Open AccessArticle
Comparative Study of Shell and Helically-Coiled Tube Heat Exchangers with Various Dimple Arrangements in Condensers for Odor Control in a Pyrolysis System
Energies 2016, 9(12), 1027; doi:10.3390/en9121027 (registering DOI) -
Abstract
This study performed evaluations of the shell and helically-coiled tube heat exchangers with various dimple arrangements, that is, flat, inline, staggered, and bulged, at different Dean numbers (De) and inlet temperatures of a hot channel. Conjugated heat transfer was analyzed to
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This study performed evaluations of the shell and helically-coiled tube heat exchangers with various dimple arrangements, that is, flat, inline, staggered, and bulged, at different Dean numbers (De) and inlet temperatures of a hot channel. Conjugated heat transfer was analyzed to evaluate the heat transfer performance of the exchangers through temperature difference between the inlet and outlet, Nusselt number inside the coiled tube, and pressure drop of the coiled tube by using 3-D Reynolds-averaged Navier–Stokes (RANS) equations with shear stress transport turbulence closure. A grid dependency test was performed to determine the optimal number of the grid system. The numerical results were validated using the experimental data, and showed good agreement. The inline and staggered arrangements show the highest temperature differences through all De. The staggered arrangement shows the best heat transfer performance, whereas the inline arrangement shows the second highest performance with all ranges of De and the hot channel’s inlet temperature. The inline and staggered arrangements show the highest pressure drop among all inlet temperatures of the hot channel. Full article
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Open AccessArticle
Gas Hydrate Growth Kinetics: A Parametric Study
Energies 2016, 9(12), 1021; doi:10.3390/en9121021 (registering DOI) -
Abstract
Gas hydrate growth kinetics was studied at a pressure of 90 bars to investigate the effect of temperature, initial water content, stirring rate, and reactor size in stirred semi-batch autoclave reactors. The mixing energy during hydrate growth was estimated by logging the power
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Gas hydrate growth kinetics was studied at a pressure of 90 bars to investigate the effect of temperature, initial water content, stirring rate, and reactor size in stirred semi-batch autoclave reactors. The mixing energy during hydrate growth was estimated by logging the power consumed. The theoretical model by Garcia-Ochoa and Gomez for estimation of the mass transfer parameters in stirred tanks has been used to evaluate the dispersion parameters of the system. The mean bubble size, impeller power input per unit volume, and impeller Reynold’s number/tip velocity were used for analyzing observed trends from the gas hydrate growth data. The growth behavior was analyzed based on the gas consumption and the growth rate per unit initial water content. The results showed that the growth rate strongly depended on the flow pattern in the cell, the gas-liquid mass transfer characteristics, and the mixing efficiency from stirring. Scale-up effects indicate that maintaining the growth rate per unit volume of reactants upon scale-up with geometric similarity does not depend only on gas dispersion in the liquid phase but may rather be a function of the specific thermal conductance, and heat and mass transfer limitations created by the limit to the degree of the liquid phase dispersion is batched and semi-batched stirred tank reactors. Full article
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Open AccessArticle
Energy Optimization and Fuel Economy Investigation of a Series Hybrid Electric Vehicle Integrated with Diesel/RCCI Engines
Energies 2016, 9(12), 1020; doi:10.3390/en9121020 (registering DOI) -
Abstract
Among different types of low temperature combustion (LTC) regimes, eactively controlled compression ignition (RCCI) has received a lot of attention as a promising advanced combustion engine technology with high indicated thermal efficiency and low nitrogen oxides (NOx) and particulate matter
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Among different types of low temperature combustion (LTC) regimes, eactively controlled compression ignition (RCCI) has received a lot of attention as a promising advanced combustion engine technology with high indicated thermal efficiency and low nitrogen oxides (NOx) and particulate matter (PM) emissions. In this study, an RCCI engine for the purpose of fuel economy investigation is incorporated in series hybrid electric vehicle (SHEV) architecture, which allows the engine to run completely in the narrow RCCI mode for common driving cycles. Three different types of energy management control (EMC) strategies are designed and implemented to achieve the best fuel economy. The EMC strategies encompass rule-based control (RBC), offline, and online optimal controllers, including dynamic programing (DP) and model predictive control (MPC), respectively. The simulation results show a 13.1% to 14.2% fuel economy saving by using an RCCI engine over a modern spark ignition (SI) engine in SHEV for different driving cycles. This fuel economy saving is reduced to 3% in comparison with a modern compression ignition (CI) engine, while NOx emissions are significantly lower. Simulation results show that the RCCI engine offers more fuel economy improvement in more aggressive driving cycles (e.g., US06), compared to less aggressive driving cycles (e.g., UDDS). In addition, the MPC results show that sub-optimal fuel economy is achieved by predicting the vehicle speed profile for a time horizon of 70 s. Full article
