In response to the inherent challenges of generating cost-effective electricity consumption schedules for dynamic systems, this paper espouses the use of GBM or Gradient Boosting Machine-based models for electricity price forecasting. These models are applied to data streams from the Irish electricity market and achieve favorable results, relative to the current state-of-the-art. Presently, electricity prices are published 10 h in advance of the trade day of interest. Using the forecasting methodology outlined in this paper, an estimation of these prices can be made available one day in advance of the official price publication, thus extending the time available to plan electricity utilization from the grid to be as cost effectively as possible. Extreme Gradient Boosting Machine (XGBM) models achieved a Mean Absolute Error (MAE) of 9.93 for data from 30 September 2018 to 12 December 2019 which is an 11.4% improvement on the avant-garde. LGBM models achieve a MAE score 9.58 on more rece... [more]

Low-emissivity (low-E) window films are designed to improve the thermal comfort and energy performance of buildings. These films can be applied to different glazing systems without having to change the whole window. This makes it possible to apply films to windows in old and historical buildings for which preservation regulations often require that windows should remain unchanged. This research aims to investigate the impacts of low-E window films on the energy performance and thermal comfort of a three-story historical stone building in the cold climate of Sweden using the simulation software “IDA ICE”. On-site measurements were taken to acquire thermal and optical properties of the windows. This research shows that the application of the low-emissivity window film on the outward-facing surface of the inner pane of the double-glazed windows helped to reduce heat loss through the windows in winter and unwanted heat gains in summer by almost 36% and 35%, respectively. This resulted in a... [more]

In this study, modern nitrogen steels used for the manufacture of rings for Honda engines (70CC, 90CC, CRF70F, XL70, XR70, C70, CT70, ATC70, CL70) as well as other transport tribotechnical units was investigated. Due to the present ecological situation in the world, new environmentally friendly lubricating fluids for nitrogen steels’ tribotechnical units and surface treatments have been proposed. The results of tribotechnical tests are presented in the form of diagrams, graphs and step polynomials obtained by mathematically describing the changes in wear intensity when the load changes for different lubricating fluids. Friction pairs were compared with ShellHF-E 46 (synthetic lubricating fluid), ShellHF-R (biological origin) and lubricating and cooling liquids with 1%, 3% and 5% vegetable oil concentrations. In tribocoupling it was found that hydrogen diffuses into the metal because the tribodestruction of lubricating coolants plays an active role in the destruction of friction surface... [more]

In the transportation sector, electric battery bus (EBB) deployment is considered to be a potential solution to reduce global warming because no greenhouse gas (GHG) emissions are directly produced by EBBs. In addition to the required charging infrastructure, estimating the energy consumption of buses has become a crucial precondition for the deployment and planning of electric bus fleets. Policy and decision-makers may not have the specific tools needed to estimate the energy consumption of a particular bus network. Therefore, many state-of-the-art studies have proposed models to determine the energy demand of electric buses. However, these studies have not critically reviewed, classified and discussed the challenges of the approaches that are applied to estimate EBBs’ energy demands. Thus, this manuscript provides a detailed review of the forecasting models used to estimate the energy consumption of EBBs. Furthermore, this work fills the gap by classifying the models for estimating E... [more]

In the geyser boiling mode, the working fluid state is divided into a boiling process and a quiet process, and the sodium-potassium (Na-K) alloy heat pipe can discontinuously transfer heat at each boiling. The overheating of the liquid working fluid at the bottom causes short-term boiling and forms slug bubble, the strong condensing ability quickly conducts heat from the evaporator section. And geyser boiling can occur before the working fluid forms continuous flow, so it transfers more heat at lower temperatures than natural convection cooling. In this study, the heat transfer process of a Na-K alloy heat pipe with forced convection cooling under different heating power was experimental studied. The geyser boiling mode can make the Na-K alloy heat pipe work below 650 °C and reduce the start-up time. In the process of geyser boiling, the heat transfer quantity was increased by the boiling frequency and the amount of vapor produced in a single boiling. The boiling temperature had no obv... [more]

This paper presents the testing campaign of the two First Wall mock-ups in the HELOKA facility, one mock-up having a 3 mm thick Oxide Dispersion Strengthened (ODS) steel layer on its surface and the other featuring a tungsten functionally graded cover. Special consideration is given to the diagnostics used for these tests, in particular, the measurement of the surface temperature of the tungsten functionally graded layer with an infrared camera. Additionally, the paper looks into the uncertainty associated with the calorimetric evaluation of the applied heating power for these experiments.

