As the time spent by people indoors continues to significantly increase, much attention has been paid to indoor air quality. While many IAQ studies have been conducted through field measurements, the use of data-driven techniques such as machine learning has been increasingly used for the prediction of indoor air pollutants. For the present study, the concentrations of indoor air pollutants such as CO2, PM2.5, and VOCs in child daycare centers were predicted by using an artificial neural network model with three different training algorithms including Levenberg−Marquardt, Bayesian regularization, and Broyden−Fletcher−Goldfarb−Shanno quasi-Newton methods. For training and validation, data of indoor pollutants measured in child daycare facilities over a 1-month period were used. The results showed all the models produced a good performance for the prediction of indoor pollutants compared with the measured data. Among the models, the prediction by the LM model met the acceptable criteria... [more]

In this study, to use carbon nanotubes (CNTs) as a conductive material instead of carbon black in cathode electrodes, their dispersions were prepared in 1-Methyl-2-pyrrolidinone (NMP) solvent by using an ultrasonic horn, and their dispersion stability was analyzed using CNTs on the formation of the network between cathode electrode constituent materials comprised of cathode material, CNTs, and current collectors, and their correlation with electrochemical performance results were investigated using various analytical techniques. Particularly, in the analysis, terahertz time domain spectroscopy (THz-TDS), a new non-destructive analysis method, was used to analyze and compare the various optical properties of the cathode’s slurries that co-existed with CNTs and cathode material, suggesting the suitability of its analytical use in the field of materials dispersion and the slurry manufacturing process for lithium-ion batteries (LIBs). In the investigated results, the sample with the highes... [more]

This paper presents an analysis of the literature that studies the possibility of sewage sludge being used in the cement industry to reduce carbon dioxide emissions from cement production and thus solve the problem of disposing of sewage sludge so that it is no longer stored, avoiding soil pollution with heavy metals, and reducing pressure on the environment. The ash of sewage sludge is a good pozzolanic material, because when it is finely ground, it can be used as a partial substitute for Portland cement. This reduces waste storage costs. Sewage sludge ash was mixed with cement, and it was analyzed to determine whether the paste obtained could be used as a raw material in the cement industry. The presented results are on the hydration characteristics of the sewage sludge ash, the compressive strength of the cement determined after different days, the workability of the cement, and the porosity of the cement paste and the ash.

Mitigating haze pollution is of practical significance to the green economy, and the development of digital finance may help achieve this goal. However, the effect of digital finance on haze pollution has not been systematically explained. Based on Chinese prefectural panel data for the 2011−2016 period, this study on haze concentration, technological innovation, and digital inclusive finance index as the dependent variable, mediating variable, and the core independent variable, respectively, investigated whether digital finance has improved haze pollution control in China using fixed effect (FE) and random effect (RE) models, a mediating effect model, a threshold panel model, and a dynamic spatial Durbin model (SDM). Four key results were obtained. (1) Digital finance significantly decreased haze pollution. After accounting for potential endogeneity, this conclusion was still valid. (2) The analysis of the influencing mechanism showed that digital finance was conducive to haze reducti... [more]

There are myriad questions that remain to be answered in greenhouse gas (GHG) emissions trading. This article addresses carbon dioxide (CO2) emission factors and carbon losses from heavy equipment that is used to transport ores. Differences occurred between the Intergovernmental Panel for Climate Change (IPCC) emission factor and those that were obtained by considering incomplete combustion and on-site exhaust concentration measurements. Emissions from four off-road vehicles were analyzed. They operated at idle (loading, unloading, and queuing) and in motion (front and rear, loaded and unloaded). The results show that the average CO2 emission factors can be as low as 64.8% of the IPCC standard value for diesel fuel. On the other hand, carbon losses can be up to 33.5% and energy losses up to 25.5%. To the best of the authors’ knowledge, the method that was developed here is innovative, simple, useful, and easily applicable in determining CO2 emission factors and fuel losses for heavy ma... [more]

Lithium-ion battery devices are essential for energy storage and supply in distributed energy generation systems. Robust battery management systems (BMSs) must guarantee that batteries work within a safe range and avoid the damage caused by overcharge and overdischarge. The state-of-charge (SoC) of Li-ion batteries is difficult to observe after batteries are manufactured. The hysteresis phenomenon influences the existing battery modeling and SoC estimation accuracy. This research applies a terminal sliding mode observer (TSMO) algorithm based on a hysteresis resistor-capacitor (RC) equivalent circuit model to enable accurate SoC estimation. The proposed method is evaluated using two dynamic battery tests: the dynamic street test (DST) and the federal urban driving schedule (FUDS) test. The simulation results show that the proposed method achieved high estimation accuracy and fast response speed. Additionally, real-time battery information, including battery output voltage and SoC, was... [more]

