Energies, Volume 12, Issue 11 (June-1 2019) – 194 articles

Millimeter Wave (mmWave) Massive Multiple Input Multiple Output (MIMO) has been a promising candidate for the current and next generation of cellular networks. The hybrid analogue/digital precoding will be a crucial ingredient in the mmWave cellular systems to reduce the number of Radio Frequency (RF) chains along with the corresponding energy and power consumption of the systems. In this paper, we aim to improve the energy efficiency of mmWave Massive MIMO by using a combination of high dimension analogue precoder and low dimension digital precoder. The spectral efficiency and the corresponding transmitted and consumed power of the mmWave Massive MIMO is formulated by taking all the consumed power from the transmitting side to receiving end into account. We propose the Power Controlled Energy Maximization (PCEM) algorithm in this paper, and the proposed algorithm works by controlling the transmission power to balance the improved radiated energy efficiency and the increased power consumption for a given number of transceiver chains. The simulation and analytical results show that the proposed algorithm performs better than the reference algorithms by maximizing the overall energy efficiency of the system without much complexity. Full article

Due to the crucial implication of oil risks for economic growth and policy making, the aim of this paper is to explore the heterogeneous interconnections of supply or demand in oil risks over time horizons and different countries. Specifically, we first examine the correlation of supply or demand in oil return risks and show the relationships in different countries based on wavelet coherence. Furthermore, we explore the time-varying interconnections between supply- or demand-side and oil return risks, as well as oil producers and demand countries. The empirical results show that the correlation between supply and oil return risks is relatively stable, whereas the linkage between demand and oil return risks shows greater volatility due to the impact of specific events. Further study indicates that there are heterogeneous interconnections between supply- or demand-side and oil return risks over sample periods. Specifically, the sign of response could be divided into four phases, i.e., 1997–2002, 2002–2010, 2010–2013 and 2014–2018. In addition, the interconnections of the demand side could be divided into three phases due to the sign of it. What is more, the dynamic interconnections of oil producers’ or countries’ demands behave quite heterogeneously in different countries. Thus policymakers should focus on the coordination level and space capacity in the global crude oil market. Full article

This paper proves the soundness of supercritical CO₂ displacement for enhancing gas recovery of a tight gas reservoir via laboratory investigations and compositional modeling. First, a novel phase behavior experimental device with a screened supercritical CO₂ dyeing agent were first presented to better understand the mixture characteristics between supercritical CO₂ and natural gas. The mass transfer between two vapor phases was also measured. Then, based on experimental results, the compositional model considering the influence of CO₂ diffusion on the gas recovery and critical property adjustment of supercritical CO₂ was established. The miscibility process and mixing properties, such as density, viscosity, and the flowing velocity vector, of supercriticalCO₂ and natural gas were visualized through a 3D display, which obtained a better understanding of the flooding mechanism of Enhanced Gas Recovery (EGR) via supercritical CO₂. Finally, with experiments and numerical simulations, the main benefits of CO₂ EGR were shown, which were partial miscibility between CO₂ and natural gas, pressure maintenance, and CO₂ displacement as a “gas cushion.” In general, experiments and numerical simulations demonstrate that CO₂ EGR can be seen as a promising way of prolonging the productive life and enhancing recovery of tight gas reservoirs. Full article

This work addresses the problem of mitigating the effects of the cogging torque in permanent magnet synchronous motors, particularly brushless motors, which is a main issue in precision electric drive applications. In this work, a method for mitigating the effects of the cogging torque is proposed, based on the use of a nonlinear automatic control technique known as feedback linearization that is ideal for underactuated dynamic systems. The aim of this work is to present an alternative to classic solutions based on the physical modification of the electrical machine to try to suppress the natural interaction between the permanent magnets and the teeth of the stator slots. Such modifications of electric machines are often expensive because they require customized procedures, while the proposed method does not require any modification of the electric drive. With respect to other algorithmic-based solutions for cogging torque reduction, the proposed control technique is scalable to different motor parameters, deterministic, and robust, and hence easy to use and verify for safety-critical applications. As an application case example, the work reports the reduction of the oscillations for the angular position control of a permanent magnet synchronous motor vs. classic PI (proportional-integrative) cascaded control. Moreover, the proposed algorithm is suitable to be implemented in low-cost embedded control units. Full article