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Open AccessArticle
Forecasting the State of Health of Electric Vehicle Batteries to Evaluate the Viability of Car Sharing Practices
Energies 2016, 9(12), 1025; doi:10.3390/en9121025 (registering DOI) -
Abstract
Car-sharing practices are introducing electric vehicles (EVs) into their fleet. However, the literature suggests that at this point shared EV systems are failing to reach satisfactory commercial viability. A potential reason for this is the effect of higher vehicle usage, which is characteristic
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Car-sharing practices are introducing electric vehicles (EVs) into their fleet. However, the literature suggests that at this point shared EV systems are failing to reach satisfactory commercial viability. A potential reason for this is the effect of higher vehicle usage, which is characteristic of car sharing, and the implications on the battery’s state of health (SoH). In this paper, we forecast the SoH of two identical EVs being used in different car-sharing practices. For this purpose, we use real life transaction data from charging stations and different EV sensors. The results indicate that insight into users’ driving and charging behavior can provide a valuable point of reference for car-sharing system designers. In particular, the forecasting results show that the moment when an EV battery reaches its theoretical end of life can differ in as much as a quarter of the time when vehicles are shared under different conditions. Full article
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Open AccessArticle
Research on a Household Dual Heat Source Heat Pump Water Heater with Preheater Based on ASPEN PLUS
Energies 2016, 9(12), 1026; doi:10.3390/en9121026 (registering DOI) -
Abstract
This article proposes a dual heat source heat pump bathroom unit with preheater which is feasible for a single family. The system effectively integrates the air source heat pump (ASHP) and wastewater source heat pump (WSHP) technologies, and incorporates a preheater to recover
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This article proposes a dual heat source heat pump bathroom unit with preheater which is feasible for a single family. The system effectively integrates the air source heat pump (ASHP) and wastewater source heat pump (WSHP) technologies, and incorporates a preheater to recover shower wastewater heat and thus improve the total coefficient of performance (COP) of the system, and it has no electric auxiliary heating device, which is favorable to improve the security of the system operation. The process simulation software ASPEN PLUS, widely used in the design and optimization of thermodynamic systems, was used to simulate various cases of system use and to analyze the impact of the preheater on the system. The average COP value of a system with preheater is 6.588 and without preheater it is 4.677. Based on the optimization and analysis, under the standard conditions of air at 25 °C, relative humidity of 70%, wastewater at 35 °C, wastewater flow rate of 0.07 kg/s, tap water at 15 °C, and condenser outlet water temperature at 50 °C, the theoretical COP of the system can reach 9.784 at an evaporating temperature of 14.96 °C, condensing temperature of 48.74 °C, and preheated water temperature of 27.19 °C. Full article
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Open AccessArticle
Inverse Aerodynamic Optimization Considering Impacts of Design Tip Speed Ratio for Variable-Speed Wind Turbines
Energies 2016, 9(12), 1023; doi:10.3390/en9121023 (registering DOI) -
Abstract
Because of the slow dynamic behavior of the large-inertia wind turbine rotor, variable-speed wind turbines (VSWTs) are actually unable to keep operating at the design tip speed ratio (TSR) during the maximum power point tracking (MPPT) process. Moreover, it has been pointed out
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Because of the slow dynamic behavior of the large-inertia wind turbine rotor, variable-speed wind turbines (VSWTs) are actually unable to keep operating at the design tip speed ratio (TSR) during the maximum power point tracking (MPPT) process. Moreover, it has been pointed out that although a larger design TSR can increase the maximum power coefficient, it also greatly prolongs the MPPT process of VSWTs. Consequently, turbines spend more time operating at the off-design TSRs and the wind energy capture efficiency is decreased. Therefore, in the inverse aerodynamic design of VSWTs, the static aerodynamic performance (i.e., the maximum power coefficient) and the dynamic process of MPPT should be comprehensively modeled for determining an appropriate design TSR. In this paper, based on the inverse design method, an aerodynamic optimization method for VSWTs, fully considering the impacts of the design TSR on the static and dynamic behavior of wind turbines is proposed. In this method, to achieve higher wind energy production, the design TSR, chord length and twist angle are jointly optimized, which is structurally different from the conventional separated design procedure. Finally, the effectiveness of the proposed method is validated by simulation results based on the Bladed software. Full article
