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The power transformer is important equipment for energy conversion and transmission in the power grid and its failure will bring significant economic losses to the power system. The hot-spot temperature is a primary factor affecting the reliability and service life of power transformers. In order to calculate the temperature distribution of oil-immersed transformer windings accurately, it is required to solve a multi-physical problem, in which the magnetic field and the fluid-temperature field are coupled. In the simulation of multi-physical field of transformer, many studies usually omit the turn-to-turn insulation of windings to simplify the oil-immersed transformer model. The purpose of this paper is to investigate the effect of the turn-to-turn insulation of windings in oil-immersed transformers on the simulation results. First, a 2D axisymmetric transformer model was established in ANSYS to study the effect of low-voltage winding turn-to-turn insulation on the magnetic field simulation results. The differences of eddy current losses in the simulation were also calculated in terms of the magnetic field simulation results. It is found that the turn-to-turn insulation does not affect the magnetic field distribution in evidence from the simulation results. Besides, the values of the magnetic field and eddy current loss appear significant differences only at both ends of the low-voltage winding. Second, the fluid-temperature field of the transformer was solved in Fluent and the turn-to-turn insulation was the controlled objective in the solution process with consideration of the difference in winding losses. The simulation results show that the turn-to-turn insulation of the winding does not change the oil flow distribution in simulation. The simulation model with turn-to-turn insulation appears a gradient in the temperature distribution of the discs and a rise in the overall temperature distribution. Moreover, this paper analyzes the possible reasons for the differences in the simulation results of the magnetic and temperature fields caused by the turn-to-turn insulation. Some results and conclusions in this paper can be used in related studies and designs.

Dedicated fan-duct-heatsink combinations have become a standard means of cooling computer processors. Most previous studies have considered optimization of fin geometry (pitch and thickness) with overall heatsink dimensions (width, height, length) fixed. The present study considers size requirements for the constraints of fixed air volume flow rate and pressure drop, fixed fan/blower power, and fixed thermal conductance. First, an ideal heatsink with infinite fin thermal conductivity is considered, providing simple power-law prediction of performance. Next, fins of finite thermal conductivity and thickness, as well as effects of developing flow are included in the analysis, permitting prediction and minimization of weight. Models of both levels of complexity can be used, previous to more detailed numerical and/or experimental studies, to design optimized heatsinks.

Oil shale is a kind of potential alternative energy source for petroleum and has attracted the attention of energy researchers all over the world. Borehole hydraulic mining has more prominent advantages than both conventional open-pit mining and underground mining. It is very important to attempt to use the borehole hydraulic mining method to exploit underground oil shale. The nozzle is the key component of borehole hydraulic mining and reasonable mining parameters are also crucial in exploiting underground oil shale efficiently. The straight cone nozzle and the oil shale of Huadian area will be taken as the research objects. The self-developed, multifunctional, experimental device can test both the jet’s performance as well as the breaking of oil shale by the high-pressure water jet using the straight cone nozzle and varying structural parameters. Comprehensive analysis of the results of an orthogonal experimental design, including range analysis and variance analysis, demonstrate the optimal structural parameters of a straight cone nozzle as follows: the outlet diameter is 4 mm, the length to diameter ratio is 2.5, and the contraction angle is 60°. In addition, in order to maximize the efficiency of borehole hydraulic mining for Huadian oil shale, the non-submerged jet should be placed parallel to the oil shale bedding. These results can provide scientific and valuable references for borehole hydraulic mining of oil shale.

Abstract Methane dry reforming with CO2 using FeO powder in molten salt has been investigated at various flow rates of CH4/CO2 mixed gases (CH4/CO2=1) between 50 and 400 ml/min at 1223 K in an infrared furnace. This work is carried out to determine the usefulness of this method for the chemical storage of solar energy. The CH4/CO2 mixed gases passing through the molten salt (Na2CO3/K2CO3=1) containing the FeO powder were catalytically decomposed into CO, H2 and H2O. The product gas mole ratios, CO/H2/H2O, were shown to be 3:1:1 for a high flow rate of 200 ml/min and to be CO/H2=2:1 for a low flow rate of 50 ml/min. The results were explained in terms of the kinetics of the CH4-reforming reaction and the thermodynamics of the redox process of FeO powder mixed in the molten salt; CH 4 +2FeO⇒2Fe+H 2 +CO+H 2 O Fe+CO 2 ⇒FeO+CO for a high flow rate, and FeO+CH 4 ⇒Fe+2H 2 +CO Fe+CO 2 ⇒FeO+CO for a low flow rate.

