Journal of Energy Engineering

Factories are forced to pay for higher energy costs in the next decades because of increasing demand for energy and limited fuel resources. Efficient management of energy is among the greatest of challenges, especially for those energy-intensive manufacturing businesses. Research efforts have been continuously made to improve the efficiency in energy consumption, and methods and tools for energy efficiency management have been developed with respect to economics/cost and environment. This paper proposes a new energy-efficient management model by investigating energy consumption at tire manufacturing workstations. The model is then used to support efficacy and safety for manufacturing operations from the perspective of energy consumption. The proposed model is based on the statistical analysis of energy consumption in the rubber vulcanization process. The efficient energy usage is characterized by the ratio of energy flow into product manufacturing process. The energy flow ratio provides a quantitative measure for detecting system anomaly. A study case for tire vulcanization is presented to validate the proposed approach.

Supercapacitors are considered to be promising candidates for power devices in future generations. These devices are expected to find many future applications in hybrid electric vehicles and other power devices and systems. For supercapacitors to realize their promise, it is important that their energy and power densities be maximized. An important way to address this is to develop advanced electrode materials and methods to fabricate these materials. The recent years have seen enormous interest in the research of numerous materials and methods for their synthesis for applications in supercapacitor electrode technology. In the constantly changing technological landscape, it is relevant to review the various aspects of supercapacitor devices. This review paper gives an overview of the types of supercapacitors. It describes the advanced materials and fabrication methods for these devices, including recent developments in these areas, and their implications on the future of supercapacitor technology. The paper also addresses the principal technological challenges facing the development efforts in the future.

This paper proposes an interval stochastic semi-infinite programming (ICCSIP) method for identification of regional renewable and nonrenewable energy policies under multiple uncertainties. Relative to conventional methods (e.g., interval linear programming and chance-constrained programming), it has the advantages of addressing the association of system cost with nonrenewable energy price, generating reliable solutions with a low risk of system failure, and providing flexible capital availability that varies with respect to nonrenewable energy price. A case study is used to illustrate the performance of ICCSIP with respect to two scenarios. Scenario 1 neglects control of air pollutant emissions and scenario 2 attempts to address it. Nonrenewable energy sources would be primarily used under scenario 1; in particular, coal would play the most important role with respect to optimum energy supply schemes. Under scenario 2, hydrological and wind energy would be the first and second choices, respectively, in terms of electricity generation. Moreover, air pollutant emissions under scenario 2 would be dramatically less than scenario 1; however, an increased system cost would be required for control of air pollutant emissions.

Various control methods for reducing nitrogen oxides (${\mathrm{NO}}_{\mathrm{x}}$) emissions of diesel engines have been developed to conform to strict emission regulations. One of the methods for controlling ${\mathrm{NO}}_{\mathrm{x}}$ emissions is to use emulsified fuel. This study investigates the effects of emulsified fuels on the diesel engine performance and main pollutant emission characteristics. Four different emulsified water–diesel fuel mixtures (0, 5, 10, 15, and 20% by mass) were used in the engine tests. The tests were conducted in a single-cylinder naturally aspirated direct injection (DI) four-stroke diesel engine under full load conditions. It has been observed that while brake power and torque slightly decrease, the brake efficiency considerably increases. ${\mathrm{NO}}_{\mathrm{x}}$ emissions have decreased with the increase in the mass rate of water in the mixtures. Optimum water rate in the mixture was found to be 20%. The maximum increase in brake efficiency was 17.5% at 1,200 rotations per minute (rpm) with E20 (emulsified fuel with 20% water content). Maximum improvements of 22, 27, and 40% were achieved in specific fuel consumption (SFC), ${\mathrm{NO}}_{\mathrm{x}}$, and smoke emissions, respectively, at 2,400 rpm.