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Open AccessArticle
Mitigation of the Impact of High Plug-in Electric Vehicle Penetration on Residential Distribution Grid Using Smart Charging Strategies
Energies 2016, 9(12), 1024; doi:10.3390/en9121024 (registering DOI) -
Abstract
Vehicle electrification presents a great opportunity to reduce transportation greenhouse gas emissions. The greater use of plug-in electric vehicles (PEVs), however, puts stress on local distribution networks. This paper presents an optimal PEV charging control method integrated with utility demand response (DR) signals
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Vehicle electrification presents a great opportunity to reduce transportation greenhouse gas emissions. The greater use of plug-in electric vehicles (PEVs), however, puts stress on local distribution networks. This paper presents an optimal PEV charging control method integrated with utility demand response (DR) signals to mitigate the impact of PEV charging to several aspects of a grid, including load surge, distribution accumulative voltage deviation, and transformer aging. To build a realistic PEV charging load model, the results of National Household Travel Survey (NHTS) have been analyzed and a stochastic PEV charging model has been defined based on survey results. The residential distribution grid contains 120 houses and is modeled in GridLAB-D. Co-simulation is performed using Matlab and GridLAB-D to enable the optimal control algorithm in Matlab to control PEV charging loads in the residential grid modeled in GridLAB-D. Simulation results demonstrate the effectiveness of the proposed optimal charging control method in mitigating the negative impacts of PEV charging on the residential grid. Full article
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Open AccessArticle
Numerical Investigation on the Effect of Cementing Properties on the Thermal and Mechanical Stability of Geothermal Wells
Energies 2016, 9(12), 1016; doi:10.3390/en9121016 -
Abstract
In this paper, a two-dimensional (2-D) Finite Element (FE) analysis of a geothermal well was performed with respect to five different cross-sections corresponding to the design specifications for the geothermal well that is currently constructed in Pohang, South Korea. Among the essential components
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In this paper, a two-dimensional (2-D) Finite Element (FE) analysis of a geothermal well was performed with respect to five different cross-sections corresponding to the design specifications for the geothermal well that is currently constructed in Pohang, South Korea. Among the essential components (such as ground formation, casing, and cementing) of a geothermal well, the thermal and mechanical stability of the cementing component was discussed based on a series of parametric studies with consideration of the thermal conductivity and Young’s modulus of the cementing component. With increasing number of casing layers, the cementing component experiences less stress concentration. In addition, the lower thermal conductivity of the cementing material is advantageous for effectively controlling radial displacement. Consequently, it should be noted in geothermal well cementing construction that long-term strength degradation of the cementing might cause the severe structural instability of an entire geothermal well. Full article
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Open AccessArticle
Forecasting Crude Oil Price Using EEMD and RVM with Adaptive PSO-Based Kernels
Energies 2016, 9(12), 1014; doi:10.3390/en9121014 -
Abstract
Crude oil, as one of the most important energy sources in the world, plays a crucial role in global economic events. An accurate prediction for crude oil price is an interesting and challenging task for enterprises, governments, investors, and researchers. To cope with
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Crude oil, as one of the most important energy sources in the world, plays a crucial role in global economic events. An accurate prediction for crude oil price is an interesting and challenging task for enterprises, governments, investors, and researchers. To cope with this issue, in this paper, we proposed a method integrating ensemble empirical mode decomposition (EEMD), adaptive particle swarm optimization (APSO), and relevance vector machine (RVM)—namely, EEMD-APSO-RVM—to predict crude oil price based on the “decomposition and ensemble” framework. Specifically, the raw time series of crude oil price were firstly decomposed into several intrinsic mode functions (IMFs) and one residue by EEMD. Then, RVM with combined kernels was applied to predict target value for the residue and each IMF individually. To improve the prediction performance of each component, an extended particle swarm optimization (PSO) was utilized to simultaneously optimize the weights and parameters of single kernels for the combined kernel of RVM. Finally, simple addition was used to aggregate all the predicted results of components into an ensemble result as the final result. Extensive experiments were conducted on the crude oil spot price of the West Texas Intermediate (WTI) to illustrate and evaluate the proposed method. The experimental results are superior to those by several state-of-the-art benchmark methods in terms of root mean squared error (RMSE), mean absolute percent error (MAPE), and directional statistic (Dstat), showing that the proposed EEMD-APSO-RVM is promising for forecasting crude oil price. Full article