With the large number of distributed generation (DG) access to the distribution network, the traditional distribution network with a single-supply radial structure has been transformed into an active distribution system (ADS) with source and bidirectional currents. This transformation makes the calculation of the power supply capacity (PSC) of the ADS face new challenges, and the uncertainty of the DG output increases the difficulty in calculating the PSC. At the same time, the power market transaction check needs to meet the safety constraints of the distribution network operation, and is required to know the PSC information of the ADS more quickly and accurately. Therefore, in order to quickly evaluate the PSC of the ADS, this paper proposes a fast evaluation method of the PSC based on the DG output rolling prediction and the information gap decision theory (IGDT). The method first establishes a rolling prediction model of the DG output, and calculates the PSC of the ADS at the corresponding time. Next, it establishes a risk avoidance model (RAM) and a risk speculation model (RSM) for the PSC of the ADS based on the IGDT. These models further calculate the probability of the range of the PSC at the corresponding time, so as to better evaluate the PSC of the ADS. Finally, the improved IEEE-14 node is used to verify that the model can consider the influence of the DG output uncertainty and quickly calculate the information of PSC. Full article

Steam-explosion is a promising technology for recovering phenolic compounds from olive mill solid waste (OMSW) due to its high impact on the structure of the fibre. Moreover, the recovery of the phenols, which are well-known microbial inhibitors, could improve the subsequent biomethanization of the dephenolized OMSW to produce energy. However, there is a considerable lack of knowledge about how the remaining phenolic compounds could affect a long-term biomethanization process of steam-exploded OMSW. This work evaluated a semi-continuous mesophilic anaerobic digestion of dephenolized steam-exploited OMSW during a long operational period (275 days), assessing different organic loading rates (OLRs). The process was stable at an OLR of 1 gVS/(L·d), with a specific production rate of 163 ± 28 mL CH₄/(gVS·d). However, the increment of the OLR up to 2 gVS/(L·d) resulted in total exhaust of the methane production. The increment in the propionic acid concentration up to 1486 mg/L could be the main responsible factor for the inhibition. Regardless of the OLR, the concentration of phenolic compounds was always lower than the inhibition limits. Therefore, steam-exploited OMSW could be a suitable substrate for anaerobic digestion at a suitable OLR. Full article

This paper deals with a methodical design approach of fault-tolerant controller that gives assurance for the the stabilization and acceptable control performance of the nonlinear systems which can be described by Takagi–Sugeno (T–S) fuzzy models. Takagi–Sugeno fuzzy model gives a unique edge that allows us to apply the traditional linear system theory for the investigation and blend of nonlinear systems by linear models in a different state space region. The overall fuzzy model of the nonlinear system is obtained by fuzzy combination of the all linear models. After that, based on this linear model, we employ parallel distributed compensation for designing linear controllers for each linear model. Also this paper reports of the T–S fuzzy system with less conservative stabilization condition which gives decent performance. However, the controller synthesis for nonlinear systems described by the T–S fuzzy model is a complicated task, which can be reduced to convex problems linking with linear matrix inequalities (LMIs). Further sufficient conservative stabilization conditions are represented by a set of LMIs for the Takagi–Sugeno fuzzy control systems, which can be solved by using MATLAB software. Two-rule T–S fuzzy model is used to describe the nonlinear system and this system demonstrated with proposed fault-tolerant control scheme. The proposed fault-tolerant controller implemented and validated on three interconnected conical tank system with two constraints in terms of faults, one issed to build the actuator and sond is system component (leak) respectively. The MATLAB Simulink platform with linear fuzzy models and an LMI Toolbox was used to solve the LMIs and determine the controller gains subject to the proposed design approach. Full article