Fluctuations in renewable energy production, especially from solar and wind plants, can be solved by large-scale energy storage. One of the possibilities is storing energy in the form of hydrogen or methane−hydrogen blends. A viable alternative for storing hydrogen in salt caverns is Lined Rock Cavern (LRC) underground energy storage. One of the most significant challenges in LRC for hydrogen storage is sealing liners, which need to have satisfactory sealing and mechanical properties. An experimental study of hydrogen permeability of different kinds of polymers was conducted, followed by modeling of hydrogen permeability of these materials with different additives (graphite, halloysite and fly ash). Fillers in polymers can have an impact on the hydrogen permeability ratio and reduce the amount of polymer required to make a sealing liner in the reservoir. Results of this study show that hydrogen permeability coefficients of polymers and estimated hydrogen leakage through these materials... [more]

With the increasing need for cooling and the concerns for pollution due to fossil fuel-based energy use, renewable energy is considered an add-on to cooling technologies. The climatic condition in the Middle East, analyzed in this paper, provides the potential to integrate solar energy with the cooling system. Due to the availability of various solar energy and cooling technologies, multiple configurations of solar-cooling systems can be considered to satisfy the cooling demand. The research presented in this paper aims to assess and compare these configurations by considering the energy prices and the installation area. The proposed model is formulated in Mixed-Integer Linear Programming and optimizes the holistic system design and operation. The economic, renewable energy use, and environmental performances of the optimal solution for each configuration are analyzed and compared to the base grid-DCS configuration. Results show that the electricity tariff and the available installatio... [more]

This article aims to present changes in the use of electricity by service companies, resulting from regulations within the framework of increasing energy efficiency from the perspective of the implementation of the European Green Deal strategy. To achieve the above goal, the following research question was formulated: to what extent did the COVID-19 pandemic affect the implementation of energy transformation and electricity consumption among the surveyed group of recipients? It should be noted that, so far in the global environment, more and more electricity has been used every year, and this tendency is still continuous and growing. Therefore, in European Union countries, measures have been taken to balance demand and its rational use, resulting from the implementation of the European Green Deal strategy. According to the strategic goal of the indicated policy, EU countries are obliged to implement a sequence of actions enabling their transformation into a modern, resource-efficient,... [more]

Lithium-ion batteries exhibit a dynamic voltage behaviour depending nonlinearly on current and state of charge. The modelling of lithium-ion batteries is therefore complicated and model parametrisation is often time demanding. Grey-box models combine physical and data-driven modelling to benefit from their respective advantages. Neural ordinary differential equations (NODEs) offer new possibilities for grey-box modelling. Differential equations given by physical laws and NODEs can be combined in a single modelling framework. Here we demonstrate the use of NODEs for grey-box modelling of lithium-ion batteries. A simple equivalent circuit model serves as a basis and represents the physical part of the model. The voltage drop over the resistor−capacitor circuit, including its dependency on current and state of charge, is implemented as a NODE. After training, the grey-box model shows good agreement with experimental full-cycle data and pulse tests on a lithium iron phosphate cell. We test... [more]

Worldwide, in the rotary kilns of cement plants, various amounts of combustible waste are burned, which would otherwise end up in municipal landfills. The paper first analyzes the literature on the co-processing of waste in cement manufacture and its influence on the environment and human health. Then, it shows how the combustion components of co-processed waste can influence the final characteristics of clinker and cement. The main objective of the paper is to determine the level of emissions of the resulting pollutants (total dust and flue gases: NOx, SO2, and CO) at the outlet of the chimney of the clinker kiln and flour mill to meet the requirements of the Integrated Environmental Permit (EIA) from Romania and present an estimation of the level of atmospheric air pollution using the climatological model of pollutant dispersion. Following these assessments (data shown), the cement factories will establish measures to reduce the pollution, if necessary, to comply with the regulations... [more]

This paper proposes a rational approximation-based approach to find positive real parameters for the extended Debye model (EDM), aimed at condition assessment of insulation systems of power transformers. The EDM can model the slow and fast polarization phenomenon, including relaxation mechanisms with different relaxation times within a composite dielectric material. In the proposed approach, the complex permittivity of the transformer’s composite insulation is approximated via rational functions, as given by the vector fitting (VF) software tool, and the EDM parameters are identified from the obtained poles/residues. To guarantee positive real parameters, i.e., a physically realizable circuit, VF is internally modified to calculate the final residues of the rational approximation via a constrained linear least-squares problem without resorting to further post-processing algorithms, as in existing methods, hence without affecting fitting accuracy. The effectiveness of the parametrized E... [more]

Lithium batteries for energy storage systems are a prominent solution for both stationary and mobile applications. Electro-thermal modelling of the cell is a useful tool for monitoring voltage and temperature in order to predict battery behaviour especially in cases of critical operative conditions. This paper provides a modelling approach focusing on the calibration of parameters of an electro-thermal model for large prismatic LFP lithium cells. The designed model is tuned by means of experimental tests that identify a set of parameters that are function of a cell’s state-of-charge and temperature. The model outputs are voltage, cell surface, and internal temperature profiles, which are validated against experimental data referring to realistic working conditions, even providing an intense level of thermal stress. The model accuracy is marked by a voltage mean average error lower than 1% and a mean cell surface temperature deviation lower than 1 K.

