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Energies, Volume 11, Issue 2 (February 2018)

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Cover Story (view full-size image) Axial turbocharger turbines have, in recent years, become viable alternatives to radial turbines [...] Read more.
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Open AccessArticle Estimation of the Diesel Particulate Filter Soot Load Based on an Equivalent Circuit Model
Energies 2018, 11(2), 472; https://doi.org/10.3390/en11020472
Received: 31 January 2018 / Revised: 16 February 2018 / Accepted: 21 February 2018 / Published: 23 February 2018
Cited by 1 | PDF Full-text (1967 KB) | HTML Full-text | XML Full-text
Abstract
In order to estimate the diesel particulate filter (DPF) soot load and improve the accuracy of regeneration timing, a novel method based on an equivalent circuit model is proposed based on the electric-fluid analogy. This proposed method can reduce the impact of the
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In order to estimate the diesel particulate filter (DPF) soot load and improve the accuracy of regeneration timing, a novel method based on an equivalent circuit model is proposed based on the electric-fluid analogy. This proposed method can reduce the impact of the engine transient operation on the soot load, accurately calculate the flow resistance, and improve the estimation accuracy of the soot load. Firstly, the least square method is used to identify the flow resistance based on the World Harmonized Transient Cycle (WHTC) test data, and the relationship between flow resistance, exhaust temperature and soot load is established. Secondly, the online estimation of the soot load is achieved by using the dual extended Kalman filter (DEKF). The results show that this method has good convergence and robustness with the maximal absolute error of 0.2 g/L at regeneration timing, which can meet engineering requirements. Additionally, this method can estimate the soot load under engine transient operating conditions and avoids a large number of experimental tests, extensive calibration and the analysis of complex chemical reactions required in traditional methods. Full article
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Open AccessArticle Analysis of dc-Link Voltage Switching Ripple in Three-Phase PWM Inverters
Energies 2018, 11(2), 471; https://doi.org/10.3390/en11020471
Received: 6 February 2018 / Revised: 19 February 2018 / Accepted: 21 February 2018 / Published: 23 February 2018
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Abstract
The three-phase voltage source inverter (VSI) is de facto standard in power conversion systems. To realize high power density systems, one of the items to be correctly addressed is the design and selection of the dc-link capacitor in relation to the voltage switching
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The three-phase voltage source inverter (VSI) is de facto standard in power conversion systems. To realize high power density systems, one of the items to be correctly addressed is the design and selection of the dc-link capacitor in relation to the voltage switching ripple. In this paper, effective formulas for designing the dc-link capacitor as a function of the switching voltage ripple amplitude are obtained, considering the operating conditions such as the modulation index and the output current amplitude. The calculations are obtained considering the requirements and restrictions referring to the high (switching)-frequency dc-link voltage ripple component. Analyses have been performed considering the dc source impedance (non-ideal dc voltage source at the switching frequency) and a balanced load. Analytical expressions are derived for the dc-link voltage switching ripple amplitude and its maximum value over the fundamental period. Different values of modulation index and output phase angle have been considered and different diagrams are presented. Analytical results were validated both by simulations and comprehensive experimental tests. Full article
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Open AccessArticle Analysis of Switching Transients during Energization in Large Offshore Wind Farms
Energies 2018, 11(2), 470; https://doi.org/10.3390/en11020470
Received: 24 January 2018 / Revised: 13 February 2018 / Accepted: 19 February 2018 / Published: 23 February 2018
Cited by 1 | PDF Full-text (4323 KB) | HTML Full-text | XML Full-text
Abstract
In order to study switching transients in an offshore wind farm (OWF) collector system, we employ modeling methods of the main components in OWFs, including vacuum circuit breakers (VCBs), submarine cables, and wind turbine transformers (WTTs). In particular, a high frequency (HF) VCB
[...] Read more.
In order to study switching transients in an offshore wind farm (OWF) collector system, we employ modeling methods of the main components in OWFs, including vacuum circuit breakers (VCBs), submarine cables, and wind turbine transformers (WTTs). In particular, a high frequency (HF) VCB model that reflects the prestrike characteristics of VCBs was developed. Moreover, a simplified experimental system of an OWF electric collection system was set up to verify the developed models, and a typical OWF medium voltage (MV) cable collection system was built in PSCAD/EMTDC based on the developed models. Finally, we investigated the influences of both the initial closing phase angle of VCBs and typical system operation scenarios on the amplitude and steepness of transient overvoltages (TOVs) at the high-voltage side of WTTs. Full article
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Open AccessArticle A PSO-Optimized Fuzzy Logic Control-Based Charging Method for Individual Household Battery Storage Systems within a Community
Energies 2018, 11(2), 469; https://doi.org/10.3390/en11020469
Received: 24 January 2018 / Revised: 13 February 2018 / Accepted: 16 February 2018 / Published: 23 February 2018
Cited by 1 | PDF Full-text (7150 KB) | HTML Full-text | XML Full-text
Abstract
Self-consumption of household photovoltaic (PV) storage systems has become profitable for residential owners under the trends of limited feed-in power and decreasing PV feed-in tariffs. For individual PV-storage systems, the challenge mainly lies in managing surplus generation of battery and grid power flow,
[...] Read more.