A simple model was built to predict the national and regional electricity demand by sectors under China’s new normal situation. In the model, the data dimensionality reduction method and the Grey model (GM(1,1)) were combined and adopted to disaggregate the national economic growth rate into regional levels and forecast each region’s contribution rate to the national economic growth and regional industrial structure. Then, a bottom–up accounting model that considered the impacts of regional industrial structure transformation, regional energy efficiency, and regional household electric consumption was built to predict national and regional electric demand. Based on the predicted values, this paper analyzed the spatial changes in electric demand, and our results indicate the following. Firstly, the proposed model has high accuracy in national electricity demand prediction: the relative error in 2017 and 2018 was 2.90% and 2.60%, respectively. Secondly, China’s electric demand will not peak before 2025, and it is estimated to be between 7772.16 and 8458.85 billion kW·h in 2025, which is an increase of 31.28–42.88% compared with the total electricity consumption in 2016. The proportion of electricity demand in the mid-west regions will increase, while the eastern region will continue to be the country’s load center. Thirdly, under China’s new normal, households and the tertiary industry will be the main driving forces behind the increases in electric demand. Lastly, the drop in China’s economy under the new normal will lead to a decline in the total electricity demand, but it will not evidently change the electricity consumption share of the primary industry, secondary industry, tertiary industry, and household sector. Full article

Central inverters are usually employed in large photovoltaic farms because they offer a good compromise between costs and efficiency. However, inverters based on a single power stage have poor efficiency in the low power range, when the irradiation conditions are low. For that reason, an extended solution has been the parallel connection of several inverter modules that manage a fraction of the full power. Besides other benefits, this power architecture can improve the efficiency of the whole system by connecting or disconnecting the modules depending on the amount of managed power. In this work, a control technique is proposed that maximizes the global efficiency of this kind of systems. The developed algorithm uses a functional model of the inverters’ efficiency to decide the number of modules on stream. This model takes into account both the power that is instantaneously processed and the maximum power point tracking (MPPT) voltage that is applied to the photovoltaic field. A comparative study of several models of efficiency for photovoltaic inverters is carried out, showing that bidimensional models are the best choice for this kind of systems. The proposed algorithm has been evaluated by considering the real characteristics of commercial inverters, showing that a significant improvement of the global efficiency is obtained at the low power range in the case of sunny days. Moreover, the proposed technique dramatically improves the global efficiency in cloudy days. Full article

This study addresses the life cycle costs (LCC) of energy renovation, and the demolition and construction of a new building. A comparison is made between LCC optimal energy renovations of four different building types with thermal performance, representing Swedish constructions from the 1940s, 1950s, 1960s, and 1970s, as well as the demolition of the building and construction of a new building that complies with the Swedish building code. A Swedish multi-family building from the 1960s is used as a reference building. LCC optimal energy renovations are identified with energy saving targets ranging between 10% and 70%, in addition to the lowest possible life cycle cost. The analyses show that an ambitious energy renovation is not cost-optimal in any of the studied buildings, if achieving the lowest LCC is the objective function. The cost of the demolition and construction of a new building is higher compared to energy renovation to the same energy performance. The higher rent in new buildings does not compensate for the higher cost of new construction. A more ambitious renovation is required in buildings that have a shape factor with a high internal volume to heated floor area ratio. Full article

Velocity profiles in tidal channels cause cyclic oscillations in hydrodynamic loads due to the dependence of relative velocity on angular position, which can lead to fatigue damage. Therefore, the effect of velocity profile on the load variation and fatigue life of large-scale tidal turbines is quantified here. This is accomplished using Fluid Structure Interaction (FSI) simulations created using the ANSYS Workbench software, which couples the fluid solver ANSYS CFX to the structural solver ANSYS transient structural. While these load oscillations only minimally impact power and thrust fluctuation for rotors, they can significantly impact the load variations on individual rotor blades. To evaluate these loadings, a tidal turbine within a channel with a representative flow that follows a 1/7th power velocity profile and an onset turbulence intensity of 5% is simulated. This velocity profile increases the thrust coefficient variation from mean cycle value of an individual blade from 2.8% to 9% and the variation in flap wise bending moment coefficient is increased from 4.9% to 19%. Similarly, the variation from the mean cycle value for blade deformation and stress of 2.5% and 2.8% increased to 9.8% and 10.3%, respectively. Due to the effect of velocity profile, the mean stress is decreased, whereas, the range and variation of stress are considerably increased. Full article

