Majlesi Journal of Energy Management
Volume:3 Issue: 4, Dec 2014

This paper examines the laminar flow of Nanofluid heat transfer Water-Alumina with different nanoparticles diameters at the temperature of 293 ° K and a volume concentration of 1 to 5 percent in the space between the Square duct and Solid Tubes located in center. For this purpose equations governing to Nanofluid with the help of numerical finite volume method have been solved. The research findings in which has geometry of 0.0298 hydraulic diameter indicates using higher Nanofluid with volume concentration and less nanoparticles based on their diameters causes considerable increase in heat transfer coefficient and Nusslet Number.

In the last decades, the fossil fuel depletion has accelerated massively, leading to emit a huge volume of greenhouse gasses into the atmosphere daily and the earth temperature increase. New policies all around the world are devised to reduce the consumption of nonrenewable energy sources. Renewable sources of energy (RES), like wind and solar, are considered to provide future energy of the mankind activities. Future Smart Grid, which includes a lot of new technologies and standards, is the best matter to have RES vastly in utilization. Undeniably this extensive change of the electricity grid, requires sufficient research and investigation besides to excessive governmental investment. On the other side, the first steps for implementing a smart grid or employing RES should be practical and less expensive. As a result, household sector, and specifically buildings that are blamed for consuming about 40 percent of whole global energy seems to be a good point to start. In the next generation of buildings, the annual energy consumption is equal to generated on-site renewable energy and because of that, they are called Net-Zero Energy Building (NZEB). NZEB could be grid-connected or off-grid which suggests the best choice for electrifying remote isolate areas. In this paper, a review on new definitions and advances in the field of NZEB is presented.

Using the smart materials in building industry improves the conditions for buildings’’ users. Nano materials are smart materials that made advance changes in the optimization of building energy consumption by making nano coating that is discussed in the present paper. The aim of this study is to find the effects of nano coating in the optimization of building energy consumption in buildings. The method is library and Internet and sample survey. This research results is to achieve the features of nano coating in 90 % reduction of adverse effects of solar radiations, heat Resistant Waterproof Coating and reduction of energy waste in buildings.

In this paper, Hybridization of Simulated Annealing and Nelder-Mead (SANM) algorithm is proposed to solve optimal reactive power dispatch problem. The new-fangled algorithm (SANM) starts with a primary solution, which is generated arbitrarily and then the solution is alienated into partitions. The neighbourhood zone is generated, arbitrary number of partitions are selected and variables updating procedure is starting in order to generate a trail neighbour solutions. This process helps the SANM algorithm to explore the region around a current iterate solution. The Nelder- Mead algorithm is used in the final stage in order to progress the best solution found so far and accelerates the convergence in the final stage. The proposed SANM has been tested on standard IEEE 30 test system and simulation results show the better performance of the proposed algorithm in reducing the real power loss.

In this study,the laminar unsteady MHD (magneto hydro dynamic) flow over a stretchingrotating disk is investigated. A hybrid algorithm including artificial neuralnetwork (ANN) and artificial bee colony (ABC) for optimization of entropygeneration in this flow is applied. An ANN model is developed for predicting entropy generation.Approximately, 97 data sets obtained from the published literature, are appliedto develop the ANN model. In addition, the entropy generation is set as thefitness function for the ABC algorithm. Finally, results are compared withthese of evolutionary optimization algorithms, Particle Swarm Optimization(PSO). All the experiments of this paper have demonstrated that the optimalentropy is 8.41002 kJ/kg at Unsteadiness Parameter(S)=0, Magnetic Interaction Parameter (M) =0 and Reynolds number (Re)=5.

Power system stabilizers (PSS) has been widely used to enhance damping due to the electromechanical low frequency oscillations occurrence in power systems. In this paper, a new method is used for the online tuning of parameters of conventional power system stabilizers (CPSS) using fuzzy logic. Fuzzy logic enables mathematical modeling and computation of some nonlinear parameters of the system, which are usually derived empirically by utilization of expert knowledge rules. Various literatures has shown that fuzzy logic controller is one of the most useful methods for expert knowledge utilization. This type of controller is adaptive in nature and can be used successfully as a power system stabilizer. The design of fuzzy logic controllers is mainly based on fuzzy rules and input/output membership functions. Simple and efficient clustering algorithms allow data classification in distinct groups using distance and/or similarity functions. In the present paper, the optimum generation of fuzzy rules base using Fuzzy C-means (FCM) clustering technique is used. In fact, data are classified and the number of fuzzy rules which depends on convergence radius is determined. Finally, the performance of proposed FCM controller is compared with that of conventional controller. The active power, reactive power and bus voltages used as inputs to the fuzzy logic network based power system stabilizer and the parameters of the optimum stabilizer, i.e. gain factor as well as time constants of the lead/lag compensator, are the outputs of the proposed system. The design method has been successfully implemented on a single machine power system connected to an infinite bus over various operating conditions.

In the current contribution, attention is focused to experimentally measure the volumetric thermal expansion coefficient for several water-based nanofluids under different temperature conditions. For this purpose, Al2O3-water, CuO-water, TiO2-water, Al2O3-CuO-water, and Al2O3-TiO2-water nanofluids are analyzed and the corresponding results are compared with that of pure water. Water as well as the nanofluids with different nanoparticle fractions are heated gradually in the volumetric flask from 30°C to a maximum of about 80°C and their volume increases are recorded for each 10°C temperature rise. Thereafter, the volumetric thermal expansion coefficients are evaluated from the measured data. The results provide evidence that, addition of the nanoparticles to the base fluid leads to increase in the volumetric thermal expansion coefficient. In spite of that, it is found that presence of two different nanoparticles in the base fluid diminishes the nanofluid expansion.