Table of Contents

This paper describes the reduced capacity of the inrush current suppressor using a matrix converter (MC) in a large-capacity wind power generation system (WPGS) with two squirrel-cage induction machines (SCIMs). These SCIMs are switched over depending on the wind speed. The input side of the MC is connected to the source in parallel. The output side of the MC is connected in series with the SCIM through matching transformers. The modulation method of the MC used is direct duty ratio pulse width modulation. The reference output voltage of the MC is decided by multiplying the SCIM current with the variable control gain. Therefore, the MC performs as resistors for the inrush current. Digital computer simulation is implemented to confirm the validity and practicability of the proposed inrush current suppressor using PSCAD/EMTDC (power system computer-aided design/electromagnetic transients including DC). Furthermore, the equivalent resistance of the MC is decided by the relationship between the equivalent resistance and the capacity of the MC. Simulation results demonstrate that the proposed inrush current suppressor can suppress the inrush current perfectly. Full article

Natural gas hydrate accumulations were confirmed in the Dongsha Area of the South China Sea by the Guangzhou Marine Geological Survey 2 (GMGS2) scientific drilling expedition in 2013. The drilling sites of GMGS2-01, -04, -05, -07, -08, -09, -11, -12, and -16 verified the existence of a hydrate-bearing layer. In this work gas production behavior was evaluated at GMGS2-8 by numerical simulation. The hydrate reservoir in the GMGS2-8 was characterized by dual hydrate layers and a massive hydrate layer. A single vertical well was considered as the well configuration, and depressurization was employed as the dissociation method. Analyses of gas production sensitivity to the production pressure, the thermal conductivity, and the intrinsic permeability were investigated as well. Simulation results indicated that the total gas production from the reference case is approximately 7.3 × 10⁷ ST m³ in 30 years. The average gas production rate in 30 years is 6.7 × 10³ ST m³/day, which is much higher than the previous study in the Shenhu Area of the South China Sea performed by the GMGS-1. Moreover, the maximum gas production rate (9.5 × 10³ ST m³/day) has the same order of magnitude of the first offshore methane hydrate production test in the Nankai Trough. When production pressure decreases from 4.5 to 3.4 MPa, the volume of gas production increases by 20.5%, and when production pressure decreases from 3.4 to 2.3 MPa, the volume of gas production increases by 13.6%. Production behaviors are not sensitive to the thermal conductivity. In the initial 10 years, the higher permeability leads to a larger rate of gas production, however, the final volume of gas production in the case with the lowest permeability is the highest. Full article

Electric load forecasting is an important issue for a power utility, associated with the management of daily operations such as energy transfer scheduling, unit commitment, and load dispatch. Inspired by strong non-linear learning capability of support vector regression (SVR), this paper presents an SVR model hybridized with the differential empirical mode decomposition (DEMD) method and quantum particle swarm optimization algorithm (QPSO) for electric load forecasting. The DEMD method is employed to decompose the electric load to several detail parts associated with high frequencies (intrinsic mode function—IMF) and an approximate part associated with low frequencies. Hybridized with quantum theory to enhance particle searching performance, the so-called QPSO is used to optimize the parameters of SVR. The electric load data of the New South Wales (Sydney, Australia) market and the New York Independent System Operator (NYISO, New York, USA) are used for comparing the forecasting performances of different forecasting models. The results illustrate the validity of the idea that the proposed model can simultaneously provide forecasting with good accuracy and interpretability. Full article

Currently, most hybrid electric vehicles (HEVs) equipped with automated mechanical transmission (AMT) are implemented with the conventional two-parameter gear shift schedule based on engineering experience. However, this approach cannot take full advantage of hybrid drives. In other words, the powertrain of an HEV is not able to work at the best fuel-economy points during the whole driving profile. To solve this problem, an optimization method of gear shift schedule for HEVs is proposed based on Dynamic Programming (DP) and a corresponding solving algorithm is also put forward. A gear shift schedule that can be employed in real-vehicle is extracted from the obtained optimal gear shift points by DP approach and is optimized based on analysis of the engineering experience in a typical Chinese urban driving cycle. Compared with the conventional two-parameter gear shift schedule in both simulation and real vehicle experiments, the extracted gear shift schedule is proved to clearly improve the fuel economy of the HEV. Full article