The energy efficient operation of a manufacturing system is important for sustainable development of industry. Apart from the device and process level, energy saving methods at the system level has attracted increasing attention with the rapid growth of the industrial Internet of things technology, which makes it possible to sense and collect real-time data from the production line and provide more opportunities for online control for energy saving purposes. In this paper, a dynamic adaptive fuzzy reasoning Petri net is proposed to decide the machine energy saving state considering the production information of a discrete stochastic manufacturing system. Fuzzy knowledge for energy saving operations of a machine is represented in weighted fuzzy production rules with certain values. The rules describe uncertain, imprecise, and ambiguous knowledge of machine state decisions. This makes an energy saving sleep decision in advance when a machine has the inclination of starvation or blockage, which is based on the real-time production rates and level of connected buffers. A dynamic adaptive fuzzy reasoning Petri net is formally defined to implement the reasoning process of the machine state decision. A manufacturing system case is used to demonstrate the application of our method and the results indicate its effectiveness for energy saving operation purposes. Full article

Inrecent electrical power networks a number of failures due to overloading of the transmission lines, stability problems, mismatch in supply and demand, narrow scope for expanding the transmission network and other issues like global warming, environmental conditions, etc. have been noticed. In this paper, a thyristor-controlled series compensator (TCSC) is placed at the optimum position by using two indices for enhancing the power flows as well as the voltage security and power quality of the integrated system. A fusedseverity index is proposed for the optimal positionalong with a grey wolf algorithm-based optimal tuning of the TCSC for reduction of real power losses, fuel cost with valve-point effect, carbon emissions, and voltage deviation in a modern electrical network. The voltage stability index to evaluate the power flow of the line and a novel line stability indexto assessthe line capacityare used. The TCSC is placed at the highest value of the fusedseverity index. In addition, an intermittent severity index (IMSI) is used to find the most severely affected line and is used for relocating the TCSC to a better location under different contingencies.Lognormal and Weibull probability density functions (PDFs)are utilized forassessing the output ofphotovoltaic (PV) and wind power. The proposed methodhas been implemented on the IEEE 57 bus system to validate the methodology, and the results of the integrated system with and without TCSC are comparedunder normal and contingency conditions. Full article

In order to solve the problem of the electric vehicle (EV) charging amount fluctuation caused by the variation of driving speed during dynamic wireless charging, this paper proposes an EV dynamic wireless charging control method adapting to speed change. Firstly, a dynamic wireless charging model based on a long-track transmitting coil is established, and the expression of the charging power of each load under multi-load situation is obtained. Secondly, the influence of the EV charging number and maximum driving speed on the range of system parameters is studied. Subsequently, the method for determining the load resistance value according to the driving speed under a multi-EV charging condition is further discussed. Afterwards, a charging power control method adapting to the speed variation by load adjustment is proposed. By adjusting the equivalent load of the variable-speed charging EV, its speed variation range can reach 20~60 km/h, while the remaining EVs’ charging power fluctuation range can be kept within 10%~15%. Finally, the experimental prototype is built to verify the above-mentioned control method. Full article

Chinese dome digesters are usually operated at long hydraulic retention times (HRT) and low influent total solids (TS) concentration because of limited mixing. In this study, a newly optimised Chinese dome digester with a self-agitating mechanism was investigated at a pilot scale (digester volume = 500 L) and compared with a conventional Chinese dome digester (as blank) at 15% influent TS concentration at two retention times (30 and 40 days). The reactors were operated at ambient temperature: 27–33 °C. The average specific methane production, volatile fatty acids and percentage of volatile solids (VS) reduction are 0.16 ± 0.13 and 0.25 ± 0.05L CH₄/g VS; 1 ± 0.5 and 0.7 ± 0.3 g/L; and 51 ± 14 and 57 ± 10% at 40 days HRT (day 52–136) for the blank and optimised digester, respectively. At 30 days HRT (day 137–309) the results are 0.19 ± 0.12 and 0.23 ± 0.04 L CH₄/g VS; 1.2 ± 0.6 and 0.7 ± 0.3 g/L; and 51 ± 9 and 58 ± 11.6%. Overall, the optimised digester produced 40% more methane than the blank, despite the high loading rates applied. The optimised digester showed superior digestion treatment efficiency and was more stable in terms of VFA concentration than the blank digester, can be therefore operated at high influent TS (15%) concentration. Full article