Despite having extensive research dedicated towards designing methodologies for synchronous out-of-step detection, the risk posed by a large-scale power blackout still makes power system protection an active research area. In recent decades, multiple out-of-step detection techniques such as impedance-based relays and equal-area criterion-analysis-based methods have been widely adopted. However, these conventional techniques have been known to suffer from drawbacks that may be attributed to the inherent assumptions of their foundational design principles. Therefore, to alleviate some of the problems faced in the currently adopted techniques, researchers have been studying the implementation of estimation algorithms for synchronous out-of-step detection. Aiming to contribute to this research area, this paper proposes a synchronous out-of-step detection algorithm that uses a deep Q-network-based disturbance observer, robust to measurement noise. Using the disturbance estimation provided b... [more]

A solar bifacial photovoltaic (PV) module is designed so that it permits the addition of the back electrode to the prevailing silicon PV on the front side. Hence, it has the ability to harvest energy using its front and back faces. This study presents an optimization model for calculating the extra energy yield (EY) that can be harvested from the backside of a bifacial PV module using the Firefly Algorithm (FA). Mathematical modelling of the various parameters that influence the extra EY of the backside of a bifacial module was carried out using SIMULINK. Moreover, the mathematical model of the EY of the module was also carried out and then optimized using FA. The optimization model was confined to two orientation states namely the vertical south−north and vertical east−west at Ogbomosho (8.1227° N, 4.2436° E), Nigeria, with different values of albedo and mounting heights. The simulation result shows that the vertical east−west oriented modules outperform the vertical south−north orien... [more]

The monitoring of partial discharges (PDs) is one of the main methods used worldwide for evaluation and diagnosis of the insulation conditions in equipment powered by medium and high voltages. The occurrence of PDs is usually an indication of the appearance of insulation defects, which over time can compromise the dielectric withstand of the material used, increasing the probability of complete breakdown. In general, laboratory tests for detecting and registering PDs are carried out using purely sinusoidal voltages. However, it is very common for an electrical asset to be subjected at some point in its operating life to voltages distorted by harmonic components. Some studies reported in the literature reveal that harmonic distortions can affect the PDs’ characteristics, nevertheless, the effects of individual harmonic components on PDs still need to be analyzed. In this context, this paper proposes to evaluate the impacts of harmonic voltage distortions on the dynamic behavior and the... [more]

The study shows that the current network of hydrometeorological observation in the permafrost zone of Russia is insufficient to provide data for the statistical approaches adopted at the state level for engineering surveys and calculations. The alternative to the financially costly and practically impossible expansion of the monitoring network is the development of hydrological research stations and the implementation of new methods for calculating streamflow characteristics based on mathematical modeling. The data of the Kolyma Water-Balance Station, the first research basin in the world in a permafrost environment (1948−1997), and the process-based hydrological model Hydrograph are applied to simulate streamflow hydrographs in remote mountainous permafrost basins. The satisfactory results confirm that mathematical modeling may substitute or replace statistical approaches in the conditions of extreme data insufficiency. The improvement of the models in a changing climate requires the... [more]

Three different algorithms that can be used to estimate the available power of a wind turbine are investigated and validated in this study. The first method is the simplest and using the power curve with the measured nacelle wind speed. The other two are to estimate the equivalent wind speed first without using the measured Nacelle wind speed and to estimate the available power from the rotor power equation. The two methods are different in that the second method is to use the drive-train model to estimate the rotor torque but the third method is to use a simplified equation to avoid sharp peaks in the wind speed estimation. Simulations were performed to validate the constructed available power estimation algorithms with the measured data of a 2 MW target wind turbine. It was found from the validation that the third available power estimation algorithm works properly and is closer to the power actually generated from the wind turbine than the other methods considered. In addition, the... [more]

Assessing the performance of photovoltaic systems, particularly dedicated DC/AC inverter devices, requires the use of photovoltaic panels operating under natural environmental conditions, such as variations in solar radiation intensity, temperature and wind speed. Environmental testing is obviously very troublesome, inconvenient and limited. An alternative solution is to use a device that emulates the output photovoltaic panel curves in variable weather conditions, which allows the carrying out of all necessary tests at the laboratory. This paper presents a new photovoltaic emulator (PVE), mimicking the output characteristics of the photovoltaic panels. The proposed PVE is designed and constructed at the renewable energy laboratory for testing low-power PV inverters connected to the LV grid. A novelty of this solution is the method for shaping emulated current−voltage characteristics I−V. The concept of this method assumes autonomous regulation of slopes and shapes of emulated curve fr... [more]