The electricity sector is undergoing an evolution that demands the development of a network model with a high level of intelligence, known as a Smart Grid. One of the factors accelerating these changes is the development and implementation of renewable energy. In particular, increased photovoltaic generation can affect the network’s stability. One line of action is to provide inverters with a management capacity that enables them to act upon the grid in order to compensate for these problems. This paper describes the design and development of a prototype embedded system able to integrate with a photovoltaic inverter and provide it with multifunctional ability in order to analyze power quality and operate with protection. The most important subsystems of this prototype are described, indicating their operating fundamentals. This prototype has been tested with class A protocols according to IEC 61000-4-30 and IEC 62586-2. Tests have also been carried out to validate the response time in generating orders and alarm signals for protections. The highlights of these experimental results are discussed. Some descriptive aspects of the integration of the prototype in an experimental smart inverter are also commented upon. Full article

The conversion efficiency of thin-film silicon solar cells needs to be improved to be competitive with respect to other technologies. For a more efficient use of light across the solar spectrum, multi-junction architectures are being considered. Light-management considerations are also crucial in order to maximize light absorption in the active regions with a minimum of parasitic optical losses in the supportive layers. Intrinsic and doped silicon oxide alloys can be advantageously applied within thin-film Si solar cells for these purposes. Intrinsic a-SiO_x:H films have been fabricated and characterized as a promising wide gap absorber for application in triple-junction solar cells. Single-junction test devices with open circuit voltage up to 950 mV and ~1 V have been demonstrated, in case of rough and flat front electrodes, respectively. Doped silicon oxide alloys with mixed-phase structure have been developed, characterized by considerably lower absorption and refractive index with respect to standard Si-based films, accompanied by electrical conductivity above 10⁻⁵ S/cm. These layers have been successfully applied both into single-junction and micromorph tandem solar cells as superior doped layers with additional functionalities. Full article

A standalone DC microgrid integrated with distributed renewable energy sources, energy storage devices and loads is analyzed. To mitigate the interaction among distributed power modules, this paper describes a modeling and control design procedure for the distributed converters. The system configuration and steady-state analysis of the standalone DC microgrid under study are discussed first. The dynamic models of the distributed converters are then developed from two aspects corresponding to their two operating modes, device-regulating mode and bus-regulating mode. Average current mode control and linear compensators are designed accordingly for each operating mode. The stability of the designed system is analyzed at last. The operation and control design of the system are verified by simulation results. Full article

Current offshore wind farms (OWFs) design processes are based on a sequential approach which does not guarantee system optimality because it oversimplifies the problem by discarding important interdependencies between design aspects. This article presents a framework to integrate, automate and optimize the design of OWF layouts and the respective electrical infrastructures. The proposed framework optimizes simultaneously different goals (e.g., annual energy delivered and investment cost) which leads to efficient trade-offs during the design phase, e.g., reduction of wake losses vs collection system length. Furthermore, the proposed framework is independent of economic assumptions, meaning that no a priori values such as the interest rate or energy price, are needed. The proposed framework was applied to the Dutch Borssele areas I and II. A wide range of OWF layouts were obtained through the optimization framework. OWFs with similar energy production and investment cost as layouts designed with standard sequential strategies were obtained through the framework, meaning that the proposed framework has the capability to create different OWF layouts that would have been missed by the designers. In conclusion, the proposed multi-objective optimization framework represents a mind shift in design tools for OWFs which allows cost savings in the design and operation phases. Full article

Energy-efficient building performance requires sophisticated control systems that are based on realistic occupant behaviour models. To provide robust data for the development of these models, research studies in real-world settings are needed. Yet, such studies are challenging and necessitate careful design in terms of data collection methods and procedures. This paper describes and critiques the design of a mixed methods approach for occupant behaviour research. It reviews the methodology developed for a longitudinal study in a real-world office environment where occupants’ experience with a novel facade technology (electrochromic glazing) was investigated. The methodology integrates objective physical measurements, observational data and self-reported experience data. Using data from one day of the study, this paper illustrates how the different sources can be combined in order to derive an in-depth understanding of the interplay between external daylight conditions, characteristics of the facade technology, occupant interaction with the technology and the resulting occupant experience. It was found that whilst the individual methods may be affected by practical limitations, these can be partially offset by combining physical measurements and observations with self-reported data. The paper critically evaluates the individual techniques, as well as the benefits of their integration and makes recommendations for the design of future occupant behaviour studies in real-world settings. Full article