Node-localization technology has been supported in the wireless sensor network (WSN) environment. Node localization is based on a few access-point (AP) nodes that comprises positioning information because they are fixed, and a beacon node that comprises unknown positioning information because it is moving. To determine the position of the unknown node, it must use two or three APs that comprise certain positioning information. There are a number of representative range-based methods, including time of arrival (TOA), weighted centroid locating algorithm, received signal strength intensity (RSSI), and time difference of arrival (TDOA) signal, that are received by the receiver. The RSSI method has its advantages. A simple device structure means that the RSSI method is easy to use. Because the structures of previous wireless local area network (LAN) technologies make them compatible with RSSI information, the RSSI method is widely used in the related area of position tracking. In addition, this algorithm has a hardware system that cannot be increased, has the advantage of the miniaturization of the node, and can wear through obstacles. This paper proposes the application of a robust ranging method that can be applied in robots and Internet of Things (IoT) using RSSI, especially in the tracing location of each nursing home patient, where the RSSI method with trilateral technique is used. This paper shows the results of the measured point from the application of the trilateral technique, and it also represents the results of the error distance between the ideal point and the measured point using computer simulation. Finally, this paper presents an estimation of localization using a real experimental device with a BLE (Bluetooth low-energy) transmitter and receiver, and beacon gateway, by applying an RSSI algorithm with the trilateral technique. Full article

This paper presents a comprehensive investigation on the self-sustained oscillation of silicon carbide (SiC) MOSFETs. At first, based on the double pulse switching test, it is identified that the self-sustained oscillation of SiC MOSFETs can be triggered by two distinct test conditions. To investigate the oscillatory criteria of the two types of self-sustained oscillation, a small-signal ac model is introduced to obtain the transfer function of the oscillatory system. The instability of the oscillation is thereby determined by the two conjugate pole pairs of the transfer function. By analyzing the damping ratios of the two pole pairs, the parametric sensitivity of various circuit and device’s parameters on the two types of self-sustained oscillation are obtained. The analyses reveal the oscillatory criteria of the self-sustained oscillation for SiC MOSFETs. Based on the oscillatory criteria, necessary methods are proposed to prevent the oscillation. The proposed oscillation suppression methods are validated by the experiment at the end of the paper. Full article

In the following years all European Union member states should bring into force national laws on the energy performance of buildings. Moreover, university campus dormitories are buildings of great importance, due to their architectural characteristics and their social impact. In this study, the energy performance along with the indoor environmental conditions of a dormitory of a university has been analysed. The in situ measurements included temperature, relative humidity, concentrations of carbon dioxide, total volatile organic compounds, and electrical consumption; lastly, the energy signature of the whole building was investigated. The study focused on the summer months, during which significantly increased thermal needs of the building were identified. The ground floor was found to be the floor with the highest percentage of thermal conditions within the comfort range, and the third floor the lowest. Lastly, a significant correlation between electrical consumption and the outdoor temperature was presented, highlighting the lack of thermal insulation. Overall, it was clear that a redesign of the cooling and heating system, the installation of a ventilation system, and thermal insulation are essential for improving the energy efficiency of this building. Full article

This paper provides a novel bad data detection processor to identify false data injection attacks (FDIAs) on the power system state estimation. The attackers are able to alter the result of the state estimation virtually intending to change the result of the state estimation without being detected by the bad data processors. However, using a specific configuration of an artificial neural network (ANN), named nonlinear autoregressive exogenous (NARX), can help to identify the injected bad data in state estimation. Considering the high correlation between power system measurements as well as state variables, the proposed neural network-based approach is feasible to detect any potential FDIAs. Two different strategies of FDIAs have been simulated in power system state estimation using IEEE standard 14-bus test system for evaluating the performance of the proposed method. The results indicate that the proposed bad data detection processor is able to detect the false injected data launched into the system accurately. Full article

Stand-alone/grid connected renewable energy systems (RESs) require direct current (DC)/DC converters with continuous-input continuous-output current capabilities as maximum power point tracking (MPPT) converters. The continuous-input current feature minimizes the extracted power ripples while the continuous-output current offers non-pulsating power to the storage batteries/DC-link. CUK, D1 and D2 DC/DC converters are highly competitive candidates for this task especially because they share similar low-component count and functionality. Although these converters are of high resemblance, their performance assessment has not been previously compared. In this paper, a detailed comparison between the previously mentioned converters is carried out as several aspects should be addressed, mainly the converter tracking efficiency, conversion efficiency, inductor loss, system modelling, transient and steady-state performance. First, average model and dynamic analysis of the three converters are derived. Then, D1 and D2 small signal analysis in voltage-fed-mode is originated and compared to that of CUK in order to address the nature of converters’ response to small system changes. Finally, the effect of converters’ inductance variation on their performance is studied using rigorous simulation and experimental implementation under varying operating conditions. The assessment finally revels that D1 converter achieves the best overall efficiency with minimal inductor value. Full article