Self-consumption of household photovoltaic (PV) storage systems has become profitable for residential owners under the trends of limited feed-in power and decreasing PV feed-in tariffs. For individual PV-storage systems, the challenge mainly lies in managing surplus generation of battery and grid power flow, ideally without relying on error-prone forecasts for both generation and consumption. Considering the large variation in power profiles of different houses in a neighborhood, the strategy is also supposed to be beneficial and applicable for the entire community. In this study, an adaptable battery charging control strategy is designed in order to obtain minimum costs for houses without any meteorological or load forecasts. Based on fuzzy logic control (FLC), battery state-of-charge (SOC) and the variation of SOC (∆SOC) are taken as input variables to dynamically determine output charging power with minimum costs. The proposed FLC-based algorithm benefits from the charging battery as much as possible during the daytime, and meanwhile properly preserves the capacity at midday when there is high possibility of curtailment loss. In addition, due to distinct power profiles in each individual house, input membership functions of FLC are improved by particle swarm optimization (PSO) to achieve better overall performance. A neighborhood with 74 houses in Germany is set up as a scenario for comparison to prior studies. Without forecasts of generation and consumption power, the proposed method leads to minimum costs in 98.6% of houses in the community, and attains the lowest average expenses for a single house each year. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle Multi-Rate and Parallel Electromagnetic Transient Simulation Considering Nonlinear Characteristics of a Power System
Energies 2018, 11(2), 468; https://doi.org/10.3390/en11020468
Received: 27 November 2017 / Revised: 24 January 2018 / Accepted: 31 January 2018 / Published: 23 February 2018
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Abstract
The electromagnetic transient simulation of a power system with nonlinear characteristics is very time-consuming due to numerous inversion calculations of the admittance matrix. To speed up the simulation of the power system with nonlinear characteristics, a multi-rate and parallel electromagnetic transient simulation method
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The electromagnetic transient simulation of a power system with nonlinear characteristics is very time-consuming due to numerous inversion calculations of the admittance matrix. To speed up the simulation of the power system with nonlinear characteristics, a multi-rate and parallel electromagnetic transient simulation method is proposed. Firstly, a Multi-Area Thevenin Equivalents (MATE)-based parallel algorithm considering nonlinear characteristics of the power system is proposed. This method guarantees the admittance matrix is constant by considering changing branches as link current without dividing the subnet again. Secondly, considering the differences of the time constant of the AC/DC subnet, different simulation steps are used for these subnets. The Lagrange interpolation method is used for calculating the Thevenin voltage of the AC subnet in non-synchronous time. Calculation methods of the DC subnet Thevenin voltage is proposed by considering the simulation results during the entire large simulation step. Finally, the simulation process is optimized for improving the simulation efficiency further. The simulation results show that the proposed method could greatly improve the simulation efficiency without losing simulation accuracy too much compared with the traditional method. Full article
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Open AccessArticle Experimental Determination of Gas Relative Permeability Considering Slippage Effect in a Tight Formation
Energies 2018, 11(2), 467; https://doi.org/10.3390/en11020467
Received: 1 February 2018 / Revised: 17 February 2018 / Accepted: 19 February 2018 / Published: 23 February 2018
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Abstract
In this paper, the gas relative permeability considering slippage effect has been experimentally examined under various experimental conditions (i.e., ambient, high confining pressure, and high temperature). Experimentally, Klinkenberg permeabilities of 12 core samples have been measured by using steady-state flow experiment. It has
[...] Read more.
In this paper, the gas relative permeability considering slippage effect has been experimentally examined under various experimental conditions (i.e., ambient, high confining pressure, and high temperature). Experimentally, Klinkenberg permeabilities of 12 core samples have been measured by using steady-state flow experiment. It has been found that the Klinkenberg permeability is independent of the experimental temperature and dramatically decreases as confining pressure is increasing. Furthermore, linear correlations have been newly developed between the Klinkenberg permeability and the gas-measured permeability under various conditions. Subsequently, the developed correlations are correspondingly applied to calibrate the gas relative permeability. It has been found that the gas relative permeability can be overestimated without consideration of the slippage effect, i.e., Klinkenberg effect. In addition, the newly developed correlations have been applied to analyze the sensitivity of gas–water relative permeability to gas-measured permeability, confining pressure, and temperature. It is demonstrated that mobile water greatly alleviates the gas relative permeability in comparison to irreducible water. Although an increased confining pressure simultaneously reduces the effective water phase and gas phase permeability, the gas relative permeability increases and the water relative permeability decreases as the confining pressure increases. It is attributed to the fact that the effective water phase permeability is more sensitive to the confining pressure. Given an elevated experimental temperature, the gas relative permeability is reduced while the water relative permeability is enhanced, implying the significance of temperature effect on gas–water relative permeability measurements. Full article
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Open AccessArticle Composite Reliability Evaluation of Load Demand Side Management and Dynamic Thermal Rating Systems
Energies 2018, 11(2), 466; https://doi.org/10.3390/en11020466
Received: 23 January 2018 / Revised: 9 February 2018 / Accepted: 9 February 2018 / Published: 23 February 2018
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Abstract
Electric power utilities across the globe are facing higher demand for electricity than ever before, while juggling to balance environmental conservation with transmission corridor expansions. Demand side management (DSM) and dynamic thermal rating systems (DTR) play an important role in alleviating some of
[...] Read more.
Electric power utilities across the globe are facing higher demand for electricity than ever before, while juggling to balance environmental conservation with transmission corridor expansions. Demand side management (DSM) and dynamic thermal rating systems (DTR) play an important role in alleviating some of the challenges faced by electric power utilities. In this paper, various DSM measures are explored and their interactions with the application of the DTR system in the transmission network are examined. The proposed modelling of DSM in this paper implements load shifting on load demand curves from the system, bus and load sector levels. The correlation effects of line ratings are considered in the DTR system modelling as the weather that influences line ratings is also correlated. The modelling of the line ratings was performed using the time series method, the auto regressive moving average (ARMA) model. Both the DSM and the DTR systems were implemented on the modified IEEE reliability test network. The modification was achieved by developing a load model starting from the perspective of the load sectors at each bus and a new collective hourly load curve for the system was obtained by combining the loads at all buses. Finally, the results in this paper elucidate the interaction of DSM and DTR systems. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle PV Hosting Capacity Dependence on Harmonic Voltage Distortion in Low-Voltage Grids: Model Validation with Experimental Data
Energies 2018, 11(2), 465; https://doi.org/10.3390/en11020465
Received: 29 January 2018 / Revised: 15 February 2018 / Accepted: 19 February 2018 / Published: 23 February 2018
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Abstract
This paper introduces a brief analysis on hosting capacity and related concepts as applied to distribution network systems. Furthermore, it addresses the applicability of hosting capacity study methodologies to harmonic voltage distortion caused by photovoltaic panels (PV) connected at a low-voltage (LV) side
[...] Read more.