The efficient operation of a passive solar house requires an efficient ventilation system to prevent the loss of energy and provide the required ventilation rates. This paper proposes the use of “breathing architectural members” (BAMs) as passive natural ventilation devices to achieve much improved ventilation and insulation performance compared to mechanical ventilation. Considering the importance of evaluating the ventilation and insulation performances of the members, we also propose numerical models for predicting the heat and air movements afforded by the members. The numerical model was validated by comparison with experimental results. The effectiveness of the BAMs was also verified by installation in houses located in an area with warm climate. For this purpose, chamber experiments were performed using samples of the BAMs, as well as numerical simulations to assess natural ventilation and heat load. The main findings of the study are as follows: (1) the one-dimensional chamber experiments confirmed the validity of the numerical models for predicting the heat and air movements afforded by the BAMs. Comparison of the experimental and calculated values for the temperature of air that flowed into the room from outside revealed a difference of less than 5%; (2) observations of the case studies in which BAMs were installed in the ceilings and exterior walls of Tokyo model houses revealed good annual ventilation and energy-saving effects. When BAMs with an opening area per unit area of A = 0.002 m²/m² were applied to three surfaces, the required ventilation rate was 0.5 ACH (air changes per hour), and this was achieved consistently. Compared to a house with general insulation and conventional mechanical ventilation, heating load was reduced by 15.3%–40.2% depending on the BAM installation points and the differing areas of the house models. Full article

This paper presents an actuator control unit (ACU) with a 450-J embedded energy storage backup to face safety critical mechatronic applications. The idea is to ensure full operation of electric actuators, even in the case of battery failure, by using supercapacitors as a local energy tank. Thanks to integrated switching converter circuitry, the supercapacitors provide the required voltage and current levels for the required time to guarantee actuator operation until the system enters into safety mode. Experimental results are presented for a target application related to the control of servomotors for a robotized prosthetic arm. Mechatronic devices for rehabilitation or assisted living of injured and/or elderly people are available today. In most cases, they are battery powered with lithium-based cells, providing high energy density and low weight, but at the expense of a reduced robustness compared to lead-acid- or nickel-based battery cells. The ACU of this work ensures full operation of the wearable robotized arm, controlled through acceleration and electromyography (EMG) sensor signals, even in the case of battery failure, thanks to the embedded energy backup unit. To prove the configurability and scalability of the proposed solution, experimental results related to the electric actuation of the car door latch and of a robotized gearbox in vehicles are also shown. The reliability of the energy backup device has been assessed in a wide temperature range, from −40 to 130 °C, and in a durability test campaign of more than 10,000 cycles. Achieved results prove the suitability of the proposed approach for ACUs requiring a burst of power of hundreds of watts for only a few seconds in safety-critical applications. Alternatively, the aging and temperature characterizations of energy backup units is limited to supercapacitors of thousands of farads for high power applications (e.g., electric/hybrid propulsion) and with a temperature range limited to 70 °C. Full article

The evaluation of the thermodynamic performance of the mutual transformation of different kinds of exergy linked to the intensive thermodynamic parameters of the flow inside the ejector of a refrigeration system is undertaken. Two thermodynamic metrics, exergy produced and exergy consumed, are introduced to assess these transformations. Their calculation is based on the evaluation of the transiting exergy within different ejector sections taking into account the temperature, pressure and velocity variations. The analysis based on these metrics has allowed pinpointing the most important factors affecting the ejector’s performance. A new result, namely the temperature rise in the sub-environmental region of the mixing section is detected as an important factor responsible for the ejector’s thermodynamic irreversibility. The overall exergy efficiency of the ejector as well as the efficiencies of its sections are evaluated based on the proposed thermodynamic metrics. Full article

