Önder Kizilkan

Thermodynamic analysis of variable speed refrigeration system using artificial neural networks

This study presents thermodynamic performance modeling of an experimental refrigeration system driven by variable speed compressor using artificial neural networks (ANNs) with small data sets. Controlling the rotational speed of compressor with a frequency inverter is one of the best methods to vary the capacity of refrigeration system. For this aim, an experimental refrigeration system was designed with a frequency inverter mounted on compressor electric motor. The experiments were made for different compressor electric motor frequencies. Instead of several experiments, the use of ANNs had been proposed to determine the system performance parameters based on various compressor frequencies and cooling loads using results of experimental analysis. The backpropagation learning algorithm with two different variants was used in the network. In order to train the neural network, limited experimental measurements were used as training and test data. The best fitting training data set was obtained with eight neurons in the hidden layer. The results showed that the statistical error values of training were obviously within acceptable uncertainties. Also the predicted values were very close to actual values.

Solar Assisted Organic Rankine Cycle for Power Generation: A Comparative Analysis for Natural Working Fluids

In this study, a comparative thermodynamic analysis of a solar assisted organic Rankine cycle (ORC) is carried out for different natural working fluids. The required heat energy demand for ORC is supplied by solar energy by means of parabolic trough solar collectors (PTSCs). For the ORC system, eight different natural working fluids those are suitable for low temperature applications such as R170, R1270, R600, R600a, R717, R744, R218 and R161 are analyzed comparatively. Also the analyses are made for R134a in order to compare the system performances. The calculations are made according to the solar flux distribution in Turkey. For the results, the energy and exergy efficiencies and exergy destruction rates of the ORC system for different working natural fluids are compared in detail. From the results of energy and exergy analyses, the best fluid is found to be R744 with a power generation rate of 4.87 kW with an energy and exergy efficiencies of 8 % and 7.1 % respectively. Also it is found that R218 has the highest exergy destruction rate as 76.98 kW. Additionally, the effects of turbine inlet temperature, turbine inlet pressure and condensation temperature on system performance are parametrically analyzed.

Exergetic assessment of a rotary kiln for clinker production in cement industry

Cement industry is one of the most energy consuming sectors in the world. Through a cement plant, rotary kiln is the most energy intensive section that consumes the highest portion of the total energy, so it is getting very substantial to perform energy and exergy analyses for determining possible energy–saving options. In this study, thermodynamic assessment of the rotary kiln unit of a cement plant is carried. For the analysis, mass, energy and exergy balances of the rotary kiln are constituted and using actual plant data the performances of the rotary kiln are identified. The rotary kiln clinker capacity is 79 tons per hour. The energy and exergy efficiency of the unit is found to be 68% and 58.6%, respectively. At the end of the study, the results are compared with the other studies concerning with the same matter of different plants and available heat recovery possibilities are discussed.

Modelling of Wind Speed Using Artificial Neural Networks for University Campus of Burdur (Turkey)

In this study, wind energy potential of the campus of Mehmet Akif Ersoy University is analyzed by artificial neural networks (ANNs) with small data sets. For determining wind energy potential of the campus, a tower 63 m in height was built up. There were two anemometers for measuring of wind speed, at 30 m and 61 heights. Additionally, wind directions, pressure, temperature and humidity values were also measured with six different sensors. The energy required for the sensors mounted on the tower was supplied by 20 W photovoltaic panels. The measured data were modelled with ANNs to predict the long term wind parameters of the campus. Four different models were used for predicting the data with ANNs and a comparison of the models were done for determining the best one. The results showed that the statistical error values of training were obviously within acceptable uncertainties. Also the predicted values were very close to actual values.

Evaluation of Thermal Characteristics of a Borehole Thermal Energy Storage System

Energy storage technologies are usually a strategic and necessary component for the efficient utilization of renewable energy sources and energy conservation. Their use is important to overcome energetic and environmental issues. Thermal energy storage (TES) serves at least three different purposes: (1) energy conservation and substitution (by using natural energy sources and waste energy), (2) energy peak shifting (from more expensive daytime to less expensive nighttime rates), and (3) electricity conservation (by operating efficient devices at full load instead of part load to reduce peak power demands and increase efficiency of electricity use). Numerous TES systems have received attention for practical applications. Underground thermal energy storage systems may be divided into two groups: (1) closed storage systems, so-called borehole TES, in which a heat transport fluid (water in most cases) is pumped through heat exchangers in the ground and (2) open systems where groundwater is pumped out of the ground and then injected into the ground using wells (aquifer TES) or in underground caverns. In this study, the thermal resistance characteristics of borehole heat exchangers of borehole TES at University of Ontario Institute of Technology (UOIT) are investigated. In this regard, the ground thermal properties of Oshawa are studied, and a comparison of different methods for determining such thermal resistances is made for practical applications. Finally, a thermal response test mode for BTES is illustrated.