Forecasting Photovoltaic (PV) energy production, based on the last weather and power data only, can obtain acceptable prediction accuracy in short-time horizons. Numerical Weather Prediction (NWP) systems usually produce free forecasts of the local cloud amount each 6 h. These are considerably delayed by several hours and do not provide sufficient quality. A Differential Polynomial Neural Network (D-PNN) is a recent unconventional soft-computing technique that can model complex weather patterns. D-PNN expands the n-variable kth order Partial Differential Equation (PDE) into selected two-variable node PDEs of the first or second order. Their derivatives are easy to convert into the Laplace transforms and substitute using Operator Calculus (OC). D-PNN proves two-input nodes to insert their PDE components into its gradually expanded sum model. Its PDE representation allows for the variability and uncertainty of specific patterns in the surface layer. The proposed all-day single-model and... [more]

Regulating the frequencies of power grids by controlling electric vehicle charging and discharging, known as vehicle-to-grid (V2G) ancillary services, is a promising and profitable means of providing flexibility that integrates variable renewable energy (VRE) into traditional power systems. However, the ancillary services market is a niche, and the scale, saturation, and time-dependency are unclear when assuming future changes in the power system structure. We studied the marginal value of V2G ancillary services as a balancing capacity of the power system operation on the load-frequency control (LFC) timescale and evaluated the reasonable maximum capacity of the LFC provided by V2G. As a case study, we assumed that the Japanese power system would be used under various VRE penetration scenarios and considered the limited availability time of V2G, based on the daily commuter cycle. The power system operation was modeled by considering pumped storage, interconnection lines, and thermal po... [more]

The largest companies that are part of the energy sector are defined by Forbes as those associated with the production of energy from nonrenewable sources and they play a very significant role in the world economy and in the generation of the command and control (C & C) function of cities. No comprehensive studies are available at the present time illustrating changes in financial performance in relation to the share of the largest firms in the energy sector in terms of their role in the generation of the C & C function. Thus, the aim of the paper is to show changes in financial performance and the impacts of energy sector companies on the C & C function of cities as well as to show spatial variances in the sector’s geography. The energy sector is developing most rapidly in Chinese cities, although it does not play a major role in the most important cities in the world via its impact on the C & C function—this may be due to rapid growth in other sectors of the economy. It is, however,... [more]

The design of monopile foundations for offshore wind turbines is most often driven by fatigue. With the foundation price contributing to the total price of a turbine structure by more than 30%, wind farm operators seek to gain knowledge about the amount of consumed fatigue. Monitoring concepts are developed to uncover structural reserves coming from conservative designs in order to prolong the lifetime of a turbine. Amongst promising concepts is a wide array of methods using in-situ measurement data and extrapolating these results to desired locations below water surface and even seabed using models. The modal decomposition algorithm is used for this purpose. The algorithm obtains modal amplitudes from acceleration and strain measurements. In the subsequent expansion step these amplitudes are expanded to virtual measurements at arbitrary locations. The algorithm uses a reduced order model that can be obtained from either a FE model or measurements. In this work, operational modal analy... [more]

The resilience of a system can be considered as a function of its reliability and recoverability. Hence, for effective resilience management, the reliability and recoverability of all components which build up the system need to be identified. After that, their importance should be identified using an appropriate model for future resource allocation. The critical infrastructures are under dynamic stress due to operational conditions. Such stress can significantly affect the recoverability and reliability of a system’s components, the system configuration, and consequently, the importance of components. Hence, their effect on the developed importance measure needs to be identified and then quantified appropriately. The dynamic operational condition can be modeled using the risk factors. However, in most of the available importance measures, the effect of risk factors has not been addressed properly. In this paper, a reliability importance measure has been used to determine the critical... [more]

Deployment of CTA-2045−enabled devices is increasing in the U.S. market. These devices allow utilities or third-party aggregators to control appliance energy use in homes, and could also be applied to end uses in small commercial buildings. This study focuses on a field study using CTA-2045−enabled water heaters to shift electric load off the peak and toward periods when renewable resources are more prevalent (e.g., near noon for solar resources and near midnight for wind resources). The following load shifting strategies were compared to understand effects on the aggregate load-shifting capabilities of Heat Pump Water Heaters (HPWHs) and on consumer hot water supply: non-targeted (traditional), targeted (grouped, with different shifting schedules) and “smart” (adaptive control commands). The results of this study show that targeted and smart control strategies yield significantly more load-shifting potential from a population of water heaters than the non-targeted approach without sac... [more]

Compensation of data loss in the state estimation plays an indispensable role in efficient and stable control and communication systems. However, accurate compensation of data loss in the state estimation is extremely challenging issue. To cater this challenging issue, two techniques such as the open-loop Kalman filter and the compensating closed-loop Kalman filter have emerged. The closed-loop technique compensates for the missing data using the autoregressive model. However, the autoregressive model used only past measurements for data loss compensation. Considering only one parameter, i.e., the past measurements, is insufficient and leads to inaccurate state estimation. Thus, in this work, autoregressive moving average with exogenous inputs model considers three parameters, i.e., the past measurements, the input signal, and the sensor noise, simultaneously to compensate data loss in state estimation. To endorse the effectiveness and applicability of the proposed model, a standard ma... [more]