The broad diffusion of renewable energy-based technologies has introduced several open issues in the design and operation of smart grids (SGs) when distributed generators (DGs) inject a large amount of power into the grid. In this paper, a theoretical investigation on active and reactive power data is performed for one active line characterized by several photovoltaic (PV) plants with a great amount of injectable power and two passive lines, one of them having a small peak power PV plant and the other one having no PV power. The frequencies calculated via the empirical mode decomposition (EMD) method based on the Hilbert-Huang transform (HHT) are compared to the ones obtained via the fast Fourier transform (FFT) and the wavelet transform (WT), showing a wider spectrum of significant modes mainly due to the non-periodical behavior of the power signals. The results obtained according to the HHT-EMD analysis are corroborated by the calculation of three new indices that are computed starting from the electrical signal itself and not from the Hilbert spectrum. These indices give the quantitative deviation from the periodicity and the coherence degree of the power signals, which typically deviate from the stationary regime and have a nonlinear behavior in terms of amplitude and phase. This information allows to extract intrinsic features of power lines belonging to SGs and this is useful for their optimal operation and planning. Full article

Distributed renewable electricity generators facilitate decarbonising the electricity network, and the smart grid allows higher renewable penetration while improving efficiency. Smart grid scenarios often emphasise localised control, balancing small renewable generation with consumer electricity demand. This research investigates the applicability of proposed decentralised smart grid scenarios utilising a mixed strategy: quantitative analysis of PV adoption data and qualitative policy analysis focusing on policy design, apparent drivers for adoption of the deviation of observed data from the feed-in tariff impact assessment predictions. Analysis reveals that areas of similar installed PV capacity are clustered, indicating a strong dependence on local conditions for PV adoption. Analysing time series of PV adoption finds that it fits neither neo-classical predictions, nor diffusion of innovation S-curves of adoption cleanly. This suggests the influence of external factors on the decision making process. It is shown that clusters of low installed PV capacity coincide with areas of high population density and vice versa, implying that while visions of locally-balanced smart grids may be viable in certain rural and suburban areas, applicability to urban centres may be limited. Taken in combination, the data analysis, policy impact and socio-psychological drivers of adoption demonstrate the need for a multi-disciplinary approach to understanding and modelling the adoption of technology necessary to enable the future smart grid. Full article

The pulse-based charging method for battery cells has been recognized as a fast and efficient way to overcome the shortcoming of a slow charging time in distributed battery cells, which is regarded as a connection of cells such as the Internet of Things (IoT). The pulse frequency for controlling the battery charge duration is dynamically controlled within a certain range in order to inject the maximum charge current into the battery cells. The optimal frequency is determined in order to minimize battery impedance. The adaptation of the proposed pulse duty and frequency decreases the concentration of the polarization by sensing the runtime characteristics of battery cells so that it guarantees a certain level of safety in charging the distributed battery cells within the operating temperature range of 5–45 °C. The sensed terminal voltage and temperature of battery cells are dynamically monitored while the battery is charging so as to adjust the frequency and duty of the proposed charging pulse method, thereby preventing battery degradation. The evaluation results show that a newly designed charging algorithm for the implemented charger system is about 18.6% faster than the conventional constant-current (CC) charging method with the temperature rise within a reasonable range. The implemented charger system, which is based on the proposed dynamic frequency and duty control by considering the cell polarization, charges to about 80% of its maximum capacity in less than 56 min and involves a 13 °C maximum temperature rise without damaging the battery. Full article

With its large capacity, the total urban rail transit energy consumption is very high; thus, energy saving operations are quite meaningful. The effective use of regenerative braking energy is the mainstream method for improving the efficiency of energy saving. This paper examines the optimization of train dwell time and builds a multiple train operation model for energy conservation of a power supply system. By changing the dwell time, the braking energy can be absorbed and utilized by other traction trains as efficiently as possible. The application of genetic algorithms is proposed for the optimization, based on the current schedule. Next, to validate the correctness and effectiveness of the optimization, a real case is studied. Actual data from the Beijing subway Yizhuang Line are employed to perform the simulation, and the results indicate that the optimization method of the dwell time is effective. Full article

This study describes the performance evaluation of an energy management system, based on electricity consumption, for a Gen 6 Thin Film Transistor Liquid Crystal Display (TFT-LCD) panel plant. Of the various production lines and facility systems, the array system and the compressed dry air consumed the most electricity of 21.8% and 19.8%, respectively, while the public utility used only 1.6% of the total electricity. The baseline electricity consumptions were correlated well (R² ≥ 0.77) to the monthly average wet-bulb temperatures of ambient air and the panel yield rates, which were determined by the product yield over the equipment available time index. After implementing the energy saving projects, the energy conservation performance was determined using a three-parameter change-point regression model incorporated with the panel yield rates. The post-retrofit monthly savings of the total electricity consumption for the panel manufacture were 5.35%–10.36%, with the efficiency of the electricity performance revealing an upswing trend following the implementation of the energy management system. Full article

