The estimation of energy consumption is an important prerequisite for planning the required infrastructure for charging and optimising the schedules of battery electric buses used in public urban transport. This paper proposes a model using a reduced number of readily acquired bus trip parameters: arrival times at the bus stops, map positions of the bus stops and a parameter indicating the trip conditions. A deep learning network is developed for deriving the estimates of energy consumption stop by stop of bus lines. Deep learning networks belong to the important group of methods capable of the analysis of large datasets—“big data”. This property allows for the scaling of the method and application to different sized transport networks. Validation of the network is done using real-world data provided by bus authorities of the town of Jaworzno in Poland. The estimates of energy consumption are compared with the results obtained using a regression model that is based on the collected dat... [more]

The traditional security-constrained optimal power flow (SCOPF) model under the classical N-1 criterion is implemented in the power industry to ensure the secure operation of a power system. However, with increasing uncertainties from renewable energy sources (RES) and loads, the existing SCOPF model has difficulty meeting the practical requirements of the industry. This paper proposed a novel chance-constrained preventive SCOPF model that considers the uncertainty of power injections, including RES and load, and contingency probability. The chance constraint is used to constrain the overall line flow within the limits with high probabilistic guarantees and to significantly reduce the constraint scales. The cumulant and Johnson systems were combined to accurately approximate the cumulative distribution functions, which is important in solving chance-constrained optimization problems. The simulation results show that the model proposed in this paper can achieve better performance than t... [more]

Load switches in power systems may cause oscillations in active and reactive power flow. Such oscillations can be damped by synthetic inertia provided by smart inverters providing power from DC sources such as photovoltaic or battery storage. However, AC current provided by inverters is inherently non-sinusoidal, making measurements of active and reactive power subject to harmonic distortion. As a result, transient effects due to load switching can be obscured by harmonic distortion. An RLC circuit serves as a reference load. The oscillation caused by switching in the load presents as a dual-sideband suppressed-carrier signal. The carrier frequency is available via voltage data but the phase is not. Given a group of candidate signals formed from phase voltages, an algorithm based on Costas Loop that can quickly quantify the phase difference between each candidate and carrier (thus identifying the best signal for demodulation) is presented. Algorithm functionality is demonstrated in the... [more]

The fundamental modeling of energy systems through individual unit commitment decisions is crucial for energy system planning. However, current large-scale models are not capable of including uncertainties or even risk-averse behavior arising from forecasting errors of variable renewable energies. However, risks associated with uncertain forecasting errors have become increasingly relevant within the process of decarbonization. The intraday market serves to compensate for these forecasting errors. Thus, the uncertainty of forecasting errors results in uncertain intraday prices and quantities. Therefore, this paper proposes a two-stage risk-constrained stochastic optimization approach to fundamentally model unit commitment decisions facing an uncertain intraday market. By the nesting of Lagrangian relaxation and an extended Benders decomposition, this model can be applied to large-scale, e.g., pan-European, power systems. The approach is applied to scenarios for 2023—considering a full... [more]

This paper presents a study of the carbon support corrosion and mitigation strategies through the use of a pseudo-3D model. This model consists in coupling a 2D model along the channel with another model perpendicular to the flow at the rib/channel scale. Simulations offer a deeper understanding of the corrosion through the analysis of the local conditions. Rib/channel heterogeneities show the higher degradation in the zones facing the anodic rib. These results are validated qualitatively on literature data by analysis of SEM images and carbon dioxide concentration at the cathode outlet. Three mitigation strategies are studied using the model. The first one consists in speeding up the hydrogen filling of the cell. The second strategy involves an external electrical resistance to create a current leak during the startup. Third, a design study of the rib/channel is performed to minimize the cathode degradation. Whatever the mitigation strategy, it consists in reducing either the duration... [more]

For wide-area measurement systems and smart grids, phasor measurement units (PMUs) have become key elements since they provide synchronized information related to the fundamental frequency components of voltages and currents. In recent years, some works have extended the concept of PMU to harmonic analysis due to the proliferation of nonlinear loads. In this work, as a first contribution, the reference model for P-class and M-class PMUs provided by the IEEE Standard C37.118.1 is expanded with the aim of obtaining the harmonic information and electric power quantities. Additionally, as a second contribution, the approach of global harmonic parameters (GHPs) for PMUs is proposed. Specifically, GHPs are introduced in this work as unified quantities regarding the overall harmonic content of voltages and currents signals. With the help of these parameters, the estimation of power quality indices (PQIs) according to the IEEE Standard 1459 can be carried out but with an important advantage, i... [more]