This paper presents a novel approach for improving the safety of vehicles equipped with Adaptive Cruise Control (ACC) by making use of Machine Learning (ML) and physical knowledge. More exactly, we train a Soft Actor-Critic (SAC) Reinforcement Learning (RL) algorithm that makes use of physical knowledge such as the jam-avoiding distance in order to automatically adjust the ideal longitudinal distance between the ego- and leading-vehicle, resulting in a safer solution. In our use case, the experimental results indicate that the physics-guided (PG) RL approach is better at avoiding collisions at any selected deceleration level and any fleet size when compared to a pure RL approach, proving that a physics-informed ML approach is more reliable when developing safe and efficient Artificial Intelligence (AI) components in autonomous vehicles (AVs).

Multiple microgrids (MGs) close to each other can be interconnected to construct a cluster to enhance reliability and flexibility. This paper presents a comprehensive and comparative review of recent studies on DC MG clusters’ control strategies. Different schemes regarding the two significant control aspects of networked DC MGs, namely DC-link voltage control and power flow control between MGs, are investigated. A discussion about the architecture configuration of DC MG clusters is also provided. All advantages and limitations of various control strategies of recent studies are discussed in this paper. Furthermore, this paper discusses three types of consensus protocol with different time boundaries, including linear, finite, and fixed. Based on the main findings from the reviewed studies, future research recommendations are proposed.

Energy-saving and efficiency represent a crucial role in achieving a clean environment as well as economic and social development, providing substantial benefits to stakeholders, including householders. Better cost savings can be achieved by simply changing behavior. However, real energy users lack proper technical energy knowledge, awareness, and education in most cases. In most countries, women are involved in a higher percentage of energy activities in household chores but have less gender participation in energy decisions. In this regard, a gender perspective effectively understands energy users’ pragmatic and strategic needs for energy-saving behavior improvement. Previous literature reviews have been focusing on specific aspects of energy sustainability; however, no review has focused on energy-saving from a gender perspective to the best of our knowledge. It aims to provide a systematic review of literature on energy-saving and management, highlighting the importance of gender r... [more]

The poor indoor air quality (IAQ) of severely polluted toilets is associated with increased risk of severe disease. This study aimed to evaluate the overall IAQ according to the contaminant removal efficiency, volume average concentration, and breathing zone control level. The characteristics of contaminant transmission in a non-flushing ecological toilet (NFET) were analyzed using the computational fluid dynamics (CFD) methodology, and the proposed model was further validated based on experimental measurements. Both an orthogonal experimental design and CFD were used to analyze factors such as exhaust fan position (EFP), air change rate per hour (ACH), natural vent location (NVL), and grid height (G-h). The EFP and ACH were demonstrated to be the dominant factors affecting the IAQ, whereas NVL and G-h were found to play key roles. Single-factor analysis based on the significance levels of the ACH, EFP, and NVL was conducted using the CFD methodology to define three exhaust behaviors—n... [more]

The decline in small towns is a concern in many countries. The manufacturing and tourism sectors are considered to be important in the revitalisation of towns but could be subject to ‘Dutch disease’. This is a malady in which success in one sector leads to a decline in the other. The importance of, and relationships between, the manufacturing and tourism sectors of more than 500 United States micropolitan statistical areas (micropolitans) were extensively investigated by following settlement scaling theory. Publicly available 2016 datasets were used to test a hypothesis that Dutch disease between the two sectors is important. Both sectors are present and important in virtually all of the micropolitans. Regression analyses, including log−log (power-law) analyses, were used to examine the population-based and enterprise-based orderliness in the micropolitan demographic−socioeconomic−entrepreneurial nexus. There is much orderliness, and non-linear relationships are prevalent. No evidence... [more]

Energy efficiency generally implies the efficient use of energy in all sectors of final consumption—industry, services, agriculture, households and transport. Shipping accounts for nearly 3% of global greenhouse gas emissions, making it the sixth largest CO2 producer in the world. This is a result of inefficient ship design, lack of planning and optimal use of resources. As the transport sector expands, so does the pressure for a greener and cleaner maritime industry. Reducing fuel consumption is a major driver of the need for energy efficiency on ships. In this paper, due to the importance of maritime transport, we observed the impact of reducing the dimensions of the main switchboard as a contribution to energy efficiency. This contribution is not of great importance as is the case with the optimization of the navigation route, etc., but it certainly affects the weight and, thus, the fuel consumption, which contributes to energy efficiency in the designed system. The aim of this pape... [more]