The quest for single-stage deposition of CuInGaSe₂ (CIGS) is an open race to replace very effective but capital intensive thin film solar cell manufacturing processes like multiple-stage coevaporation or sputtering combined with high pressure selenisation treatments. In this paper the most recent achievements of Low Temperature Pulsed Electron Deposition (LTPED), a novel single stage deposition process by which CIGS can be deposited at 250 °C, are presented and discussed. We show that selenium loss during the film deposition is not a problem with LTPED as good crystalline films are formed very close to the melting temperature of selenium. The mechanism of formation of good ohmic contacts between CIGS and Mo in the absence of any MoSe₂ transition layers is also illustrated, followed by a brief summary of the measured characteristics of test solar cells grown by LTPED. The 17% efficiency target achieved by lab-scale CIGS devices without bandgap modulation, antireflection coating or K-doping is considered to be a crucial milestone along the path to the industrial scale-up of LTPED. The paper ends with a brief review of the open scientific and technological issues related to the scale-up and the possible future applications of the new technology. Full article

The paper presents the results of a transient numerical investigation of the melting and solidification process of sodium nitrate (NaNO₃), which is used as phase change material. For enhancing the heat transfer to the sodium nitrate an aluminum wire matrix is used. The numerical simulation of the melting and solidification process was done with the enthalpy-porosity approach. The numerical analysis of the melting process has shown that apart from the first period of the charging process, where heat conduction is the main heat transfer mechanism, natural convection is the dominant heat transfer mechanism. The numerical investigation of the solidification process has shown that the dominant heat transfer mechanism is heat conduction. Based on the numerical results, the discharging process has been slower than the charging process. The performance of the charged and discharged power has shown that the wire matrix is an alternative method to enhance the heat transfer into the phase change material. Full article

In this paper, it is argued that some low-level aspects of the usual IEC 61850 mapping to Ethernet are not well suited to microgrids due to their dynamic nature and geographical distribution as compared to substations. It is proposed that the integration of IEEE time-sensitive networking (TSN) concepts (which are currently implemented as audio video bridging (AVB) technologies) within an IEC 61850 / Manufacturing Message Specification framework provides a flexible and reconfigurable platform capable of overcoming such issues. A prototype test platform and bump-in-the-wire device for tunneling horizontal traffic through AVB are described. Experimental results are presented for sending IEC 61850 GOOSE (generic object oriented substation events) and SV (sampled values) messages through AVB tunnels. The obtained results verify that IEC 61850 event and sampled data may be reliably transported within the proposed framework with very low latency, even over a congested network. It is argued that since AVB streams can be flexibly configured from one or more central locations, and bandwidth reserved for their data ensuring predictability of delivery, this gives a solution which seems significantly more reliable than a pure MMS-based solution. Full article

Logging residues, which refer to the unused portions of trees cut during logging, are important sources of biomass for the emerging biofuel industry and are critical feedstocks for the first-type biofuel facilities (e.g., corn-ethanol facilities). Logging residues are under-utilized sources of biomass for energetic purposes. To support the scaling-up of the bioenergy industry, it is essential to design cost-effective biofuel supply chains that not only minimize costs, but also consider the biomass quality characteristics. The biomass quality is heavily dependent upon the moisture and the ash contents. Ignoring the biomass quality characteristics and its intrinsic costs may yield substantial economic losses that will only be discovered after operations at a biorefinery have begun. This paper proposes a novel bioenergy supply chain network design model that minimizes operational costs and includes the biomass quality-related costs. The proposed model is unique in the sense that it supports decisions where quality is not unrealistically assumed to be perfect. The effectiveness of the proposed methodology is proven by assessing a case study in the state of Tennessee, USA. The results demonstrate that the ash and moisture contents of logging residues affect the performance of the supply chain (in monetary terms). Higher-than-target moisture and ash contents incur in additional quality-related costs. The quality-related costs in the optimal solution (with final ash content of 1% and final moisture of 50%) account for 27% of overall supply chain cost. Based on the numeral experimentation, the total supply chain cost increased 7%, on average, for each additional percent in the final ash content. Full article

