Results in Journal Journal of Energy Systems: 61
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Journal of Energy Systems; doi:10.30521/jes.762506
Journal of Energy Systems; doi:10.30521/jes.775961
Heat loss/gain through the walls accounts for about 30% of the total building energy losses. Bricks are indispensable parts of buildings as a very common masonry wall unit, hence the present work aims at optimising thermal resistance of lightweight concrete hollow bricks through a CFD based numerical research. The optimisation is conducted over a certain number of independent variables such as hollow geometry and design, number of hollow rows across the heat transfer path and hollow depth for natural convection aspects within the hollow enclosure. A reliable CFD software ANSYS FLUENT 18.1 is utilised in the research. The accuracy of the CFD results is justified first through the reference model brick (RMB). Overall heat transfer coefficient (U-value) of RMB is determined to be 0.916 W/m2.K, which is in good accordance with the manufacturer’s data report (0.9 W/m2.K). Following this, parametric research is carried out for various scenarios to optimise the U-value as a function of brick mass. Based on the findings, the maximum improvement is found to be about 53% (U-value 0.43 W/m2.K) through the case of B48 which has an h-ratio of 1 (continuous hollow from top to bottom). Moreover, depending on the increase in h-ratio, it is achieved that the thermal performance of the bricks proportionally increases. The minimum weight of the brick design (B45) is found to be 7.645 kg and the corresponding U-value is obtained as 0.44 W/m2.K.
Journal of Energy Systems; doi:10.30521/jes.738363
The phase diagram of the Zn-Te binary system was recalculated using Thermo-Calc software 2019b and compared with the experimental and computational ones found in the literature. The obtained phase diagram shows five stable phases and six fields of two mixed phases, in agreement with published experimental results. The melting points of Zn, Te, and stoichiometic ZnTe were determined and compared with previous ones obtained by different authors. A monotectic reaction was found at monotectic temperature of 1479.14 K (1205.99 °C) and 59.369 Zn mole percent. A miscibility gap was found in the phase diagram between 59.369 and 97.2781 Zn mole percent above monotectic temperature. In addition, two eutectic reactions were observed at the Te and Zn terminals. Solubility of ZnTe in liquid Te and Zn was determined. These results are important for development of preparation methods of ZnTe the intermediate compound of this system, which is important for several industries including solar cells.
Journal of Energy Systems; doi:10.30521/jes.731845
A single phase 120V, 60Hz on board Electric Vehicle (EV) charging circuit configuration is considered with SMC for V2G discharging and G2V charging modes of operation. An on-board battery charger of rating 20 kWH which can be charged at home is presented. Bidirectional AC/DC and DC/DC converters are used for real power flow control. A nonlinear control technique Sliding Mode Controller (SMC) is used due to its robustness and good tracking capabilities. It is observed that 2nd order dc output voltage reduced by 57%, grid current THD is 3.289%, settling time is 0.1s and convergence are comparatively less than with a PR and PI controllers. The tracking of grid current is effective with very less steady state error of 1.52%. Both the modes of operation are obtained with a single stage conversion. During transitions, support to grid with reactive power by EV is simulated and understood. As an application, a solar based charging circuit is also presented for EV charging. The battery SOC (state of charge) depicts changeover state from normal charging to solar charging reaching 100% within short period. The results obtained are presented in PSCAD v4.6 software simulator.
Journal of Energy Systems, Volume 4, pp 58-70; doi:10.30521/jes.740587
The very high annual heat demand of greenhouses is the most critical factor that increases production costs. Conventional methods are generally used to obtain the optimum temperature required for greenhouses. In these systems, greenhouse air is heated by a boiler and pipe networks are connected to it, and in this way, most of the heat energy is transferred from the greenhouse ceiling to the atmosphere. In addition, in the greenhouse, not only the air but also the soil should be heated in order not to spoil the roots of the plants. The objective of this research is to provide sustainable heating for greenhouse applications. For this purpose, an innovative heating system has been designed for greenhouse heating by using of solar energy and heat pump technologies. In this study, a new approach was presented by designing a novelty heat pump flow for the heat required in the greenhouse. With this design, not only greenhouse air but also the soil will be heated and the best conditions for the development of plants will be provided. In the system, an ethylene glycol water mixture was used to prevent damage caused by freezing. In addition, it is designed to provide sustainability with an auxiliary heater when solar radiation is insufficient. It is highly recommended to apply this presented system for all greenhouse types.