One of the most important techniques for energy harvesting is the clean energy collection from the ambient vibration. Piezoelectric energy harvesting systems became a hot topic in the literature and attracted most researchers. The reason behind this attraction is that piezoelectric materials are a simple structure and provide a higher power density among other mechanisms (electromagnetic and electrostatic). The aim of this manuscript is to succinctly review and present the state of the art of different existing vibrational applications utilizing piezoelectric energy harvesting technique. Meanwhile, the main concentration is harvesting energy from a vehicle suspension system. There is a significant amount of dissipated energy from the suspension dampers that is worthy of being harvested. Different mathematical car models with their experimental setup are presented, discussed, and compared. The piezoelectric material can be mounted in different locations such as suspension springs, dampe... [more]

In recent years, the tomographic visualization of laminar and turbulent flames has received much attention due to the possibility of observing combustion processes on-line and with high temporal resolution. In most cases, either the spectrally non-resolved flame luminescence or the chemiluminescence of a single species is detected and used for the tomographic reconstruction. In this work, we present a novel 2D emission tomographic setup that allows for the simultaneous detection of multiple species (e.g., OH*, CH* and soot but not limited to these) using a single image intensified CCD camera. We demonstrate the simultaneous detection of OH* (310 nm), CH* (430 nm) and soot (750 nm) in laminar methane/air, as well as turbulent methane/air and ethylene/air diffusion flames. As expected, the reconstructed distributions of OH* and CH* in laminar and turbulent flames are highly correlated, which supports the feasibility of tomographic measurements on these kinds of flames and at timescales d... [more]

This pioneering Special Issue aims at providing the state-of-the-art on open energy data analytics; its availability in the different contexts, i.e., country peculiarities; and at different scales, i.e., building, district, and regional for data-aware planning and policy-making. Ten high-quality papers were published after a demanding peer review process and are commented on in this Editorial.

Thirty-two novel hybrid transmissions consisting of a Ravigneaux gear train and a single planetary gear train are synthesized using a creative design methodology based on graph-theory and the lever analogy method. The design process commences by identifying an existing transmission configuration which meets all of the design requirements. The chosen design is then used to synthesize all possible mechanism permutations which satisfy the design constraints. The feasible mechanisms which satisfy both the design requirements and the design constraints are converted into analogous levers. The levers which fail to provide the required operation modes of the hybrid transmission are eliminated and the remaining levers are assigned brakes and clutches in order to realize the final designs. The responsiveness of the new hybrid transmissions and the feasibility of the proposed design methodology are confirmed by analyzing the power flow and kinematics of one of the designs in all of the operation... [more]

This paper employs the cluster analysis to classify the energy sector into three types, namely, technology-, capital-, and labor-intensive energy company. It then studies the interactive endogenous relationship between R&D investment and financially sustainable performance and the moderate effect of the executive incentive through three-stage least squares (3SLS) of the simultaneous equations model (SEM). The results show that for the technology-intensive energy company, an increase in the previous period in R&D investment improves the current period of financially sustainable performance, and the improvement in the current period in financially sustainable performance results in a decline in financially sustainable performance in the next period, which demands an increase in R&D investment subsequently. In contrast, for the capital-intensive energy company, R&D investment can significantly improve the financially sustainable performance in the current period, and the improvement in fi... [more]

Power distribution networks are vulnerable to different faults, which compromise the grid performance and need to be managed effectively. Automatic and accurate fault detection and location are key components of effective fault management. This paper proposes a new framework for fault detection and location for smart distribution networks that are equipped with data loggers. The framework supports networks with mixed overhead lines and underground cables. The proposed framework consists of area detection, faulty section identification, and high impedance fault location. Firstly, the faulty zone and section are detected based on the operation of over-current relays and digital fault recorders. Then, by comparing the recorded traveling times at both ends of lines, which are related to the protection zone, the faulty line is identified. In the last step, the location of the fault is estimated based on discrete wavelet transform. The proposed method is tested on a 20 kV 13 node network, wh... [more]

The shift-by-wire (SBW) system in vehicles aims to increase performance, safety, and comfort during driving. Switched reluctance motors (SRMs) are simple, resilient, and require only minimum maintenance; these factors make it a good option for use as an SBW actuator. Inherently, SRM generates a higher torque ripple than other AC machines, which can lead to a deterioration of its function. In this paper, a non-uniform air-gap rotor structure combined with the careful positioning of holes near the pole surface is proposed to reduce the torque ripple. The finite element method (FEM) is employed to analyze the electromagnetic characteristics of the design. The proposed motor is manufactured, and experiments are done to verify the performance. The design alone can reduce the torque ripple by 7% and flatten the torque waveform. The experimental result shows that the proposed motor can achieve the desired performance. The estimated torque ripple from the experiment is 26.65%.