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Open AccessArticle
Ensemble Learning Approach for Probabilistic Forecasting of Solar Power Generation
Energies 2016, 9(12), 1017; doi:10.3390/en9121017 -
Abstract
Probabilistic forecasting accounts for the uncertainty in prediction that arises from inaccurate input data due to measurement errors, as well as the inherent inaccuracy of a prediction model. Because of the variable nature of renewable power generation depending on weather conditions, probabilistic forecasting
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Probabilistic forecasting accounts for the uncertainty in prediction that arises from inaccurate input data due to measurement errors, as well as the inherent inaccuracy of a prediction model. Because of the variable nature of renewable power generation depending on weather conditions, probabilistic forecasting is well suited to it. For a grid-tied solar farm, it is increasingly important to forecast the solar power generation several hours ahead. In this study, we propose three different methods for ensemble probabilistic forecasting, derived from seven individual machine learning models, to generate 24-h ahead solar power forecasts. We have shown that while all of the individual machine learning models are more accurate than the traditional benchmark models, like autoregressive integrated moving average (ARIMA), the ensemble models offer even more accurate results than any individual machine learning model alone does. Furthermore, it is observed that running separate models on the data belonging to the same hour of the day vastly improves the accuracy of the results. Getting more accurate forecasts will help the stakeholders come up with better decisions in resource planning and control when large-scale solar farms are integrated into the power grid. Full article
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Open AccessArticle
Numerical Study of the Dynamic Response of Heat and Mass Transfer to Operation Mode Switching of a Unitized Regenerative Fuel Cell
Energies 2016, 9(12), 1015; doi:10.3390/en9121015 -
Abstract
Knowledge concerning the complicated changes of mass and heat transfer is desired to improve the performance and durability of unitized regenerative fuel cells (URFCs). In this study, a transient, non-isothermal, single-phase, and multi-physics mathematical model for a URFC based on the proton exchange
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Knowledge concerning the complicated changes of mass and heat transfer is desired to improve the performance and durability of unitized regenerative fuel cells (URFCs). In this study, a transient, non-isothermal, single-phase, and multi-physics mathematical model for a URFC based on the proton exchange membrane is generated to investigate transient responses in the process of operation mode switching from fuel cell (FC) to electrolysis cell (EC). Various heat generation mechanisms, including Joule heat, reaction heat, and the heat attributed to activation polarizations, have been considered in the transient model coupled with electrochemical reaction and mass transfer in porous electrodes. The polarization curves of the steady-state models are validated by experimental data in the literatures. Numerical results reveal that current density, gas mass fractions, and temperature suddenly change with the sudden change of operating voltage in the mode switching process. The response time of temperature is longer than that of current density and gas mass fractions. In both FC and EC modes, the cell temperature and gradient of gas mass fraction in the oxygen side are larger than that in the hydrogen side. The temperature difference of the entire cell is less than 1.5 K. The highest temperature appears at oxygen-side catalyst layer under the FC mode and at membrane under a more stable EC mode. The cell is exothermic all the time. These dynamic responses and phenomena have important implications for heat analysis and provide proven guidelines for the improvement of URFCs mode switching. Full article
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Open AccessArticle
Experimental Investigation of Crack Extension Patterns in Hydraulic Fracturing with Shale, Sandstone and Granite Cores
Energies 2016, 9(12), 1018; doi:10.3390/en9121018 -
Abstract
Hydraulic fracturing is an important method of reservoir stimulation in the exploitation of geothermal resources, and conventional and unconventional oil and gas resources. In this article, hydraulic fracturing experiments with shale, sandstone cores (from southern Sichuan Basin), and granite cores (from Inner Mongolia)
