obtain a better configuration network,applying multilayer feed-forward,the TANSIG transfer function,and the back-propagation learning algorithm.The input parameters are ambient temperature and the uncontrolled natural factor of solar radiation.The output network contains a variable representing the adsorbent bed temperature.The values obtained from the network model were compared with the experimental data,and the prediction performance of the network model was examined using various performance parameters.The mean square error(MSE)and the statistical coefficient of determination(R2)values are excellent numerical criteria for evaluating the performance of a prediction tool.A well-trained neural network model produces small MSE and higher R2 values.In the current study,the adsorbent bed temperature results obtained from a neural network with a two neuron in hidden layer and the number of the tapped time-delays d=9 provided a reasonable degree of accuracy:MSE=1.0121 and R2=0.99864 and the index of agreement was 0.9988.This network model,based on a high-performance algorithm,provided reliable and high-precision results concerning the predictable temperature of the adsorbent bed.

Heat Recovery for Adsorption Refrigeration System via Pinch Technology

An adsorption refrigeration system can be driven by low grade heat and uses natural refrigerant with the advantage of reducing the greenhouse gases emission.However,one of the weaknesses is its low efficiency and more importantly its high cost.The recovery of internal waste heat becomes therefore very important in order to improve the coefficient of performance(COP).Analysis based on pinch technology can be helpful to optimal heat recovery operation.In this paper,temperature-heat diagrams and problem tables for adsorption refrigeration systems are proposed and analyzed using Pinch Technology.The results show that pinch point is located between beds and the main waste heat needs to be recovered between beds.Dynamic characteristic(time factor)of adsorption refrigeration system is the main resistance for heat recovery.The effect of pinch point temperature difference on the system COP is not distinct.Furthermore,when the driving temperature is 90°C,the COP of adsorption refrigeration via optimization of pinch analysis is 0.73 which is fairly comparable to Li Br-water absorption refrigeration system.Pinch Technology can be adopted in different types of adsorption refrigeration systems(two-bed,four-bed,mass recovery,et al.).

Integration of evacuated solar collectors with an adsorptive ice maker for hot climate region

This research study compares the steady-state and dynamic behaviour of a solar-powered activated carbon-35(AC35)/methanol-based vapour adsorption refrigeration system for production of ice at hot climate region.Ther-modynamic comparisons are made with the coefficient of performance(COP),system COP(SCOP),specific refrig-eration capacity(SRC)and critical parameters such as cycle time and ice production rate are quantified.Further,the sustainability of the proposed ice maker has proven by integrating economic and environmental perceptions.The minimum solar flux required to ensure continuous ice production was found 800 W/m^(2).Moreover,the max-imum ice production rate and COP were decreased by 32.36%and 37.63%respectively when the system was operated under real ambient conditions.The proposed solar adsorptive ice maker achieved maximum SRC of 61.6 g m^(−2)during April month and reduced the CO_(2)emissions by 12.82 ton annually.