This paper introduces a brief analysis on hosting capacity and related concepts as applied to distribution network systems. Furthermore, it addresses the applicability of hosting capacity study methodologies to harmonic voltage distortion caused by photovoltaic panels (PV) connected at a low-voltage (LV) side of a university campus grid. The analysis of the penetration of new distributed generation technologies, such as PV panels, in the distribution grid of the campus was carried out via measurement processes, and later by computer simulations analyzing a new concept of the hosting capacity approach in relation to voltage harmonics distortion. The voltage rise due to harmonic injection is analyzed and discussed with the aim of validating the discussed model and also putting forward recommendations for connecting PV generation across other network systems. Full article
(This article belongs to the Special Issue Distributed and Renewable Power Generation)
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Open AccessArticle Modulation Strategy of a 3 × 5 Modular Multilevel Matrix Converter
Energies 2018, 11(2), 464; https://doi.org/10.3390/en11020464
Received: 2 January 2018 / Revised: 8 February 2018 / Accepted: 9 February 2018 / Published: 23 February 2018
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Abstract
In this paper, a modulation strategy of a 3 × 5 modular multilevel matrix converter (M3C) is proposed. The circuit of 3 × 5 M3C is firstly introduced. Then, operation rules of 3 × 5 M3C are illustrated, and a connection pattern of
[...] Read more.
In this paper, a modulation strategy of a 3 × 5 modular multilevel matrix converter (M3C) is proposed. The circuit of 3 × 5 M3C is firstly introduced. Then, operation rules of 3 × 5 M3C are illustrated, and a connection pattern of branches is determined based on these rules. Different voltage states in the input and output side can be achieved by different connection patterns. These voltage states are represented in the form of vector. It is hard to synthesize five-phase output with the three-level synthesis method. Therefore, the five-level synthesis method is adopted in this paper; i.e., is the branch states have been increased. Ten effective vectors and a zero vector are selected based on the five-level synthesis method. With this modulation strategy, we achieve output line-to-line voltages that are in line with the trend of a sine wave. The segment division and duty cycle calculation are very simple, and the modulation strategy can be implemented easily. The simulation model of 3 × 5 M3C is constructed based on Matlab/Simulink, and the corresponding experimental platform is set up. The results of simulation and experiment show that the proposed method is reasonable and correct. Full article
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Open AccessArticle A Comprehensive Energy Analysis and Related Carbon Footprint of Dairy Farms, Part 2: Investigation and Modeling of Indirect Energy Requirements
Energies 2018, 11(2), 463; https://doi.org/10.3390/en11020463
Received: 22 December 2017 / Revised: 8 February 2018 / Accepted: 13 February 2018 / Published: 22 February 2018
Cited by 1 | PDF Full-text (1508 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Dairy cattle farms are continuously developing more intensive systems of management, which require higher utilization of durable and non-durable inputs. These inputs are responsible for significant direct and indirect fossil energy requirements, which are related to remarkable emissions of CO2. This
[...] Read more.
Dairy cattle farms are continuously developing more intensive systems of management, which require higher utilization of durable and non-durable inputs. These inputs are responsible for significant direct and indirect fossil energy requirements, which are related to remarkable emissions of CO2. This study focused on investigating the indirect energy requirements of 285 conventional dairy farms and the related carbon footprint. A detailed analysis of the indirect energy inputs related to farm buildings, machinery and agricultural inputs was carried out. A partial life cycle assessment approach was carried out to evaluate indirect energy inputs and the carbon footprint of farms over a period of one harvest year. The investigation highlights the importance and the weight related to the use of agricultural inputs, which represent more than 80% of the total indirect energy requirements. Moreover, the analyses carried out underline that the assumption of similarity in terms of requirements of indirect energy and related carbon emissions among dairy farms is incorrect especially when observing different farm sizes and milk production levels. Moreover, a mathematical model to estimate the indirect energy requirements of dairy farms has been developed in order to provide an instrument allowing researchers to assess the energy incorporated into farm machinery, agricultural inputs and buildings. Combining the results of this two-part series, the total energy demand (expressed in GJ per farm) results in being mostly due to agricultural inputs and fuel consumption, which have the largest share of the annual requirements for each milk yield class. Direct and indirect energy requirements increased, going from small sized farms to larger ones, from 1302–5109 GJ·y−1, respectively. However, the related carbon dioxide emissions expressed per 100 kg of milk showed a negative trend going from class <5000 to >9000 kg of milk yield, where larger farms were able to emit 48% less carbon dioxide than small herd size farm (43 vs. 82 kg CO2-eq per 100 kg Fat- and Protein-Corrected Milk (FPCM)). Decreasing direct and indirect energy requirements allowed reducing the anthropogenic gas emissions to the environment, reducing the energy costs for dairy farms and improving the efficient utilization of natural resources. Full article
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Open AccessArticle Fuzzy Logic-Based Perturb and Observe Algorithm with Variable Step of a Reference Voltage for Solar Permanent Magnet Synchronous Motor Drive System Fed by Direct-Connected Photovoltaic Array
Energies 2018, 11(2), 462; https://doi.org/10.3390/en11020462
Received: 17 January 2018 / Revised: 14 February 2018 / Accepted: 14 February 2018 / Published: 22 February 2018
Cited by 1 | PDF Full-text (2462 KB) | HTML Full-text | XML Full-text
Abstract
Photovoltaic pumping is considered to be the most used application amongst other photovoltaic energy applications in isolated sites. This technology is developing with a slow progression to allow the photovoltaic system to operate at its maximum power. This work introduces the modified algorithm
[...] Read more.
Photovoltaic pumping is considered to be the most used application amongst other photovoltaic energy applications in isolated sites. This technology is developing with a slow progression to allow the photovoltaic system to operate at its maximum power. This work introduces the modified algorithm which is a perturb and observe (P&O) type to overcome the limitations of the conventional P&O algorithm and increase its global performance in abrupt weather condition changes. The most significant conventional P&O algorithm restriction is the difficulty faced when choosing the variable step of the reference voltage value, a good compromise between the swift dynamic response and the stability in the steady state. To adjust the step reference voltage according to the location of the operating point of the maximum power point (MPP), a fuzzy logic controller (FLC) block adapted to the P&O algorithm is used. This allows the improvement of the tracking pace and the steady state oscillation elimination. The suggested method was evaluated by simulation using MATLAB/SimPowerSystems blocks and compared to the classical P&O under different irradiation levels. The results obtained show the effectiveness of the technique proposed and its capacity for the practical and efficient tracking of maximum power. Full article
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Open AccessArticle A Steady-State Analysis Method for Modular Multilevel Converters Connected to Permanent Magnet Synchronous Generator-Based Wind Energy Conversion Systems
Energies 2018, 11(2), 461; https://doi.org/10.3390/en11020461
Received: 23 January 2018 / Revised: 10 February 2018 / Accepted: 20 February 2018 / Published: 22 February 2018
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Abstract
Modular multilevel converters (MMCs) have shown great potential in the area of multi-megawatt wind energy conversion system (WECS) based on permanent magnet synchronous generators (PMSGs). However, the studies in this area are few, and most of them refer to the MMC used in
[...] Read more.