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Hydraulic fracturing is an important method of reservoir stimulation in the exploitation of geothermal resources, and conventional and unconventional oil and gas resources. In this article, hydraulic fracturing experiments with shale, sandstone cores (from southern Sichuan Basin), and granite cores (from Inner Mongolia) were conducted to investigate the different hydraulic fracture extension patterns in these three reservoir rocks. The different reactions between reservoir lithology and pump pressure can be reflected by the pump pressure monitoring curves of hydraulic fracture experiments. An X-ray computer tomography (CT) scanner was employed to obtain the spatial distribution of hydraulic fractures in fractured shale, sandstone, and granite cores. From the microscopic and macroscopic observation of hydraulic fractures, different extension patterns of the hydraulic fracture can be analyzed. In fractured sandstone, symmetrical hydraulic fracture morphology could be formed, while some micro cracks were also induced near the injection hole. Although the macroscopic cracks in fractured granite cores are barely observed by naked eye, the results of X-ray CT scanning obviously show the morphology of hydraulic fractures. It is indicated that the typical bedding planes well developed in shale formation play an important role in the propagation of hydraulic fractures in shale cores. The results also demonstrated that heterogeneity influenced the pathway of the hydraulic fracture in granite cores. Full article
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Open AccessArticle
American’s Energy Future: An Analysis of the Proposed Energy Policy Plans in Presidential Election
Energies 2016, 9(12), 1000; doi:10.3390/en9121000 -
Abstract
As the leader of the largest economy, President of the United States has substantive influence on addressing climate change problems. However, a presidential election is often dominated by issues other than energy problems. This paper focuses on the 2016 presidential election, and examines
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As the leader of the largest economy, President of the United States has substantive influence on addressing climate change problems. However, a presidential election is often dominated by issues other than energy problems. This paper focuses on the 2016 presidential election, and examines the energy plans proposed by the leading Democrat and Republican candidates. Our data from the Iowa caucus survey in January 2016 suggests that voters were more concerned about terrorism and economic issues than environmental issues. We then compare the Democratic and Republican candidate’s view of America’s energy future, and evaluate their proposed renewable energy targets. We find that the view on renewable energy is polarized between Democratic and Republican candidates, while candidates from both parties agree on the need for energy efficiency. Results from our ordinal least squares regression models suggests that Democratic candidates have moderate to ambitious goals for developing solar and other renewables. The Republican candidates favor fossil fuels and they choose not to provide any specific target for developing renewable energy. In addition, this trend of party polarization has grown more significant when compared with the past three presidential elections. Our observation suggests that energy policies need to be discussed more often regarding the diversification and decarbonization of the nation’s energy system. Full article
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Open AccessArticle
Experimental and Potential Analysis of a Single-Valve Expander for Waste Heat Recovery of a Gasoline Engine
Energies 2016, 9(12), 1001; doi:10.3390/en9121001 -
Abstract
In this paper, a Rankine cycle test system is established to recover exhaust energy from a 2.0 L gasoline engine. Experiments on the system’s performance are carried out under various working conditions. The experimental results indicate that the recovery power of the expander
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In this paper, a Rankine cycle test system is established to recover exhaust energy from a 2.0 L gasoline engine. Experiments on the system’s performance are carried out under various working conditions. The experimental results indicate that the recovery power of the expander is strongly related to the load and speed of the gasoline engine. It is found that when the output power of the gasoline engine is 39.8–76.6 kW, the net power of the expander is 1.8–2.97 kW, which is equivalent to 3.9%–4.9% of the engine power. The performance simulation shows that the mass flow rate, power output, and isentropic efficiency of the piston expander are directly determined by the intake valve timing. Selecting a suitable intake valve timing can optimize the performance of the expander. The simulation results show that a 1 kW increment in power can be obtained only by selecting an optimum intake open timing. The experimental results further verify that the single-valve piston expander, because of its small dimensions, simple structure, and high speed, is appropriate, and has great potential for energy recovery of gasoline engine exhaust and has good prospects for engineering applications. Full article
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Open AccessArticle
Augmented Nonlinear Controller for Maximum Power-Point Tracking with Artificial Neural Network in Grid-Connected Photovoltaic Systems
Energies 2016, 9(12), 1005; doi:10.3390/en9121005 -
Abstract