Vehicle speed prediction plays a critical role in energy management strategy (EMS). Based on the adaptive particle swarm optimization–least squares support vector machine (APSO-LSSVM) algorithm with BP neural network (BPNN), a novel closed-loop vehicle speed prediction system is proposed. The database of a vehicle internet platform was adopted to construct a speed prediction model based on the APSO-LSSVM algorithm. Furthermore, a BPNN is established according to the local high-precision nonlinear fitting relationship between the predicted value and error so as to correct the prediction value. Then, the results are returned to the APSO-LSSVM model for calculating the minimum fitness function, thus obtaining a closed-loop prediction system. Finally, equivalent fuel consumption minimization strategy (ECMS) based EMS was performed. According to the simulation results, the RMSE performance is 0.831 km/h within 5 s, which is over 20% higher than other performances. Additionally, the training time is 15 min within 5 s, which is advantageous over BPNN. Furthermore, fuel consumption increases by 6.95% compared with the dynamic-programming algorithm and decreased by 5.6%~10.9% compared with the low accuracy of speed prediction. Overall, the proposed method is crucial for optimizing EMS as it is not only effective in improving prediction accuracy but also capable of reducing training time.

Abstract Integration of solar photovoltaic (PV) and battery storage systems is an upward trend for residential sector to achieve major targets like minimizing the electricity bill, grid dependency, emission and so forth. In recent years, there has been a rapid deployment of PV and battery installation in residential sector. In this regard, optimal planning of PV-battery systems is a critical issue for the designers, consumers, and network operators due to high number of parameters that can affect the optimization problem. This paper aims to present a comprehensive and critical review on the effective parameters in optimal planning process of solar PV and battery storage system for grid-connected residential sector. The key parameters in process of optimal planning for PV-battery system are recognized and explained. These parameters are economic and technical data, objective functions, energy management systems, design constraints, optimization algorithms, and electricity pricing programs. A timely review on the state-of-the-art studies in PV-battery optimal planning is presented. The challenges, trends and latest developments in the topic are discussed. At the end, scopes for future studies are developed. It is found that new guidelines should be provided for the customers based on various electricity rates and demand response programs. Also, several design considerations like grid dependency and resiliency need further investigation in the optimal planning of PV-battery systems.

In order to mitigate the power density shortage of current energy storage systems (ESSs) in pure electric vehicles (PEVs or EVs), a hybrid ESS (HESS), which consists of a battery and a supercapacitor, is considered in this research. Due to the use of the two ESSs, an energy management should be carried out for the HESS. An optimal energy management strategy is proposed based on the Pontryagin's minimum principle in this research, which instantaneously distributes the required propulsion power to the two ESSs during the vehicle's propulsion and also instantaneously allocates the regenerative braking energy to the two ESSs during the vehicle's braking. The objective of the proposed energy management strategy is to minimize the electricity usage of the EV and meanwhile to maximize the battery lifetime. A simulation study is conducted for the proposed energy management strategy and also for a rule-based energy management strategy. The simulation results show that the proposed strategy saves electricity compared to the rule-based strategy and the single ESS case for the three typical driving cycles studied in this research. Meantime, the proposed strategy has the effect of prolonging the battery lifetime compared to the other two cases.

Abstract Heat pipes have been extensively applied in the domain of energy conversion and heat recovery application. A novel radial heat pipe with internally finned condenser has been proposed to recover waste heat from air conditioning units. Full mathematical description and computational fluid dynamics model were developed to predict the loop flow and thermal performance in a single radial heat pipe, respectively. The research focuses mainly on the effects of input power, filling ratio, pipe diameter, and velocity of the cooling water on the thermal performance and entropy generation rate of this novel heat pipe. Numerical results illustrate that average reductions in total thermal resistance with utilization of fins approximately achieved 8.69% and 14.78% for fins nf = 4 and nf = 8, respectively. Similarly, entropy generation rate shows an average decrease of 19.4% and 37.5% for identical operations. Additionally, the effect of internally finned condenser on the multiphase fluid flow has been comprehensively analyzed, including the break of the condensed film, generation of bubbles and nucleation boiling. The results further indicate that incorporation of internal fins has a significant influence on enhancing thermal homogenization and waste thermal recovery efficiency of a radial heat pipe. Case results agreed well with experimental data within average deviation being no more than 10%.

Abstract The upward energy demand, along with the depletion of conventional energy sources, demands improved utilization of renewable energy resources. Among all renewable energy resources, solar energy is the most appropriate alternative to conventional energy sources owing to its inexhaustibility and green property. Solar collectors are devices that convert solar radiation into heat or energy. However, the efficiency of the solar collector is still not adequate. The competent step to enhance the efficiency of the solar collector is to use nanofluids. This study is carried out different phases viz. characterization and stabilization while both qualitative and quantitative methods used to evaluate the stability of nanofluids thermophysical properties of Al2O3 and CNC nanofluids such as thermal conductivity measured at four different temperature using KD2 Pro, viscosity and specific heat determined at similar temperature range by viscometer and differential scanning calorimetry respectively. The experiment is executed with a fixed flow rate and in steady-state conditions under extensive solar radiation. The experimental study has revealed that up to 2.48% and 8.46% efficiency of solar collector enhanced by using 0.5% Al2O3 and 0.5% CNC nanofluids respectively. Moreover, nanofluids show good to moderate stability performance. Besides, the thermal conductivity of nanofluids increased while viscosity is in a decreasing trend with increasing temperature. Nanofluids could enhance the efficiency of a flat-plate solar collector.