Modular multilevel converters (MMCs) have shown great potential in the area of multi-megawatt wind energy conversion system (WECS) based on permanent magnet synchronous generators (PMSGs). However, the studies in this area are few, and most of them refer to the MMC used in high-voltage direct current (HVDC) systems, and hence the characteristics of the PMSG are not considered. This paper proposes a steady-state analysis method for MMCs connected to a PMSG-based WECS. In the proposed method, only the wind speed (operating condition) is required as input, and all the electrical quantities in the MMC, including the amplitudes, phase angles and their harmonics, can be calculated step by step. The analysis method is built on the proposed d-q frame mathematical model. Interactions of electrical quantities between the MMC and PMSG are comprehensively considered. Moreover, a new way to calculate the average switching functions are adopted in order to improve the accuracy of the analysis method. Applications of the proposed method are also presented, which includes the characteristic analysis of capacitor voltage ripples and the capacitor sizing. Finally, the accuracy of the method and the correctness of the analysis are verified by simulations and experiments. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessFeature PaperArticle Estimation of Effective Diffusion Coefficient of O2 in Ash Layer in Underground Coal Gasification by Thermogravimetric Apparatus
Energies 2018, 11(2), 460; https://doi.org/10.3390/en11020460
Received: 28 January 2018 / Revised: 14 February 2018 / Accepted: 14 February 2018 / Published: 22 February 2018
Cited by 1 | PDF Full-text (5051 KB) | HTML Full-text | XML Full-text
Abstract
Underground coal gasification (UCG) proceeds generally in the presence of an ash layer on coal (or char) surface. The ash layer increases the mass transfer resistance of O2 to the gasification surface, which may become the limiting step of whole process. This
[...] Read more.
Underground coal gasification (UCG) proceeds generally in the presence of an ash layer on coal (or char) surface. The ash layer increases the mass transfer resistance of O2 to the gasification surface, which may become the limiting step of whole process. This paper studies O2 diffusion in ash layer formed on cylindrical char samples using a specially designed one-dimension setup in a thermogravimetric apparatus (TGA). The effective internal diffusion coefficient (De) is found to increase with an increase in ash layer thickness, due to an increase in median pore diameter. Methods are established to correlate De with operating conditions and to estimate the role of internal diffusion resistance in overall mass transfer resistance. Full article
(This article belongs to the Special Issue Biomass Chars: Elaboration, Characterization and Applications Ⅱ)
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Open AccessArticle Real-Time Genetic Algorithms-Based MPPT: Study and Comparison (Theoretical an Experimental) with Conventional Methods
Energies 2018, 11(2), 459; https://doi.org/10.3390/en11020459
Received: 9 January 2018 / Revised: 19 February 2018 / Accepted: 20 February 2018 / Published: 22 February 2018
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Abstract
Maximum Power Point Tracking (MPPT) methods are used in photovoltaic (PV) systems to continually maximize the PV array output power, which strongly depends on both solar radiation and cell temperature. The PV power oscillations around the maximum power point (MPP) resulting from the
[...] Read more.
Maximum Power Point Tracking (MPPT) methods are used in photovoltaic (PV) systems to continually maximize the PV array output power, which strongly depends on both solar radiation and cell temperature. The PV power oscillations around the maximum power point (MPP) resulting from the conventional methods and complexity of the non-conventional ones are convincing reasons to look for novel MPPT methods. This paper deals with simple Genetic Algorithms (GAs) based MPPT method in order to improve the convergence, rapidity, and accuracy of the PV system. The proposed method can also efficiently track the global MPP, which is very useful for partial shading. At first, a review of the algorithm is given, followed with many test examples; then, a comparison by means Matlab/Simulink© (R2009b) is conducted between the proposed MPPT and, the popular Perturb and Observe (PO) and Incremental Conductance (IC) techniques. The results show clearly the superiority of the proposed controller. Indeed, with the proposed algorithm, oscillations around the MPP are dramatically minimized, a better stability is observed and increase in the output power efficiency is obtained. All these results are experimentally validated by a test bench developed at LIAS laboratory (Poitiers University, Poitiers, France) using real PV panels and a PV emulator which allows one to define a profile insolation model. In addition, the proposed method permits one to perform the test of linearity between the optimal current I mp (current at maximum power) and the short-circuit current I sc , and between the optimal voltage V mp and open-circuit voltage V oc , so the current and voltage factors can be easily obtained with our algorithm. Full article
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Open AccessArticle Selective Harmonic Elimination in a Wide Modulation Range Using Modified Newton–Raphson and Pattern Generation Methods for a Multilevel Inverter
Energies 2018, 11(2), 458; https://doi.org/10.3390/en11020458
Received: 19 January 2018 / Revised: 5 February 2018 / Accepted: 11 February 2018 / Published: 22 February 2018
Cited by 2 | PDF Full-text (6681 KB) | HTML Full-text | XML Full-text
Abstract
Considering the aim of having low switching losses, especially in medium-voltage and high-power converters, the pre-programmed pulse width modulation technique is very useful because the generated harmonic content can be known in advance and optimized. Among the different low switching frequency techniques, the
[...] Read more.