This paper analyzes the drivers behind the changes of the Aggregate Carbon Intensity (ACI) of Latin America and the Caribbean (LAC) power sector in five periods between 1990 and 2017. Since 1990 the carbon intensity of the world has been reduced almost 8.8% whereas the carbon intensity of LAC countries only decreased 0.8%. Even though by 2017 the regional carbon intensity is very similar to the one observed by 1990, this index has showed high variability, mainly in the last three years when the ACI of LAC fell from 285 gCO2/kWh in 2015 to 257.7 gCO2/kWh. To understand what happened with the evolution of the carbon intensity in the region, in this paper a Logarithmic Mean Divisia for Index Decomposition Analysis (IDA-LMDI) is carried out to identify the accelerating and attenuating drivers of the ACI behavior along five periods. The proposal outperforms existing studies previously applied to LAC based upon a single period of analysis. Key contributions are introduced by considering the... [more]

Borehole thermal energy storage (BTES) systems facilitate the subsurface seasonal storage of thermal energy on district heating scales. These systems’ performances are strongly dependent on operational conditions like temperature levels or hydraulic circuitry. Preliminary numerical system simulations improve comprehension of the storage performance and its interdependencies with other system components, but require both accurate and computationally efficient models. This study presents a toolbox for the simulation of borehole thermal energy storage systems in Modelica. The storage model is divided into a borehole heat exchanger (BHE), a local, and a global sub-model. For each sub-model, different modeling approaches can be deployed. To assess the overall performance of the model, two studies are carried out: One compares the model results to those of 3D finite element method (FEM) models to investigate the model’s validity over a large range of parameters. In a second study, the accura... [more]

The primary regulation of photovoltaic (PV) systems is a current matter of research in the scientific community. In Grid-Feeding operating mode, the regulation aims to track the maximum power point in order to fully exploit the renewable energy sources and produce the amount of reactive power ordered by a hierarchically superior control level or by the local Distribution System Operator (DSO). Actually, this task is performed by Proportional−Integral−Derivative (PID)-based regulators, which are, however, affected by major drawbacks. This paper proposes a novel control architecture involving advanced control theories, like Model Predictive Control (MPC) and Sliding Mode (SM), in order to improve the overall system performance. A comparison with the conventional PID-based approach is presented and the control theories that display a better performance are highlighted.

In this case study, the energy performance of a secondary school building from the 1960s in Gävle, Sweden, was modelled in the building energy simulation (BES) tool IDA ICE version 4.8 prior to major renovation planning. The objectives of the study were to validate the BES model during both occupied and unoccupied periods, investigate how to model airing and varying occupancy behaviour, and finally investigate energy use to identify potential energy-efficiency measures. The BES model was validated by using field measurements and evidence-based input. Thermal bridges, infiltration, mechanical ventilation, domestic hot water circulation losses, and space heating power were calculated and measured. A backcasting method was developed to model heat losses due to airing, opening windows and doors, and other occupancy behaviour through regression analysis between daily heat power and outdoor temperature. Validation results show good agreement: 3.4% discrepancy between space heating measuremen... [more]

This article presents a method for selecting the elements of a C-type filter working with a conventional LC-type filter for compensating reactive power and filtering out higher harmonics generated by arc furnaces and ladle furnaces. The study was conducted in a steel mill supplied by a 110 kV transmission system, where higher harmonic currents and nonlinear loads were measured. A series of computer simulations were performed under various operating conditions, and an algorithm for selecting the parameters of a third-order C-type filter (for suppressing the second harmonic) and two second-order LC-type filters (for suppressing the third harmonic) was proposed. The filtering system was tested in an arc furnace with the highest rated power, and harmonics in the current spectrum were evaluated. The results of the measurements were used to analyze the effectiveness of the compensation system comprising two passive C-type and LC-type filters at different system configurations. C-type filters... [more]

Disproportionation and phase separation are big issues that occur under extreme pressure and temperature conditions during hydrogen compressor cycles, which makes metal hydrides inactive and reduces compression efficiency. It is important to identify boundary conditions to avoid such unwanted phase separation. However, no investigation related to this problem has been carried out so far. Thus we propose a method to investigate the critical temperature and pressure condition for the alloy degradation during the hydrogen compressor cycle. The V20Ti32Cr48 alloy was chosen as a model system for the purpose. The influence of two important parameters (i.e., hydrogen content and temperature) was investigated individually. The disproportionation of V20Ti32Cr48 alloy during the hydrogen compressor cycle test occurred at temperatures higher than 200 °C and 75% H2 content of the total capacity at the initial condition. A clear and obvious boundary condition between disproportionation and keeping... [more]