Kalina power plants have an efficient system of heat recovery compared with a single-fluid system because of a better temperature match between hot and cold fluids. The high-temperature regenerator (HTRGN), economizer, and evaporators are serially connected in a regular low-temperature Kalina power system. A higher amount of vapor from the generator followed by a separator gives high power output by a turbine. But with this condition, low heat recovery in HTRGN results in low thermal efficiency with the serial connected heat exchangers. It can be solved by sharing the heat load between HTRGN and a boiler (economizer plus partial evaporator) based on available heat with parallel arrangement in place of serial. It also facilitates the flexible operation of heaters with the heat source conditions. The current work has been focused on the comparison of these two heat recovery configurations with energy and exergy criteria to select a best layout. The influence of vapor fraction, separator temperature, turbine concentration, and solar beam radiation on performance of the plant has been studied. The key parameters are optimized to get a high performance with minimized collector’s cost. The results show that at high vapor fraction, the parallel arrangement results in higher improvement. The total variations in plant energy efficiency, cycle energy efficiency, and cycle exergy efficiency are 0–2%, 0–5%, and 0–12%, respectively, with the parallel arrangement of heaters at variable operational conditions.

This works aims to develop and study a new reaction microhydro tubular propeller turbine with five blades as a promising answer to solve the lack of energy in rural and remote areas. The first stage is to validate numerical and experimental tests made for the flow behavior for different values of head, discharge, and rotational impeller speed. Using specific mathematical formulations, a blade model configuration is developed based on the velocity triangles at the impeller inlet and outlet and experimental results based on pressure, discharge, and velocity profiles in different turbine sections. Through characteristic parameters, performance curves are obtained allowing comparisons between experimental and computational fluid dynamics (CFD) results. Also, an evaluation of the hydrodynamic behavior is made for a scaled model application by similarity turbo machines theory.

In this paper, models for short-term prediction of influent flow rate in a wastewater-treatment plant are discussed. The prediction horizon of the model is up to 180 min. The influent flow rate, rainfall rate, and radar reflectivity data are used to build the prediction model by different data-mining algorithms. The multilayer perceptron neural network algorithm has been selected to build the prediction models for different time horizons. The computational results show that the prediction model performs well for horizons up to 150 min. Both the peak values and the trends are accurately predicted by the model. There is a small lag between the predicted and observed influent flow rate for horizons exceeding 30 min. The lag becomes larger with the increase of the prediction horizon.

The writers have studied peristaltic flow of a hyperbolic tangent fluid in a diverging tube. The flow was investigated in a wave frame of reference moving with the velocity of the wave. The governing equations of hyperbolic tangent fluid in cylindrical coordinates were modeled. Heat and mass transfer phenomena were taken into consideration. The resulting nonlinear momentum, energy, and mass equations were simplified using long wavelength and low Reynolds number approximations. The resulting problem was solved using two analytical techniques, a regular perturbation method in terms of a variant of the Weissenberg number, and a homotopy analysis method. A graphical comparison of both of the solutions is presented for velocity, temperature, and concentration profiles. The expressions for axial velocity, temperature, mass concentration, heat and mass transfer coefficients, and axial pressure gradient were obtained, and the effects of various emerging parameters on these flow characteristics are illustrated graphically. The writers graphically demonstrate the numerical results for the pressure rise and frictional force for different waveforms (sinusoidal, multi-sinusoidal, triangular, square, and trapezoidal). Trapping phenomena were taken into consideration when plotting the streamlines pattern.

Voltage sag is one of the major power quality (PQ) problems, and has been the focus of PQ studies due to the impact on sensitive industrial loads and costs led by the damages and maintenance. Voltage sag source location is significant for the customers and suppliers to solve the issue between them, as well as for possible mitigation. Five main methods (the disturbance power and energy method, the slope of system trajectory method, the real current component method, the resistance sign–based method, and the distance relay method) are reviewed first. However, these methods used single criteria, and their effect is limited as the literature shows. This paper presents a pattern recognition way to locate the source of voltage sag. In the proposed method, features for pattern recognition are extracted first, based on these five methods. Then, the thought of source location by pattern classification is discussed with three steps in detail, and support vector machine (SVM) is applied in the case. The nonlinear binary classifier with optimal hyperplane is established to classify the sag source from upstream or downstream by SVM learning. To illustrate the effectiveness of the proposed method, a 110-kV distribution system is tested under simulation conditions, and records from PQ monitors installed in 35-kV substations are used.