Considering the aim of having low switching losses, especially in medium-voltage and high-power converters, the pre-programmed pulse width modulation technique is very useful because the generated harmonic content can be known in advance and optimized. Among the different low switching frequency techniques, the Selective Harmonics Elimination (SHE) modulation method is most suitable because of its direct control over the harmonic spectrum. This paper proposes a method for obtaining multiple solutions for selectively eliminating specific harmonics in a wide range of modulation indices by using modified Newton–Raphson (NR) and pattern generation techniques. The different pattern generation and synthesis approach provide more degrees of freedom and a way to operate the converter in a wide range of modulation. The modified Newton–Raphson technique is not complex and ensures fast convergence on a solution. Moreover, multiple solutions are obtained by keeping a very small increase in the modulation index. In the previous methods, solutions were not obtainable at all modulation indices. In this paper, only exact solutions to the low-order harmonics elimination for Cascaded H-bridge inverter are reported for all modulation indices. Analytical and simulation results prove the robustness and correctness of the technique proposed in this paper. Full article
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Open AccessArticle Suitability Evaluation of Specific Shallow Geothermal Technologies Using a GIS-Based Multi Criteria Decision Analysis Implementing the Analytic Hierarchic Process
Energies 2018, 11(2), 457; https://doi.org/10.3390/en11020457
Received: 14 December 2017 / Revised: 8 February 2018 / Accepted: 13 February 2018 / Published: 22 February 2018
Cited by 1 | PDF Full-text (22211 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The exploitation potential of shallow geothermal energy is usually defined in terms of site-specific ground thermal characteristics. While true, this assumption limits the complexity of the analysis, since feasibility studies involve many other components that must be taken into account when calculating the
[...] Read more.
The exploitation potential of shallow geothermal energy is usually defined in terms of site-specific ground thermal characteristics. While true, this assumption limits the complexity of the analysis, since feasibility studies involve many other components that must be taken into account when calculating the effective market viability of a geothermal technology or the economic value of a shallow geothermal project. In addition, the results of a feasibility study are not simply the sum of the various factors since some components may be conflicting while others will be of a qualitative nature only. Different approaches are therefore needed to evaluate the suitability of an area for shallow geothermal installation. This paper introduces a new GIS platform-based multicriteria decision analysis method aimed at comparing as many different shallow geothermal relevant factors as possible. Using the Analytic Hierarchic Process Tool, a geolocalized Suitability Index was obtained for a specific technological case: the integrated technologies developed within the GEOTeCH Project. A suitability map for the technologies in question was drawn up for Europe. Full article
(This article belongs to the Special Issue Geothermal Heating and Cooling)
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Open AccessArticle Experimental and Numerical Vibrational Analysis of a Horizontal-Axis Micro-Wind Turbine
Energies 2018, 11(2), 456; https://doi.org/10.3390/en11020456
Received: 18 December 2017 / Revised: 2 February 2018 / Accepted: 19 February 2018 / Published: 22 February 2018
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Abstract
Micro-wind turbines are energy conversion technologies strongly affected by fatigue, as a result of their size and the variability of loads, induced by the unsteady wind conditions, and modulated by a very high rotational speed. This work is devoted to the experimental and
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Micro-wind turbines are energy conversion technologies strongly affected by fatigue, as a result of their size and the variability of loads, induced by the unsteady wind conditions, and modulated by a very high rotational speed. This work is devoted to the experimental and numerical characterization of the aeroelastic behavior of a test-case horizontal-axis wind turbine (HAWT) with a 2 m rotor diameter and a maximum power production of 3 kW. The experimental studies have been conducted at the wind tunnel of the University of Perugia and consisted of accelerometer measurements at the tower and the tail fin. The numerical setup was the Fatigue, Aerodynamics, Structures, and Turbulence (FAST) code for aeroelastic simulations, which was fed as input with the same wind conditions employed in the wind tunnel tests. The experimental and numerical analyses were coupled with the perspective of establishing a reciprocal feedback, and this has been accomplished. On one hand, the numerical model is important for interpreting the measured spectrum of tower oscillations and, for example, inspires the detection of a mass unbalance at the blades. On the other hand, the measurements inspire the question of how to interpret the interaction between the blades and the tower. The experimental spectrum of tail fin vibrations indicates that secondary elements, in terms of weight, can also transmit to the tower, giving meaningful contributions to the vibration spectra. Therefore, an integrated numerical and experimental approach is not only valuable but is also unavoidable, to fully characterize the dynamics of small wind-energy conversion systems. Full article
(This article belongs to the Special Issue Wind Turbine Loads and Wind Plant Performance)
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Open AccessArticle Height Adjustment of Vehicles Based on a Static Equilibrium Position State Observation Algorithm
Energies 2018, 11(2), 455; https://doi.org/10.3390/en11020455
Received: 20 January 2018 / Revised: 8 February 2018 / Accepted: 9 February 2018 / Published: 21 February 2018
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Abstract
In this paper, a static state observer algorithm based on the static equilibrium position is proposed, which can realize accurate control of electric vehicle height adjustment with existing road excitation. The existence of road excitation can lead to deflection variation of the electronically
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In this paper, a static state observer algorithm based on the static equilibrium position is proposed, which can realize accurate control of electric vehicle height adjustment with existing road excitation. The existence of road excitation can lead to deflection variation of the electronically controlled air suspension (ECAS). The use of only dynamic deflection as the reference for the electric vehicle height adjustment will produce great errors. Therefore, this paper provides an observation algorithm, which can realize the accurate control of vehicle height. Firstly, the static equilibrium position equation of suspension is derived according to the theory of hydrodynamics and characteristics of pneumatic chamber. Secondly, a vehicle dynamics model with seven degrees of freedom (7-DOF) is established and the kinetic equations are discretized. Then, the unscented Kalman filter (UKF) algorithm is used to obtain the static equilibrium position of vehicle. According to the vehicle static equilibrium position obtained by UKF, the height of the vehicle is adjusted by using a fuzzy controller. The simulation and experimental results show that this proposed algorithm can realize the control of vehicle height with an accuracy of over 96%, which ensures the excellent driving performance of vehicles under different road conditions. Full article
(This article belongs to the Special Issue The International Symposium on Electric Vehicles (ISEV2017))
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Open AccessArticle Optimal Capacity Configuration of a Hybrid Energy Storage System for an Isolated Microgrid Using Quantum-Behaved Particle Swarm Optimization