Photovoltaic (PV) systems have non-linear characteristics that generate maximum power at one particular operating point. Environmental factors such as irradiance and temperature variations greatly affect the maximum power point (MPP). Diverse offline and online techniques have been introduced for tracking the MPP. Here,
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Photovoltaic (PV) systems have non-linear characteristics that generate maximum power at one particular operating point. Environmental factors such as irradiance and temperature variations greatly affect the maximum power point (MPP). Diverse offline and online techniques have been introduced for tracking the MPP. Here, to track the MPP, an augmented-state feedback linearized (AFL) non-linear controller combined with an artificial neural network (ANN) is proposed. This approach linearizes the non-linear characteristics in PV systems and DC/DC converters, for tracking and optimizing the PV system operation. It also reduces the dependency of the designed controller on linearized models, to provide global stability. A complete model of the PV system is simulated. The existing maximum power-point tracking (MPPT) and DC/DC boost-converter controller techniques are compared with the proposed ANN method. Two case studies, which simulate realistic circumstances, are presented to demonstrate the effectiveness and superiority of the proposed method. The AFL with ANN controller can provide good dynamic operation, faster convergence speed, and fewer operating-point oscillations around the MPP. It also tracks the global maxima under different conditions, especially irradiance-mutating situations, more effectively than the conventional methods. Detailed mathematical models and a control approach for a three-phase grid-connected intelligent hybrid system are proposed using MATLAB/Simulink. Full article
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Open AccessArticle
Study of Unwanted Emissions in the CENELEC-A Band Generated by Distributed Energy Resources and Their Influence over Narrow Band Power Line Communications
Energies 2016, 9(12), 1007; doi:10.3390/en9121007 -
Abstract
Distributed Energy Resources might have a severe influence on Power Line Communications, as they can generate interfering signals and high frequency emissions or supraharmonics that may cause loss of metering and control data. In this paper, the influence of various energy resources on
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Distributed Energy Resources might have a severe influence on Power Line Communications, as they can generate interfering signals and high frequency emissions or supraharmonics that may cause loss of metering and control data. In this paper, the influence of various energy resources on Narrowband Power Line Communications is described and analyzed through several test measurements performed in a real microgrid. Accordingly, the paper describes the effects on smart metering communications through the Medium Access Control (MAC) layer analysis. Results show that the switching frequency of inverters and the presence of battery chargers are remarkable sources of disturbance in low voltage distribution networks. In this sense, the results presented can contribute to efforts towards standardization and normative of emissions at higher frequencies higher, such as CENELEC EN 50160 and IEC/TS 62749. Full article
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Open AccessArticle
A Hybrid Modular Multilevel Converter with Partial Embedded Energy Storage
Energies 2016, 9(12), 1012; doi:10.3390/en9121012 -
Abstract
Modular and cascaded multilevel converters provide a functional solution for the integration of energy storage systems (ESSs). This paper develops a hybrid multilevel converter based on the modular multilevel converter (MMC) that can be functionally extended with partial embedded ESS as a fraction
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Modular and cascaded multilevel converters provide a functional solution for the integration of energy storage systems (ESSs). This paper develops a hybrid multilevel converter based on the modular multilevel converter (MMC) that can be functionally extended with partial embedded ESS as a fraction of the overall converter power rating. The configuration, which can operate as a typical DC-AC converter, enables multi-directional power flow between the DC- and AC-side of the converter, as well as the embedded energy storage elements. The use of a three-phase flying-capacitor submodule eliminates the second-order harmonic oscillations present in modular cascaded multilevel converters. Current, voltage and power control are discussed in the paper while simulation results illustrate the operation of the hybrid MMC as a DC-AC converter in a typical inverter application and the additional functions and control of the embedded ESS. Full article
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Open AccessArticle
Development of Correlations for Windage Power Losses Modeling in an Axial Flux Permanent Magnet Synchronous Machine with Geometrical Features of the Magnets
Energies 2016, 9(12), 1009; doi:10.3390/en9121009 -
Abstract
In this paper, a set of correlations for the windage power losses in a 4 kW axial flux permanent magnet synchronous machine (AFPMSM) is presented. In order to have an efficient machine, it is necessary to optimize the total electromagnetic and mechanical losses.