This paper presents a piezoelectric vibration energy harvester (PVEH) with resonance frequencies shifted down by elastically supported masses. The added elastic supporters can diminish the equivalent stiffness of the whole structure, leading to an evident decline in the resonance frequency of the cantilever body. Meantime, a new resonant peak is generated in the lower frequency range. The resonant frequency of the proposed PVEH can be easily adjusted by replacing the rubber band of the elastic support. The constructed configuration is theoretically investigated and experimentally verified. Compared with the conventional cantilever, the proposed device achieved a 46% decrease in resonance frequency and 87% enhancement in output power. Full article

In this paper, we examine non-orthogonal multiple access (NOMA) and relay selection strategy to benefit extra advantage from traditional cognitive radio (CR) relaying systems. The most important requirement to prolong lifetime of such network is employing energy harvesting in the relay to address network with limited power constraint. In particular, we study such energy harvesting CR-NOMA using amplify-and-forward (AF) scheme to improve performance far NOMA users. To further address such problem, two schemes are investigated in term of number of selected relays. To further examine system performance, the outage performance needs to be studied for such wireless powered CR-NOMA network over Rayleigh channels. The accurate expressions for the outage probability are derived to perform outage comparison of primary network and secondary network. The analytical results show clearly that position of these nodes, transmit signal to noise ratio (SNR) and power allocation coefficients result in varying outage performance. As main observation, performance gap between primary and secondary destination is decided by both power allocation factors and selection mode of single relay or multiple relays. Numerical studies were conducted to verify our derivations. Full article

To support high-level wind energy utilization, wind power prediction has become a more and more attractive topic. To improve prediction accuracy and flexibility, joint point-interval prediction of wind power via a stepwise procedure is studied in this paper. Firstly, time-information-granularity (TIG) is defined for ultra-short-term wind speed prediction. Hidden features of wind speed in TIGs are extracted via principal component analysis (PCA) and classified via adaptive affinity propagation (ADAP) clustering. Then, Gaussian process regression (GPR) with joint point-interval estimation ability is adopted for stepwise prediction of the wind power, including wind speed prediction and wind turbine power curve (WTPC) modeling. Considering the sequential uncertainties of stepwise prediction, theoretical support for an uncertainty enlargement effect is deduced. Uncertainties’ transmission from single-step or receding multi-step wind speed prediction to wind power prediction is explained in detail. After that, normalized indexes for point-interval estimation performance are presented for GPR parameters’ optimization via a hybrid particle swarm optimization-differential evolution (PSO-DE) algorithm. K-fold cross validation (K-CV) is used to test the model stability. Moreover, due to the timeliness of data-driven GPR models, an evolutionary prediction mechanism via sliding time window is proposed to guarantee the required accuracy. Finally, measured data from a wind farm in northern China are acquired for validation. From the simulation results, several conclusions can be drawn: the multi-model structure has insignificant advantages for wind speed prediction via GPR; joint point-interval prediction of wind power is realizable and very reasonable; uncertainty enlargement exists for stepwise prediction of wind power while it is more significant after receding multi-step prediction of wind speed; a reasonable quantification mechanism for uncertainty is revealed and validated. Full article