Energies 2018, 11(2), 454; https://doi.org/10.3390/en11020454
Received: 29 December 2017 / Revised: 5 February 2018 / Accepted: 9 February 2018 / Published: 21 February 2018
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Abstract
The capacity of an energy storage device configuration not only affects the economic operation of a microgrid, but also affects the power supply’s reliability. An isolated microgrid is considered with typical loads, renewable energy resources, and a hybrid energy storage system (HESS) composed
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The capacity of an energy storage device configuration not only affects the economic operation of a microgrid, but also affects the power supply’s reliability. An isolated microgrid is considered with typical loads, renewable energy resources, and a hybrid energy storage system (HESS) composed of batteries and ultracapacitors in this paper. A quantum-behaved particle swarm optimization (QPSO) algorithm that optimizes the HESS capacity is used. Based on the respective power compensation capabilities of ultracapacitors and batteries, a rational energy scheduling strategy is proposed using the principle of a low-pass filter and can help to avoid frequent batteries charging and discharging. Considering the rated power of each energy storage type, the respective compensation power is corrected. By determining whether the charging state reaches the limit, the value is corrected again. Additionally, a mathematical model that minimizes the daily cost of the HESS is derived. This paper takes an isolated micrgrid in north China as an example to verify the effectiveness of this method. The comparison between QPSO and a traditional particle swarm algorithm shows that QPSO can find the optimal solution faster and the HESS has lower daily cost. Simulation results for an isolated microgrid verified the effectiveness of the HESS optimal capacity configuration method. Full article
(This article belongs to the Section Energy Storage and Application)
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Open AccessArticle Insights into Dynamic Tuning of Magnetic-Resonant Wireless Power Transfer Receivers Based on Switch-Mode Gyrators
Energies 2018, 11(2), 453; https://doi.org/10.3390/en11020453
Received: 30 December 2017 / Revised: 5 February 2018 / Accepted: 9 February 2018 / Published: 20 February 2018
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Abstract
Magnetic-resonant wireless power transfer (WPT) has become a reliable contactless source of power for a wide range of applications. WPT spans different power levels ranging from low-power implantable devices up to high-power electric vehicles (EV) battery charging. The transmission range and efficiency of
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Magnetic-resonant wireless power transfer (WPT) has become a reliable contactless source of power for a wide range of applications. WPT spans different power levels ranging from low-power implantable devices up to high-power electric vehicles (EV) battery charging. The transmission range and efficiency of WPT have been reasonably enhanced by resonating the transmitter and receiver coils at a common frequency. Nevertheless, matching between resonance in the transmitter and receiver is quite cumbersome, particularly in single-transmitter multi-receiver systems. The resonance frequency in transmitter and receiver tank circuits has to be perfectly matched, otherwise power transfer capability is greatly degraded. This paper discusses the mistuning effect of parallel-compensated receivers, and thereof a novel dynamic frequency tuning method and related circuit topology and control is proposed and characterized in the system application. The proposed method is based on the concept of switch-mode gyrator emulating variable lossless inductors oriented to enable self-tunability in WPT receivers. Full article
(This article belongs to the Special Issue Wireless Power Transfer and Energy Harvesting Technologies)
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Open AccessArticle Big Data Mining of Energy Time Series for Behavioral Analytics and Energy Consumption Forecasting
Energies 2018, 11(2), 452; https://doi.org/10.3390/en11020452
Received: 24 December 2017 / Revised: 10 February 2018 / Accepted: 12 February 2018 / Published: 20 February 2018
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Abstract
Responsible, efficient and environmentally aware energy consumption behavior is becoming a necessity for the reliable modern electricity grid. In this paper, we present an intelligent data mining model to analyze, forecast and visualize energy time series to uncover various temporal energy consumption patterns.
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Responsible, efficient and environmentally aware energy consumption behavior is becoming a necessity for the reliable modern electricity grid. In this paper, we present an intelligent data mining model to analyze, forecast and visualize energy time series to uncover various temporal energy consumption patterns. These patterns define the appliance usage in terms of association with time such as hour of the day, period of the day, weekday, week, month and season of the year as well as appliance-appliance associations in a household, which are key factors to infer and analyze the impact of consumers’ energy consumption behavior and energy forecasting trend. This is challenging since it is not trivial to determine the multiple relationships among different appliances usage from concurrent streams of data. Also, it is difficult to derive accurate relationships between interval-based events where multiple appliance usages persist for some duration. To overcome these challenges, we propose unsupervised data clustering and frequent pattern mining analysis on energy time series, and Bayesian network prediction for energy usage forecasting. We perform extensive experiments using real-world context-rich smart meter datasets. The accuracy results of identifying appliance usage patterns using the proposed model outperformed Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) at each stage while attaining a combined accuracy of 81.82%, 85.90%, 89.58% for 25%, 50% and 75% of the training data size respectively. Moreover, we achieved energy consumption forecast accuracies of 81.89% for short-term (hourly) and 75.88%, 79.23%, 74.74%, and 72.81% for the long-term; i.e., day, week, month, and season respectively. Full article
(This article belongs to the Special Issue Data Science and Big Data in Energy Forecasting)
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Open AccessArticle A Comprehensive Energy Analysis and Related Carbon Footprint of Dairy Farms, Part 1: Direct Energy Requirements
Energies 2018, 11(2), 451; https://doi.org/10.3390/en11020451
Received: 22 December 2017 / Revised: 8 February 2018 / Accepted: 13 February 2018 / Published: 20 February 2018
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Abstract
Dairy cattle farms are continuously developing more intensive systems of management which require higher utilization of durable and not-durable inputs. These inputs are responsible of significant direct and indirect fossil energy requirements which are related to remarkable emissions of CO2. This