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In this paper, a set of correlations for the windage power losses in a 4 kW axial flux permanent magnet synchronous machine (AFPMSM) is presented. In order to have an efficient machine, it is necessary to optimize the total electromagnetic and mechanical losses. Therefore, fast equations are needed to estimate the windage power losses of the machine. The geometry consists of an open rotor–stator with sixteen magnets at the periphery of the rotor with an annular opening in the entire disk. Air can flow in a channel being formed between the magnets and in a small gap region between the magnets and the stator surface. To construct the correlations, computational fluid dynamics (CFD) simulations through the frozen rotor (FR) method are performed at the practical ranges of the geometrical parameters, namely the gap size distance, the rotational speed of the rotor, the magnet thickness and the magnet angle. Thereafter, two categories of formulations are defined to make the windage losses dimensionless based on whether the losses are mainly due to the viscous forces or the pressure forces. At the end, the correlations can be achieved via curve fittings from the numerical data. The results reveal that the pressure forces are responsible for the windage losses for the side surfaces in the air-channel, whereas for the surfaces facing the stator surface in the gap, the viscous forces mainly contribute to the windage losses. Additionally, the results of the parametric study demonstrate that the overall windage losses in the machine escalate with an increase in either the rotational Reynolds number or the magnet thickness ratio. By contrast, the windage losses decrease once the magnet angle ratio enlarges. Moreover, it can be concluded that the proposed correlations are very useful tools in the design and optimizations of this type of electrical machine. Full article
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Open AccessArticle
Cost Analysis of Direct Methanol Fuel Cell Stacks for Mass Production
Energies 2016, 9(12), 1008; doi:10.3390/en9121008 -
Abstract
Fuel cells are very promising technologies for efficient electrical energy generation. The development of enhanced system components and new engineering solutions is fundamental for the large-scale deployment of these devices. Besides automotive and stationary applications, fuel cells can be widely used as auxiliary
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Fuel cells are very promising technologies for efficient electrical energy generation. The development of enhanced system components and new engineering solutions is fundamental for the large-scale deployment of these devices. Besides automotive and stationary applications, fuel cells can be widely used as auxiliary power units (APUs). The concept of a direct methanol fuel cell (DMFC) is based on the direct feed of a methanol solution to the fuel cell anode, thus simplifying safety, delivery, and fuel distribution issues typical of conventional hydrogen-fed polymer electrolyte fuel cells (PEMFCs). In order to evaluate the feasibility of concrete application of DMFC devices, a cost analysis study was carried out in the present work. A 200 W-prototype developed in the framework of a European Project (DURAMET) was selected as the model system. The DMFC stack had a modular structure allowing for a detailed evaluation of cost characteristics related to the specific components. A scale-down approach, focusing on the model device and projected to a mass production, was used. The data used in this analysis were obtained both from research laboratories and industry suppliers specialising in the manufacturing/production of specific stack components. This study demonstrates that mass production can give a concrete perspective for the large-scale diffusion of DMFCs as APUs. The results show that the cost derived for the DMFC stack is relatively close to that of competing technologies and that the introduction of innovative approaches can result in further cost savings. Full article
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Open AccessArticle
Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation
Energies 2016, 9(12), 1010; doi:10.3390/en9121010 -
Abstract
An energy storage system (ESS) in a power system facilitates tasks such as renewable integration, peak shaving, and the use of ancillary services. Among the various functions of an ESS, this study focused on frequency regulation (or secondary reserve). This paper presents an
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An energy storage system (ESS) in a power system facilitates tasks such as renewable integration, peak shaving, and the use of ancillary services. Among the various functions of an ESS, this study focused on frequency regulation (or secondary reserve). This paper presents an optimal scheduling algorithm for frequency regulation by an ESS. This algorithm determines the bidding capacity and base point of an ESS in each operational period to achieve the maximum profit within a stable state-of-charge (SOC) range. However, the charging/discharging efficiency of an ESS causes SOC errors whenever the ESS performs frequency regulation. With an increase in SOC errors, the ESS cannot respond to an automatic generation control (AGC) signal. This situation results in low ESS performance scores, and finally, the ESS is disqualified from performing frequency regulation. This paper also presents a real-time SOC management algorithm aimed at solving the SOC error problem in real-time operations. This algorithm compensates for SOC errors by changing the base point of the ESS. The optimal scheduling algorithm is implemented in MATLAB by using the particle swarm optimization (PSO) method. In addition, changes in the SOC when the ESS performs frequency regulation in a real-time operation are confirmed using the PSCAD/EMTDC tool. The simulation results show that the optimal scheduling algorithm manages the SOC more efficiently than a commonly employed planning method. In addition, the proposed real-time SOC management algorithm is confirmed to be capable of performing SOC recovery. Full article
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