In this work, we propose a Realistic Scheduling Mechanism (RSM) to reduce user frustration and enhance appliance utility by classifying appliances with respective constraints and their time of use effectively. Algorithms are proposed regarding functioning of home appliances. A 24 hour time slot is divided into four logical sub-time slots, each composed of 360 min or 6 h. In these sub-time slots, only desired appliances (with respect to appliance classification) are scheduled to raise appliance utility, restricting power consumption by a dynamically modelled power usage limiter that does not only take the electricity consumer into account but also the electricity supplier. Once appliance, time and power usage limiter modelling is done, we use a nature-inspired heuristic algorithm, Binary Particle Swarm Optimization (BPSO), optimally to form schedules with given constraints representing each sub-time slot. These schedules tend to achieve an equilibrium amongst appliance utility and cost effectiveness. For validation of the proposed RSM, we provide a comparative analysis amongst unscheduled electrical load usage, scheduled directly by BPSO and RSM, reflecting user comfort, which is based upon cost effectiveness and appliance utility. Full article

Fast catalytic pyrolysis of wild reed was carried out at 500 °C. Waste fluidized catalytic cracking (FCC) catalyst disposed from a petroleum refinery process was activated through acetone-washing and calcination and used as catalyst for pyrolysis. In order to evaluate the catalytic activity of waste FCC catalyst, commercial HY zeolite catalyst with a SiO₂/Al₂O₃ ratio of 5.1 was also used. The bio-oil produced from pyrolysis was analyzed using gas chromatography/mass spectrometry (GC/MS). When the biomass-to-catalyst ratio was 1:1, the production of phenolics and aromatics was promoted considerably by catalysis, whereas the content of oxygenates was affected little. Significant conversion of oxygenates to furans and aromatics was observed when the biomass-to-catalyst ratio of 1:10 was used. Activated waste FCC catalyst showed comparable catalytic activity for biomass pyrolysis to HY in terms of the promotion of valuable chemicals, such as furans, phenolics and aromatics. The results of this study imply that waste FCC catalyst can be an important economical resource for producing high-value-added chemicals from biomass. Full article

Radiation forecast accounting for daily and instantaneous variability was pursued by means of a new bi-parametric statistical model that builds on a model previously proposed by the same authors. The statistical model is developed with direct reference to the Liu-Jordan clear sky theoretical expression but is not bound by a specific clear sky model; it accounts separately for the mean daily variability and for the variation of solar irradiance during the day by means of two corrective parameters. This new proposal allows for a better understanding of the physical phenomena and improves the effectiveness of statistical characterization and subsequent simulation of the introduced parameters to generate a synthetic solar irradiance time series. Furthermore, the analysis of the experimental distributions of the two parameters’ data was developed, obtaining opportune fittings by means of parametric analytical distributions or mixtures of more than one distribution. Finally, the model was further improved toward the inclusion of weather prediction information in the solar irradiance forecasting stage, from the perspective of overcoming the limitations of purely statistical approaches and implementing a new tool in the frame of solar irradiance prediction accounting for weather predictions over different time horizons. Full article

This paper presents results from an experiment performed to obtain the dynamic characteristics of a reversible pump-turbine model. The characteristics were measured in an open loop system where the turbine initially was run on low rotational speed before the generator was disconnected allowing the turbine to go towards runaway. The measurements show that the turbine experience damped oscillations in pressure, speed and flow rate around runaway corresponding with presented stability criterion in published literature. Results from the experiment is reproduced by means of transient simulations. A one dimensional analytical turbine model for representation of the pump-turbine is used in the calculations. The simulations show that it is possible to reproduce the physics in the measurement by using a simple analytical model for the pump-turbine as long as the inertia of the water masses in the turbine are modeled correctly. Full article

Three common pretreatments (mechanical, steam explosion and chemical) used to enhance the biodegradability of rice straw were compared on the basis of bio-hydrogen production potential while co-digesting rice straw with sludge under mesophilic (37 °C) and thermophilic (55 °C) temperatures. The results showed that the solid state NaOH pretreatment returned the highest experimental reduction of LCH (lignin, cellulose and hemi-cellulose) content and bio-hydrogen production from rice straw. The increase in incubation temperature from 37 °C to 55 °C increased the bio-hydrogen yield, and the highest experimental yield of 60.6 mL/g VS_removed was obtained under chemical pretreatment at 55 °C. The time required for maximum bio-hydrogen production was found on the basis of kinetic parameters as 36 h–47 h of incubation, which can be used as a hydraulic retention time for continuous bio-hydrogen production from rice straw. The optimum pH range of bio-hydrogen production was observed to be 6.7 ± 0.1–5.8 ± 0.1 and 7.1 ± 0.1–5.8 ± 0.1 under mesophilic and thermophilic conditions, respectively. The increase in temperature was found useful for controlling the volatile fatty acids (VFA) under mechanical and steam explosion pretreatments. The comparison of pretreatment methods under the same set of experimental conditions in the present study provided a baseline for future research in order to select an appropriate pretreatment method. Full article