Energy of computing is a serious environmental concern and mitigating it is an important technological challenge. Accurate measurement of energy consumption during an application execution is key to application-level energy minimization techniques. There are three popular approaches to providing it: (a) System-level physical measurements using external power meters; (b) Measurements using on-chip power sensors and (c) Energy predictive models. In this work, we present a comprehensive study comparing the accuracy of state-of-the-art on-chip power sensors and energy predictive models against system-level physical measurements using external power meters, which we consider to be the ground truth. We show that the average error of the dynamic energy profiles obtained using on-chip power sensors can be as high as 73% and the maximum reaches 300% for two scientific applications, matrix-matrix multiplication and 2D fast Fourier transform for a wide range of problem sizes. The applications are executed on three modern Intel multicore CPUs, two Nvidia GPUs and an Intel Xeon Phi accelerator. The average error of the energy predictive models employing performance monitoring counters (PMCs) as predictor variables can be as high as 32% and the maximum reaches 100% for a diverse set of seventeen benchmarks executed on two Intel multicore CPUs (one Haswell and the other Skylake). We also demonstrate that using inaccurate energy measurements provided by on-chip sensors for dynamic energy optimization can result in significant energy losses up to 84%. We show that, owing to the nature of the deviations of the energy measurements provided by on-chip sensors from the ground truth, calibration can not improve the accuracy of the on-chip sensors to an extent that can allow them to be used in optimization of applications for dynamic energy. Finally, we present the lessons learned, our recommendations for the use of on-chip sensors and energy predictive models and future directions. Full article

The ongoing deployment of smart meters and different commercial devices has made electricity disaggregation feasible in buildings and households, based on a single measure of the current and, sometimes, of the voltage. Energy disaggregation is intended to separate the total power consumption into specific appliance loads, which can be achieved by applying Non-Intrusive Load Monitoring (NILM) techniques with a minimum invasion of privacy. NILM techniques are becoming more and more widespread in recent years, as a consequence of the interest companies and consumers have in efficient energy consumption and management. This work presents a detailed review of NILM methods, focusing particularly on recent proposals and their applications, particularly in the areas of Home Energy Management Systems (HEMS) and Ambient Assisted Living (AAL), where the ability to determine the on/off status of certain devices can provide key information for making further decisions. As well as complementing previous reviews on the NILM field and providing a discussion of the applications of NILM in HEMS and AAL, this paper provides guidelines for future research in these topics. Full article

The aim of this work was to explore the effects of variables on the heat of regeneration, the stripping efficiency, the stripping rate, the steam generation rate, and the stripping factor. The Taguchi method was used for the experimental design. The process variables were the CO₂ loading (A), the reboiler temperature (B), the solvent flow rate (C), and the concentration of the solvent (monoethanolamine (MEA) + 2-amino-2-methyl-1-propanol (AMP)) (D), which each had three levels. The stripping efficiency (E), stripping rate ( ${\dot{m}}_{{\mathrm{CO}}_2}$ ), stripping factor (β), and heat of regeneration (Q) were determined by the mass and energy balances under a steady-state condition. Using signal/noise (S/N) analysis, the sequence of importance of the parameters and the optimum conditions were obtained, and the optimum operating conditions were further validated. The results showed that E was in the range of 20.98–55.69%; ${\dot{m}}_{{\mathrm{CO}}_2}$ was in the range of 5.57 × 10⁻⁵–4.03 × 10⁻⁴ kg/s, and Q was in the range of 5.52–18.94 GJ/t. In addition, the S/N ratio analysis showed that the parameter sequence of importance as a whole was A > B > D > C, while the optimum conditions were A3B3C1D1, A3B3C3D2, and A3B2C2D2, for E, ${\dot{m}}_{{\mathrm{CO}}_2}$ , and Q, respectively. Verifications were also performed and were found to satisfy the optimum conditions. Finally, the correlation equations that were obtained were discussed and an operating policy was discovered. Full article

The purpose of this paper is to investigate the effects of using gas to liquid (GTL)-biodiesel blends as an alternative fuel on the physical properties as well as the combustion and emission reduction characteristics in a diesel engine. In order to assess the influence of the GTL-biodiesel blending ratio, the biodiesel is blended with GTL fuel, which is a test fuel with various blending ratios. The effects of GTL-biodiesel blends on the fuel properties, heat release, and emission characteristics were studied at various fuel injection timing and blending ratios. The test fuels investigated here were GTL, biodiesel, and biodiesel blended GTL fuels. The biodiesel blending ratio was changed from 0%, 20% and 40% by a volume fraction. The GTL-biodiesel fuel properties such as the fuel density, viscosity, lower heating value, and cetane number were analyzed in order to compare the effects of different mixing ratios of the biodiesel fuel. Based on the experimental results, certain meaningful results were derived. The increasing rate of the density and kinematic viscosity of the GTL-biodiesel blended fuels at various temperature conditions was increased with the increase in the biodiesel volumetric fraction. The rate of density changes between biodiesel-GTL and GTL are 2.768% to 10.982%. The combustion pressure of the GTL fuel showed a higher pressure than the biodiesel blended GTL fuels. The biodiesel-GTL fuel resulted in reduced NOx and soot emissions compared to those of the unblended GTL fuel. Based on the experimental results, the ignition delay of the GTL-biodiesel blends increased with the increase of the biodiesel blending ratio because of the low cetane number of biodiesel compared to GTL. As the injection timing is advanced, the NOx emissions were significantly increased, while the effect of the injection timing on the soot emission was small compared to the NOx emissions. In the cases of the HC and CO emissions, the GTL-biodiesel blended fuels resulted in similar low emission trends and, in particular, the HC emissions showed a slight increase at the range of advanced injection timings. Full article