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Dairy cattle farms are continuously developing more intensive systems of management which require higher utilization of durable and not-durable inputs. These inputs are responsible of significant direct and indirect fossil energy requirements which are related to remarkable emissions of CO2. This study aims to analyze direct energy requirements and the related carbon footprint of a large population of conventional dairy farms located in the south of Italy. A detailed survey of electricity, diesel and Liquefied Petroleum Gas (LPG) consumptions has been carried out among on-farm activities. The results of the analyses showed an annual average fuel consumption of 40 kg per tonne of milk, while electricity accounted for 73 kWh per tonne of milk produced. Expressing the direct energy inputs as primary energy, diesel fuel results the main resource used in on-farm activities, accounting for 72% of the total fossil primary energy requirement, while electricity represents only 27%. Moreover, larger farms were able to use more efficiently the direct energy inputs and reduce the related emissions of carbon dioxide per unit of milk produced, since the milk yield increases with the herd size. The global average farm emissions of carbon dioxide equivalent, due to all direct energy usages, accounted for 156 kg CO2-eq per tonne of Fat and Protein Corrected Milk (FPCM), while farms that raise more than 200 heads emitted 36% less than the average value. In this two-part series, the total energy demand (Part 1 + Part 2) per farm is mainly due to agricultural inputs and fuel consumption, which have the largest quota of the annual requirements for each milk yield class. These results also showed that large size farms held lower CO2-eq emissions when referred to the mass of milk produced. Full article
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Open AccessArticle Hydrothermal Disintegration and Extraction of Different Microalgae Species
Energies 2018, 11(2), 450; https://doi.org/10.3390/en11020450
Received: 17 December 2017 / Revised: 28 January 2018 / Accepted: 11 February 2018 / Published: 20 February 2018
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Abstract
For the disintegration and extraction of microalgae to produce lipids and biofuels, a novel processing technology was investigated. The utilization of a hydrothermal treatment was tested on four different microalgae species (Scenedesmus rubescens, Chlorella vulgaris, Nannochloropsis oculata and Arthorspira platensis (Spirulina))
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For the disintegration and extraction of microalgae to produce lipids and biofuels, a novel processing technology was investigated. The utilization of a hydrothermal treatment was tested on four different microalgae species (Scenedesmus rubescens, Chlorella vulgaris, Nannochloropsis oculata and Arthorspira platensis (Spirulina)) to determine whether it has an advantage in comparison to other disintegration methods for lipid extraction. It was shown, that hydrothermal treatment is a reasonable opportunity to utilize microalgae without drying and increase the lipid yield of an algae extraction process. For three of the four microalgae species, the extraction yield with a prior hydrothermal treatment elevated the lipid yield up to six times in comparison to direct extraction. Only Scenedesmus rubescens showed a different behaviour. Reason can be found in the different cell wall of the species. The investigation of the differences in cell wall composition of the used species indicate that the existence of algaenan as a cell wall compound plays a major role in stability. Full article
(This article belongs to the collection Bioenergy and Biofuel)
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Open AccessArticle Energy Analysis of a Rotary Drum Bioreactor for Composting Tomato Plant Residues
Energies 2018, 11(2), 449; https://doi.org/10.3390/en11020449
Received: 7 December 2017 / Revised: 13 February 2018 / Accepted: 14 February 2018 / Published: 19 February 2018
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Abstract
Energy produced from plant residue composting has stimulated great interest in heat recovery and utilization. Composting is an exothermic process often controlled through temperature measurements. However, energy analysis of the overall composting system, especially the rotary bioreactors, is generally not well known and
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Energy produced from plant residue composting has stimulated great interest in heat recovery and utilization. Composting is an exothermic process often controlled through temperature measurements. However, energy analysis of the overall composting system, especially the rotary bioreactors, is generally not well known and very limited. This study presents detailed energy analysis in a laboratory-scale, batch-operated, rotary bioreactor used for composting tomato plant residues. The bioreactor was considered as a thermodynamic system operating under unsteady state conditions. The composting process was described, the input generated and lost energy terms as well as the relative importance of each term were quantitatively evaluated, and the composting phases were clearly identified. Results showed that the compost temperature peaked at 72 h of operation reaching 66.7 °C with a heat generation rate of 9.3 W·kg−1 of organic matter. During the composting process, the accumulated heat generation was 1.9 MJ·kg−1 of organic matter; only 4% of this heat was gained by the composting material, and 96% was lost outside the bioreactor. Contributions of thermal radiation, aeration, cylindrical, and side-walls surfaces of the reactor on the total heat loss were 1%, 2%, 69%, and 28%, respectively. The information obtained is applicable in the design, management, and control of composting operations and in improvement of bioreactor effectiveness and productivity. Full article
(This article belongs to the collection Bioenergy and Biofuel)
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Open AccessArticle The Share Price and Investment: Current Footprints for Future Oil and Gas Industry Performance
Energies 2018, 11(2), 448; https://doi.org/10.3390/en11020448
Received: 1 January 2018 / Revised: 10 February 2018 / Accepted: 13 February 2018 / Published: 19 February 2018
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Abstract
The share price has become a very important indicator for shareholders, banks, and financial institutions evaluating the performance of companies. The oil and gas industry seems to be in a difficult era of development, due to the market prices for its products. Moreover,
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The share price has become a very important indicator for shareholders, banks, and financial institutions evaluating the performance of companies. The oil and gas industry seems to be in a difficult era of development, due to the market prices for its products. Moreover, climate change and renewable energies are barriers for fossil energy. This state of affairs, and the fact that oil and gas shares are considered one of the most solid and reliable shares on the London Stock Exchange (LSE), have drawn our attention. International institutions encourage the investment in the oil and gas economic sector. This study investigates how investments of oil and gas companies in long-term assets influence the share price. Using the Ohlson share price model for a sample of 51 listed companies on the LSE proves that investments in long-term assets influence the share price in the case of companies which record losses. Investments in long-term assets are responsible for the attractiveness of the oil and gas company shares. Full article
Open AccessArticle Prediction Model of Photovoltaic Module Temperature for Power Performance of Floating PVs
Energies 2018, 11(2), 447; https://doi.org/10.3390/en11020447
Received: 13 December 2017 / Revised: 9 February 2018 / Accepted: 11 February 2018 / Published: 18 February 2018
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Abstract
Rapid reduction in the price of photovoltaic (solar PV) cells and modules has resulted in a rapid increase in solar system deployments to an annual expected capacity of 200 GW by 2020. Achieving high PV cell and module efficiency is necessary for many