Numerous industrial applications involve loads that are very sensitive to electrical supply instabilities. These instances involve various types of voltage imbalances as well as more serious disturbances such as symmetrical and asymmetrical faults. This paper proposes a cost-effective voltage imbalance and asymmetrical fault correction solution for the three phase sensitive loads utilizing an industry-standard current regulated voltage source inverter by connecting it in parallel to the grid mains powering to the sensitive load. The inverter regulates the current for the load and never permits it to go beyond a prescribed value under any type of asymmetrical fault condition, which ensures high power regulating and conditioning capacities. Experimental results are obtained from a small laboratory size prototype to validate the operation of the proposed technique. Full article

One of the most relevant challenges that have arisen in electricity markets during the last few years is the emergence of extremely low prices. Trying to predict these events is crucial for market agents in a competitive environment. This paper proposes a novel methodology to simultaneously accomplish punctual and probabilistic hourly predictions about the appearance of extremely low electricity prices in a medium-term scope. The proposed approach for making real ex ante forecasts consists of a nested compounding of different forecasting techniques, which incorporate Monte Carlo simulation, combined with spatial interpolation techniques. The procedure is based on the statistical identification of the process key drivers. Logistic regression for rare events, decision trees, multilayer perceptrons and a hybrid approach, which combines a market equilibrium model with logistic regression, are used. Moreover, this paper assesses whether periodic models in which parameters switch according to the day of the week can be even more accurate. The proposed techniques are compared to a Markov regime switching model and several naive methods. The proposed methodology empirically demonstrates its effectiveness by achieving promising results on a real case study based on the Spanish electricity market. This approach can provide valuable information for market agents when they face decision making and risk-management processes. Our findings support the additional benefit of using a hybrid approach for deriving more accurate predictions. Full article

As data and supercomputing centres increase their performance to improve service quality and target more ambitious challenges every day, their carbon footprint also continues to grow, and has already reached the magnitude of the aviation industry. Also, high power consumptions are building up to a remarkable bottleneck for the expansion of these infrastructures in economic terms due to the unavailability of sufficient energy sources. A substantial part of the problem is caused by current energy consumptions of High Performance Computing (HPC) clusters. To alleviate this situation, we present in this work EECluster, a tool that integrates with multiple open-source Resource Management Systems to significantly reduce the carbon footprint of clusters by improving their energy efficiency. EECluster implements a dynamic power management mechanism based on Computational Intelligence techniques by learning a set of rules through multi-criteria evolutionary algorithms. This approach enables cluster operators to find the optimal balance between a reduction in the cluster energy consumptions, service quality, and number of reconfigurations. Experimental studies using both synthetic and actual workloads from a real world cluster support the adoption of this tool to reduce the carbon footprint of HPC clusters. Full article

This paper studies the scalability and replicability of smart grid projects. Currently, most smart grid projects are still in the R&D or demonstration phases. The full roll-out of the tested solutions requires a suitable degree of scalability and replicability to prevent project demonstrators from remaining local experimental exercises. Scalability and replicability are the preliminary requisites to perform scaling-up and replication successfully; therefore, scalability and replicability allow for or at least reduce barriers for the growth and reuse of the results of project demonstrators. The paper proposes factors that influence and condition a project’s scalability and replicability. These factors involve technical, economic, regulatory and stakeholder acceptance related aspects, and they describe requirements for scalability and replicability. In order to assess and evaluate the identified scalability and replicability factors, data has been collected from European and national smart grid projects by means of a survey, reflecting the projects’ view and results. The evaluation of the factors allows quantifying the status quo of on-going projects with respect to the scalability and replicability, i.e., they provide a feedback on to what extent projects take into account these factors and on whether the projects’ results and solutions are actually scalable and replicable. Full article