Non-intrusive load monitoring is a blind source separation task that has been attracting significant interest from researchers working in the field of energy informatics. However, despite the considerable progress, there are a very limited number of tools and libraries dedicated to the problem of energy disaggregation. Herein, we report the development of a novel open-source framework named Torch-NILM in order to help researchers and engineers take advantage of the benefits of Pytorch. The aim of this research is to tackle the comparability and reproducibility issues often reported in NILM research by standardising the experimental setup, while providing solid baseline models by writing only a few lines of code. Torch-NILM offers a suite of tools particularly useful for training deep neural networks in the task of energy disaggregation. The basic features include: (i) easy-to-use APIs for running new experiments, (ii) a benchmark framework for evaluation, (iii) the implementation of po... [more]

This paper concerns very-short-term (5-Minute) forecasting of photovoltaic power generation. Developing the methods useful for this type of forecast is the main aim of this study. We prepared a comprehensive study based on fragmentary time series, including 4 full days, of 5 min power generation. This problem is particularly important to microgrids’ operation control, i.e., for the proper operation of small energy micro-systems. The forecasting of power generation by renewable energy sources on a very-short-term horizon, including PV systems, is very important, especially in the island mode of microgrids’ operation. Inaccurate forecasts can lead to the improper operation of microgrids or increasing costs/decreasing profits for microgrid operators. This paper presents a short description of the performance of photovoltaic systems, particularly the main environmental parameters, and a very detailed statistical analysis of data collected from four sample time series of power generation in... [more]

To make a correct decision during normal and transient states, the signal processing for relay protection must be completed and designated the correct task within the shortest given duration. This paper proposes to solve a dc offset fault current phasor with harmonics and noise based on a Deep Neural Network (DNN) autoencoder stack. The size of the data window was reduced to less than one cycle to ensure that the correct offset is rapidly computed. The effects of different numbers of the data samples per cycle are discussed. The simulations revealed that the DNN autoencoder stack reduced the size of the data window to approximately 90% of a cycle waveform, and that DNN performance accuracy depended on the number of samples per cycle (32, 64, or 128) and the training dataset used. The fewer the samples per cycle of the training dataset, the more training was required. After training using an adequate dataset, the delay in the correct magnitude prediction was better than that of the part... [more]

The main flow could be unsteady in flow fields of film cooling for several reasons such as flow interactions between the rotor and the stator in the turbine. Understanding the characteristics of the film-cooling flow with an unsteady flow is important in the design of gas turbines. The effects of 36-Hz pulsations in the main flow on the streamwise velocity distributions, turbulence statistics, and temperature fluctuations in the film-cooling flow from a cylindrical hole with an orientation angle are investigated by numerical methods. Large-eddy simulation (LES) results match the experimental data with an acceptable accuracy, whereas the Reynolds-averaged Navier−Stokes simulation (RANS) results show large deviations with the experimental data and the LES results. Under 36-Hz pulsations, the URANS results predict a weaker streamwise velocity of the coolant jet that blocks the main flow compared with the LES. With 36-Hz pulsations at the time-averaged blowing ratio of 0.5, urms, the root... [more]

Drivers for industrial energy efficiency are factors that promote the sustained adoption of energy-efficient measures and practices. Leveraging drivers to overcome barriers and encourage action which improves industrial energy efficiency can contribute to closing the energy efficiency gap. In fossil-fuel-based systems, this will also contribute to greenhouse gas abatement. A systematic literature review was used to investigate how knowledge about drivers is generated and whether prevalent drivers can be mapped to existing taxonomies. The systematic literature review confirmed that surveys and/or interviews with managers from countries who are members of the Organisation for Economic Cooperation and Development (OECD) are the most common way to gather data on drivers for industrial energy efficiency. This means the extant knowledge on drivers may be incomplete because contributions from some stakeholders, industry types and company sizes may be missing. The review also found economic dr... [more]

This paper aims to study the torque optimization control of distributed drive electric vehicles in the cornering process and reduce the cornering energy consumption. The main energy consumption of the vehicle in the cornering process is analyzed clearly based on the 7-DOF vehicle dynamics model. The torque vectoring distribution (TVD) of a distributed drive electric vehicle in the process of turning was studied on the basis of the Pontryagin Minimum Principle (PMP). The Beetle Antenna Search−Particle Swarm Optimization (BAS-PSO) algorithm was used to optimize the torque distribution coefficient offline, and the algorithm was improved to improve the operation speed. Based on the vehicle dynamics characteristics, the table of torque distribution coefficient of minimum turning energy consumption and the optimal energy-saving degree of TVD control in different bending conditions were worked out.