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Rapid reduction in the price of photovoltaic (solar PV) cells and modules has resulted in a rapid increase in solar system deployments to an annual expected capacity of 200 GW by 2020. Achieving high PV cell and module efficiency is necessary for many solar manufacturers to break even. In addition, new innovative installation methods are emerging to complement the drive to lower $/W PV system price. The floating PV (FPV) solar market space has emerged as a method for utilizing the cool ambient environment of the FPV system near the water surface based on successful FPV module (FPVM) reliability studies that showed degradation rates below 0.5% p.a. with new encapsulation material. PV module temperature analysis is another critical area, governing the efficiency performance of solar cells and module. In this paper, data collected over five-minute intervals from a PV system over a year is analyzed. We use MATLAB to derived equation coefficients of predictable environmental variables to derive FPVM’s first module temperature operation models. When comparing the theoretical prediction to real field PV module operation temperature, the corresponding model errors range between 2% and 4% depending on number of equation coefficients incorporated. This study is useful in validation results of other studies that show FPV systems producing 10% more energy than other land based systems. Full article
(This article belongs to the Special Issue PV System Design and Performance)
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Open AccessArticle A General Mathematical Formulation for Winding Layout Arrangement of Electrical Machines
Energies 2018, 11(2), 446; https://doi.org/10.3390/en11020446
Received: 24 January 2018 / Revised: 7 February 2018 / Accepted: 12 February 2018 / Published: 17 February 2018
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Abstract
Winding design methods have been a subject of research for many years of the past century. Many methods have been developed, each one characterized by some advantages and drawbacks. Nowadays, the star of slots is the most widespread design tool for electrical machine
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Winding design methods have been a subject of research for many years of the past century. Many methods have been developed, each one characterized by some advantages and drawbacks. Nowadays, the star of slots is the most widespread design tool for electrical machine windings. In this context, this paper presents a simple and effective procedure to determine the distribution of the slot EMFs over the phases and of the winding configuration in all possible typologies of electrical machines equipped with symmetrical windings. The result of this procedure gives a Winding Distribution Table (WDT), which can be used to define coils and coil groups connections and also to simply implement winding optimizations techniques, such as zone widening, imbrication, etc. Moreover, this procedure can be easily implemented on a computer in order to perform automated winding designs for rotating electrical machines. Several examples are provided in order to validate the proposed procedure. Full article
(This article belongs to the Section Energy Fundamentals and Conversion)
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Open AccessReview Ensemble-Based Data Assimilation in Reservoir Characterization: A Review
Energies 2018, 11(2), 445; https://doi.org/10.3390/en11020445
Received: 9 January 2018 / Revised: 7 February 2018 / Accepted: 9 February 2018 / Published: 17 February 2018
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Abstract
This paper presents a review of ensemble-based data assimilation for strongly nonlinear problems on the characterization of heterogeneous reservoirs with different production histories. It concentrates on ensemble Kalman filter (EnKF) and ensemble smoother (ES) as representative frameworks, discusses their pros and cons, and
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This paper presents a review of ensemble-based data assimilation for strongly nonlinear problems on the characterization of heterogeneous reservoirs with different production histories. It concentrates on ensemble Kalman filter (EnKF) and ensemble smoother (ES) as representative frameworks, discusses their pros and cons, and investigates recent progress to overcome their drawbacks. The typical weaknesses of ensemble-based methods are non-Gaussian parameters, improper prior ensembles and finite population size. Three categorized approaches, to mitigate these limitations, are reviewed with recent accomplishments; improvement of Kalman gains, add-on of transformation functions, and independent evaluation of observed data. The data assimilation in heterogeneous reservoirs, applying the improved ensemble methods, is discussed on predicting unknown dynamic data in reservoir characterization. Full article
(This article belongs to the Section Energy Sources)
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Open AccessFeature PaperArticle Analysis of Air-Side Economizers in Terms of Cooling-Energy Performance in a Data Center Considering Exhaust Air Recirculation
Energies 2018, 11(2), 444; https://doi.org/10.3390/en11020444
Received: 24 January 2018 / Revised: 12 February 2018 / Accepted: 13 February 2018 / Published: 17 February 2018
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Abstract
Demand is soaring for data centers with advanced data-processing capabilities. In data centers with high-temperature information technology (IT) equipment, enormous cooling systems are operated year-round. To date, studies have aimed to improve the cooling efficiency of server-room units, but cooling-energy-consumption analysis considering the
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Demand is soaring for data centers with advanced data-processing capabilities. In data centers with high-temperature information technology (IT) equipment, enormous cooling systems are operated year-round. To date, studies have aimed to improve the cooling efficiency of server-room units, but cooling-energy-consumption analysis considering the recirculation of exhaust air (EA) has not been researched to a sufficient degree. This study analyzed the cooling-energy saving effects considering the EA-recirculation and supply-air (SA)-temperature conditions when direct and indirect air-side economizers were applied to a data center in Korea. Thirteen case studies were conducted. The results showed that when the EA-recirculation ratio in the direct air-side economizer was 15%, its annual cooling-energy consumption increased by approximately 6.1% compared to the case with no recirculation. The indirect air-side economizer also exhibited an approximately 9% increase in cooling-energy consumption. On the other hand, when the SA temperature changed to 22 °C, the annual cooling-energy consumption of the direct and indirect air-side economizers decreased by approximately 67% and 55%, respectively, compared to a central chilled-water system. This indicates the importance of developing measures to prevent EA recirculation and of securing a wind path for the improvement of air-conditioning efficiency in data centers at the design stage. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle PWM Carrier Displacement in Multi-N-Phase Drives: An Additional Degree of Freedom to Reduce the DC-Link Stress
Energies 2018, 11(2), 443; https://doi.org/10.3390/en11020443
Received: 18 November 2017 / Revised: 6 February 2018 / Accepted: 11 February 2018 / Published: 16 February 2018
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Abstract
The paper presents a particular Pulse Width Modulation (PWM) strategy to reduce the (Direct Current) DC-link capacitor stress for multi-n-phase drives. A multi-n-phase drive is composed of multiple independent systems of n inverter supplying a multi-n-phase electric machine. The paper focused on the
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The paper presents a particular Pulse Width Modulation (PWM) strategy to reduce the (Direct Current) DC-link capacitor stress for multi-n-phase drives. A multi-n-phase drive is composed of multiple independent systems of n inverter supplying a multi-n-phase electric machine. The paper focused on the investigation of the best phase shifting between carriers for a triple-3-phase drive compared to the 3-phase counterpart in order to reduce the capacitor bench design point. Simulation and experimental results show as the control technique proposed is able to reduce the value of the DC-link capacitor current in any operating condition including fault case. In this sense, the PWM carrier displacement appears like an additional degree of freedom that can be exploited in multi-n-phase drives but also in multi-motor application. Full article
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