Deadbeat predictive current control (DBPCC) has the characteristic of fast current response, but it is sensitive to motor parameters. Observer-based DBPCC can eliminate the steady state current tracking error when parameter mismatch exists. However, the actual current will deviate from the reference current during transient state in the case of inductance mismatch. In this paper, a fast response robust deadbeat predictive current control (FRRDBPCC) method is proposed for surface mounted permanent magnet synchronous motor (SPMSM). Firstly, the current tracking error caused by inductance mismatch during transient state is analyzed in detail. Then, an extended state observer (ESO) is proposed to estimate the lumped disturbance caused by parameter mismatch. Based on discrete time ESO, the predicted currents are used to replace the sampled currents to compensate for one-step delay caused by calculation and sampling. Furthermore, an online inductance identification algorithm and a modified p... [more]

This investigation aims to model and assess the wind potential available in seven specific regions of North Algeria. These regions, i.e., Batna, Guelma, Medea, Meliana, Chlef, Tiaret, and Tlemcen, are known for their traditional agriculture. The wind data are obtained from the National Agency of Meteorology (NAM), and a Weibull distribution is applied. In the first part of this study, the wind potential available in these sites is assessed. Then, different models are used to estimate the wind system’s annual recoverable energy for these regions. We are interested in wind pumping for possible use to meet the needs of irrigation water in rural areas. Four kinds of wind turbines are explored to determine the possibility of wind energy conversion. In addition, the effects of the heights of the pylon holding the turbines are inspected by considering four cases (10, 20, 40, and 60 m). This estimation showed that the annual mean wind velocity varies from 2.48 to 5.60 m/s at a level of 10 m. T... [more]

The expansion of electric vehicles made the expansion of charging infrastructure rudimentary to keep up with this developing technology that helps people in a myriad of ways. The main drawback in electric vehicle charging, however, is the time consumed to charge a vehicle. The fast charging of electric vehicles solves this problem thus making it a lucrative technology for consumers. However, the fast charging technology is not without its limitations. In this paper we have identified the technology gaps in EV fast charging stations mostly focused on the extremely fast charging topology. It will help pave a path for researchers to direct their effort in a consolidated manner to contribute to the fast charging infrastructure. A thorough review of all aspects and limitations of existing extremely fast charging (XFC) stations have been identified and supporting data are provided. The importance of DC power network based on free fuel energy sources and silicon carbide-based power electronic... [more]

The various measurement procedures for determination of electromagnetic parameters for the induction motor (IM) equivalent circuits including the rotor deep-bar effect were proposed in the literature. One of them is the procedure based on the load curve test (LCT). Since the execution of the LCT can pose some difficulties, especially in industrial conditions, as an alternative, the finite element method (FEM) can be employed to simulate the IM operation under the LCT. In this work we developed the optimisation technique for the finite element (FE) model. This technique is performed with the use of the stator current space-vector components which determine the IM input active and reactive power consumption during no-load operation. Relying on the LCT simulation carried out with the optimised FE model the inductance frequency characteristic can be determined and then used as the reference characteristic in the electromagnetic parameter estimation for the IM equivalent circuit including t... [more]

Rotary kiln incineration technology has the advantages of strong material adaptability and a simple treatment process and has been widely used in hazardous waste treatment. However, the actual incineration process has caused problems such as ring formation in the treatment system due to the lack of research on the slagging mechanisms. In this paper, slagging phenomena occurring in the second half of the rotary kiln, the exit flue of the secondary combustion chamber, and the wall of the quench tower are analyzed and discussed in detail through characterization methods. The results indicate that the adhesion of low-melting alkali metal salts on the refractory surface in the second half of the rotary kiln is the key factor in forming the initial slagging layer. In the growth process of the slagging ring, the formed liquid phase can bond incineration residues of different sizes together and form a dense embryo body through liquid phase sintering. The deposition and solidification of molten... [more]

The conductive components of the pyro-breaker in the quench protection system (QPS) have high current density, a large number of electrical contacts and high thermal flux. The water system needs to meet the requirements of cooling and arc extinguishing at the same time. In a previous study, the bottleneck of the steady-state capacity appeared in the barrel conductor of the commutation section, which has a cylindrical cavity. The thermal stability of the commutation section at 100 kA level was simulated in ANSYS/Workbench. The results indicate a certain level of enhancement of the convective heat transfer coefficient of the cavity is required to reach the current capacity. However, the fluid flow inside the cavity is very complex, and the convective heat transfer coefficient is difficult to calculate. In this paper, Computational fluid dynamics (CFD) is applied to the optimization of the cooling water system of the pyro-breaker. By studying the enhancement method of convective heat tran... [more]