Point Daylight Factor (DF_P) has been used for daylighting design in Sweden for more than 40 years. Progressive densification of urban environments, in combination with stricter regulations on energy performance and indoor environmental quality of buildings, creates complex daylight design challenges that cannot be adequately solved with DF_P. To support a development of the current and future daylight indicators in the Swedish context, the authors have developed a comprehensive methodology for the evaluation of daylight levels in existing buildings. The methodology comprises sample buildings of various use and their digital replicas in 3D, detailed numerical simulations and correlations of diverse DF metrics in existing buildings, a field investigation on residents’ satisfaction with available daylight levels in their homes, and a comparison between the numerical and experimental data. The study was deliberately limited to the evaluation of DF metrics for their intuitive understanding and easy evaluation in real design projects. The sample buildings represent typical architectural styles and building technologies between 1887 and 2013 in Gothenburg and include eight residential buildings, two office buildings, two schools, two student apartment buildings, and two hospitals. Although the simulated DF_P is 1.4% on average, i.e., above the required 1%, large variations have been found between the studied 1200 rooms. The empirical data generally support the findings from the numerical simulations, but also bring unique insights in the residences’ preferences for rooms with good daylight. The most remarkable result is related to kitchens, typically the spaces with the lowest DF values, based on simulations, while the residents wish them to be the spaces with the most daylight. Finally, the work introduces a new DF metric, denoted DF_W, which allows daylighting design in early stages when only limited data on the building shape and windows’ arrangement are available. Full article

In this paper, a decoupled model of a train including an on-board hybrid accumulation system is presented to be used in DC traction networks. The train and the accumulation system behavior are modeled separately, and the results are then combined in order to study the effect of the whole system on the traction electrical network. The model is designed specifically to be used with power flow solvers for planning purposes. The validation has been carried out comparing the results with other methods previously developed and also with experimental measurements. A detailed description of the power flow solver is beyond the scope of this work, but it must be remarked that the model must by used with a solver able to cope with the non-linear and non-smooth characteristics of the model. In this specific case, a modified current injection-based power flow solver has been used. The solver is able to incorporate also non-reversible substations, which are the most common devices used currently for feeding DC systems. The effect of the on-board accumulation systems on the network efficiency will be analyzed using different real scenarios. Full article

End fittings are essential components in marine flexible pipe systems, performing the two main functions of connecting and sealing. To investigate the sealing principle and the influence of the temperature on the sealing performance, a hydraulic-thermal finite element (FE) model for the end fitting sealing structure was developed. The sealing mechanism of the end fitting was revealed by simulating the sealing behavior under the pressure penetration criteria. To investigate the effect of temperature, the sealing behavior of the sealing ring under different temperature fields was analyzed and discussed. The results showed that the contact pressure of path 1 (i.e., metal-to-polymer seal) was 31.7 MPa, which was much lower than that of path 2 (metal-to-metal seal) at 195.6 MPa. It was indicated that the sealing capacities were different for the two leak paths, and that the sealing performance of the metal-to-polymer interface had more complicated characteristics. Results also showed that the finite element analysis can be used in conjunction with pressure penetration criteria to evaluate the sealing capacity. According to the model, when the fluid pressures are 20 and 30 MPa, no leakage occurs in the sealing structure, while the sealing structure fails at the fluid pressure of 40 MPa. In addition, it was shown that temperature plays a significant role in the thermal deformation of a sealing structure under a temperature field and that an appropriately high temperature can increase the sealing capacity. Full article