No abstract

Negative environmental impact of fossil fuel consumption highlight the role of renewable energy sources and give them a unique opportunity to grow and improve. Among renewable energy sources solar energy attract more attention and many studies have focused on using solar energy for electricity generation. Here, in this study, solar energy technologies are reviewed to find out the best option for electricity generation. Using solar energy to generate electricity can be done either directly and indirectly. In the direct method, PV modules are utilized to convert solar irradiation into electricity. In the indirect method, thermal energy is harnessed employing concentrated solar power (CSP) plants such as Linear Fresnel collectors and parabolic trough collectors. In this paper, solar thermal technologies including soar trough collectors, linear Fresnel collectors, central tower systems, and solar parabolic dishes are comprehensively reviewed and barriers and opportunities are discussed. In addition, a comparison is made between solar thermal power plants and PV power generation plants. Based on published studies, PV‐based systems are more suitable for small‐scale power generation. They are also capable of generating more electricity in a specific area in comparison with CSP‐based systems. However, based on economic considerations, CSP plants are better in economic return.

No abstract

No abstract

No abstract

No abstract

Surging in energy demand makes it necessary to improve performance of plant equipment and optimize operation of thermal power plants. Inasmuch as thermal power plants depend on fossil fuels, their optimization can be challenging due to the environmental issues which must be considered. Nowadays, the vast majority of power plants are designed based on energetic performance obtained from first law of thermodynamic. In some cases, energy balance of a system is not appropriate tool to diagnose malfunctions of the system. Exergy analysis is a powerful method for determining the losses existing in a system. Since exergy analysis can evaluate quality of the energy, it enables designers to make intricate thermodynamic systems operates more efficiently. These days, power plant optimization based on economic criteria is a critical problem because of their complex structure. In this study, a comprehensive analysis including energy, exergy, economic (3‐E) analyses, and their applications related to various thermal power plants are reviewed and scrutinized.

In this paper, an artificial neural network is implemented for the sake of predicting the thermal conductivity ratio of TiO2-Al2O3/water nanofluid. TiO2-Al2O3/water in the role of an innovative type of nanofluid was synthesized by the sol–gel method. The results indicated that 1.5 vol.% of nanofluids enhanced the thermal conductivity by up to 25%. It was shown that the heat transfer coefficient was linearly augmented with increasing nanoparticle concentration, but its variation with temperature was nonlinear. It should be noted that the increase in concentration may cause the particles to agglomerate, and then the thermal conductivity is reduced. The increase in temperature also increases the thermal conductivity, due to an increase in the Brownian motion and collision of particles. In this research, for the sake of predicting the thermal conductivity of TiO2-Al2O3/water nanofluid based on volumetric concentration and temperature functions, an artificial neural network is implemented. In this way, for predicting thermal conductivity, SOM (self-organizing map) and BP-LM (Back Propagation-Levenberq-Marquardt) algorithms were used. Based on the results obtained, these algorithms can be considered as an exceptional tool for predicting thermal conductivity. Additionally, the correlation coefficient values were equal to 0.938 and 0.98 when implementing the SOM and BP-LM algorithms, respectively, which is highly acceptable.