Annual Energy Outlook 2008 With Projections to 2030

Thermal energy storage (TES) is a technology that stocks thermal energy by heating or cooling a storage medium so that the stored energy can be used at a later time for heating and cooling applications and power generation TES systems are used particularly in buildings and in industrial processes This paper is focused on TES technologies that provide a way of valorizing solar heat and reducing the energy demand of buildings The principles of several energy storage methods and calculation of storage capacities are described Sensible heat storage technologies, including water tank, underground, and packed-bed storage methods, are briefly reviewed Additionally, latent-heat storage systems associated with phase-change materials for use in solar heating/cooling of buildings, solar water heating, heat-pump systems, and concentrating solar power plants as well as thermo-chemical storage are discussed Finally, cool thermal energy storage is also briefly reviewed and outstanding information on the performance and costs of TES systems are included

A Comprehensive Review of Thermal Energy Storage

The use of solar energy in recent years has reached a remarkable edge. The continuous research for an alternative power source due to the perceived scarcity of fuel fossils is its driving force. It has become even more popular as the cost of fossil fuel continues to rise. The earth receives in just 1 h, more energy from the sun than what we consume in the whole world for 1 year. Its application was proven to be most economical, as most systems in individual uses requires but a few kilowatt of power. This paper reviews the present day solar thermal technologies. Performance analyses of existing designs (study), mathematical simulation (design) and fabrication of innovative designs with suggested improvements (development) have been discussed in this paper.

A review of solar thermal technologies

Review of utilization of genetic algorithms in heat transfer problems

This paper reviews on the possibilities of researches in the field of exergy analysis in various usable sectors where vapor compression refrigeration systems are used. Here, it is found that exergy depends on evaporating temperature, condensing temperature, sub-cooling and compressor pressure. It also depends on environmental temperature. Nowadays, hydrocarbons are considered as refrigerant having low ODP and GWP, and these are considerable in the aspect of exergy analysis. Refrigerants R 407a, R 600a, R 410a and R 134a are considered and analyzed with respect to exergy efficiency. Mixtures of hydrocarbons with R134a also show better performance with respect to other refrigerants. Among the components of the vapor compression system, much research showed that major part of exergy losses is occurred in the compressor. Nanofluid and nanolubricant cause to reduce the exergy losses in the compressor indirectly.

A review on exergy analysis of vapor compression refrigeration system

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.

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

The dry ice sublimation process of CO2 is a unique technique in which temperature ranges below the triple point of −56 °C can be achieved in a CO2 refrigeration system. However, during the evaporat...

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Experimental investigation of the effect of solid-gas two-phase flow in CO2 cascade refrigeration system

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.

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

Sizing of a solar and hydrogen-based integrated energy system of a stand-alone house in Izmir

The aim of this study is to carry out performance modeling of an experimental refrigeration system driven by variable speed compressor using Data Mining techniques with small data sets. In order to vary the capacity of the refrigeration systems, one of the best methods is controlling the rotational speed of the compressor motor with a frequency inverter. For this aim, an experimental refrigeration system is setup with a frequency inverter for controlling the speed of compressor electric motor. The experiments are made for 35 Hz to 50 Hz electric motor frequencies. Data mining technique is applied to determine the system performance parameters using actual data obtained from the measurements. From the results, it is observed that data mining procedure is suitable for forecasting the system characteristics for different compressor frequencies and cooling loads instead of making several experiments

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Onder Kizilkan

Papers

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

Experimental investigation of the effect of solid-gas two-phase flow in CO2 cascade refrigeration system

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

Sizing of a solar and hydrogen-based integrated energy system of a stand-alone house in Izmir

Data Mining Approach for Analysis of Variable Speed Refrigeration System