Journal of Energy Systems, Volume 4, pp 32-47; doi:10.30521/jes.690997
Direct drive gearless axial flux permanent magnet synchronous generators (AFPMSG) are designed as multi-pole for use in vertical axis wind turbines. In particular, there are multi-pole core/coreless stator structures with axial flux for use in vertical axis wind turbines (WT) that can be designed in a compact structure at low wind speeds. In this study, the parametric simulation studies have been carried out according to rotor mechanical speeds with certain linear steps depending on different wind speed scenarios for an AFPMSG designed with 16-pole and cored stator for 5 kVA rated power with the finite element analysis (FEA) software. According to the analysis results obtained, the performance of the generator is reported and current, voltage, power losses and flux distribution are investigated. In addition, the DC bus voltage at the output of the DC-DC boost converter circuit due to wind speed changes is adaptively controlled for AFPMSG, which is co-simulated with the power electronics interface used at the generator output. Thus, both power electronics circuit performance and generator side have been simulated simultaneously with electromagnetic modeling. Therefore, the performance of the designed AFPMSG, which is modeled in three dimensions (3D) before the prototype stage, can be determined under more realistic conditions.
Journal of Energy Systems, Volume 4, pp 48-57; doi:10.30521/jes.724207
Nowadays the advancement of technology and equipment to monitor the operating performance of power transformer has achieved a high level. So, the monitoring system enables the continued investigation of the operational work of power transformer parameters as well as the prevention of failures and enhance reliability. However, the monitoring of power transformers is of unquestionable value for the electrical power systems and consumers to have more reliability in supplying. Therefore, given that monitoring involves a considerable number of parameters and elements of transformers, in the present case the overview of the monitoring of some of the most important parameters has been taken into account. Thus, the paper includes the monitoring parameters such as; partial discharges, oil and winding temperatures, bushing currents, tap changer, moisture and dissolved gas analysis. Also, in the paper are presented data for the operation of these parameters in different periods as well as with different loading regimes. The reports of events that correspond to the operational performance of the transformer, which are a good cause for diagnosis and preliminary actions in transformers, are also presented.
Journal of Energy Systems, Volume 4, pp 71-87; doi:10.30521/jes.727975
Model predictive control has been widely used in the industry. This can control the multivariable system with constraints on input and output variables but it needs online computation solver, and creates the non-convex solution in nonlinear plant due to the parameter uncertainties. The online computational problem and non-convex solution of the model predictive control are achieved via neural network model predictive control. The paper explores the speed control of permanent magnet synchronous motor (PMSM) by using neural network model predictive control (NNMPC) technique. The multi-layer artificial neural network is used to identify the dynamics of PMSM. The set point speed tracking control of PMSM is identified by using neural network model predictive control strategy. By using the set of input and output data obtained from the system, the multi input-output feed-forward neural network model is created. Levenberg-Marquardt algorithm is used to train the process models of the PMSM. That provides future plant output for control optimization of the predictive control. The overall system is developed and tested in the MATLAB/Simulink. To evaluate the efficiency of the controller proposed, it is compared with a constrained model predictive controller through the studies of simulation. The overshoot and settling time of the speed response of the PMSM are measured and analyzed for NNMPC and constrained MPC.
Journal of Energy Systems, Volume 4, pp 22-31; doi:10.30521/jes.703313
The effect of the cathode radius variation (from 11.5 cm to 17 cm) on neutron yield, discharge current, plasma temperature, and ion properties (velocity, energy, and density) are investigated in this study using the developed spherical plasma focus model and the results are reported in this paper. Peak discharge current and peak beam-ion properties decrease with increasing the cathode radius. Maximum plasma temperature (22.34 eV) and maximum beam-target neutron yield (1.18×1013) are achieved using the cathode with 15 cm radius. The longest pinch duration for all calculations is also achieved using 15 cm cathode radius. It is found that the optimum cathode radius is 15 cm in terms of the neutron yield, plasma temperature and beam-ion properties in spherical plasma focus device.
Journal of Energy Systems, Volume 4, pp 1-11; doi:10.30521/jes.635582
DC-DC converter circuits are topologies commonly used in power electronics applications such as renewable energy sources, electric vehicles, uninterruptible power supplies and DC transmission systems. The most important factors affecting efficiency and thus performance is the choice of the power semiconductor switching element as well as the circuit design and types of these topologies. In this context, power semiconductors are determined according to the switching frequency and current-voltage parameters. However, due to other operating modes of the circuit and load variation during the power conversion, the losses of the switching elements do not remain constant. In this study, a parametric simulation is performed in a conventional DC-DC boost converter circuit using the parameters related to the Insulated-Gate Bipolar Transistor (IGBT) power-switching element selected at a certain current-voltage capacity. These parameters are switching frequency, duty ratio and load change of the converter. Finally, using the data obtained, the loss of switching losses are estimated by the Multilayer Perceptron (MLP), Support Vector Machine (SVM), K- Nearest Neighbors (KNN) and Random Forest (RF) Machine Learning (ML) techniques.