The bioethanol sector is an extremely complex set of actors, technologies and market structures, influenced simultaneously by different natural, economic, social and political processes. That is why it lends itself to the application of system dynamics modelling. In last five years a relatively high level of experience and knowledge has accumulated related to the application of computer-aided system modelling for the analysis and forecasting of the bioethanol sector. The goal of the current paper is to offer a systematic review of the application of system dynamics models in order to better understand the structure, conduct and performance of the bioethanol sector. Our method has been the preferred reporting items for systematic reviews and meta-analyses (PRISMA), based on English-language materials published between 2015 and 2020. The results highlight that system dynamic models have become more and more complex, but as a consequence of the improvement in information technology and st... [more]

Double-oxide Mn3O4-Co3O4 nanoparticles were synthesized and anchored on multiwalled carbon nanotubes (MWCNTs) via a single-step solvothermal method. The largest specific area (99.82 m2g−1) of the catalyst was confirmed via a nitrogen adsorption isotherm. Furthermore, the uniform coating of the Mn3O4-Co3O4 nanoparticles on the surface of the MWCNTs was observed via scanning electron microscopy and transmission electron microscopy; the uniform coating provided an effective transport pathway during the electrocatalytic activities. The rotating disk electrode and rotating ring disk electrode measurements indicated that the electron transfer number was 3.96 and the evolution of H2O2 was 2%. In addition, the Mn3O4-Co3O4/MWCNT catalyst did not undergo urea poisoning and remained stable in an alkaline solution. Conversely, commercial Pt/C could not withstand urea poisoning for long. The performance cell achieved a power density of 0.4226 mW cm−2 at 50 °C. Therefore, Mn3O4-Co3O4/MWCNT is an eff... [more]

Building energy code compliance is the crucial link between the actual energy savings and the efficiency prescribed in energy codes. A research project aiming to identify opportunities to reduce energy consumption in new single-family residential construction by increasing compliance with the building energy code was conducted in several states of the United States. The study was comprised of three phases: (1) a baseline study to document typical practice and identify opportunities for improvement based on empirical data gathered from the field; (2) an education and training phase targeting the opportunities identified; and (3) a post-study to assess whether a reduction in average state-wide energy use could be achieved following the education and training phase. We proposed a novel methodology based on large-scale building energy simulation inferred by limited field data to assess the performance of a large population of homes. This paper presents the methodology, findings, and result... [more]

For a wind turbine to extract as much energy as possible from the wind, blade geometry optimization to maximize the aerodynamic performance is important. Blade design optimization includes linearizing the blade chord and twist distribution for practical manufacturing. As blade linearization changes the blade geometry, it also affects the aerodynamic performance and load characteristics of the wind turbine rotor. Therefore, it is necessary to understand the effects of the design parameters used in linearization. In this study, the effects of these parameters on the aerodynamic performance of a wind turbine blade were examined. In addition, an optimization algorithm for linearization and an objective function that applies multiple tip speed ratios to optimize the aerodynamic efficiency were developed. The analysis revealed that increasing the chord length and chord profile slope improves the aerodynamic efficiency at low wind speeds but lowers it at high wind speeds, and that the twist p... [more]

Increase in global energy demand and constraints from fossil fuels have encouraged a growing share of renewable energy resources in the utility grid. Accordingly, an increased penetration of direct current (DC) power sources and loads (e.g., solar photovoltaics and electric vehicles) as well as the necessity for active power flow control has been witnessed in the power distribution networks. Passive transformers are susceptible to DC offset and possess no controllability when employed in smart grids. Solid state transformers (SSTs) are identified as a potential solution to modernize and harmonize alternating current (AC) and DC electrical networks and as suitable solutions in applications such as traction, electric ships, and aerospace industry. This paper provides a complete overview on SST: concepts, topologies, classification, power converters, material selection, and key aspects for design criteria and control schemes proposed in the literature. It also proposes a simple terminolog... [more]

(1) Background: Forecasting of energy consumption demand is a crucial task linked directly with the economy of every country all over the world. Accurate natural gas consumption forecasting allows policy makers to formulate natural gas supply planning and apply the right strategic policies in this direction. In order to develop a real accurate natural gas (NG) prediction model for Greece, we examine the application of neuro-fuzzy models, which have recently shown significant contribution in the energy domain. (2) Methods: The adaptive neuro-fuzzy inference system (ANFIS) is a flexible and easy to use modeling method in the area of soft computing, integrating both neural networks and fuzzy logic principles. The present study aims to develop a proper ANFIS architecture for time series modeling and prediction of day-ahead natural gas demand. (3) Results: An efficient and fast ANFIS architecture is built based on neuro-fuzzy exploration performance for energy demand prediction using histor... [more]