Drinking water distribution networks (DWDNs) have a huge potential for cold thermal energy recovery (TED). TED can provide cooling for buildings and spaces with high cooling requirements as an alternative for traditional cooling, reduce usage of electricity or fossil fuel, and thus TED helps reduce greenhouse gas (GHG) emissions. There is no research on the environmental assessment of TED systems, and no standards are available for the maximum temperature limit (Tmax) after recovery of cold. During cold recovery, the water temperature increases, and water at the customer’s tap may be warmer as a result. Previous research showed that increasing Tmax up to 30 °C is safe in terms of microbiological risks. The present research was carried out to determine what raising Tmax would entail in terms of energy savings, GHG emission reduction and water temperature dynamics during transport. For this purpose, a full-scale TED system in Amsterdam was used as a benchmark, where Tmax is currently set... [more]

Development of a transition metal based catalyst aiming at concomitant high activity and stability attributed to distinguished catalytic characteristics is considered as the bottleneck for dry reforming of methane (DRM). This work highlights the role of modifying zirconia (ZrO2) and alumina (Al2O3) supported nickel based catalysts using lanthanum oxide (La2O3) varying from 0 to 20 wt% during dry reforming of methane. The mesoporous catalysts with improved BET surface areas, improved dispersion, relatively lower reduction temperatures and enhanced surface basicity are identified after La2O3 doping. These factors have influenced the catalytic activity and higher hydrogen yields are found for La2O3 modified catalysts as compared to base catalysts (5 wt% Ni-ZrO2 and 5 wt% Ni-Al2O3). Post-reaction characterizations such as TGA have showed less coke formation over La2O3 modified samples. Raman spectra indicates decreased graphitization for La2O3 catalysts. The 5Ni-10La2O3-ZrO2 catalyst produ... [more]

Electric trams are one of the standard forms of public transport. They are characterized by large amounts of electric current and electric current gradient from the power grid, especially during acceleration. For this reason, a regenerative braking system is considered with the aim of reducing electric current peaks and increasing energy efficiency by reducing the total energy consumption of the power grid. A supercapacitor module is used as a storage device for storing and utilizing the braking energy. The supercapacitor module and the power grid constitute a hybrid energy system, for which a control algorithm has been developed. The control algorithm takes into account the influence of the elevation profile and the slope of the vehicle route in storing and using the braking energy. The operation of the algorithm was simulated and analyzed using the MATLAB/Simulink software package for tram lines with different elevation profiles.

In this research, Zinc Oxide-Ethylene @ glycol distilled water based nanofluid was synthesized using the sonochemical method. The convective heat transfer properties of as synthesized nanofluid were observed for a closed single circular tube pipe in turbulent flow regimes. The prepared nanofluids were characterized by ultra violet spectroscopy (UV−VIS), UV−VIS absorbance, X-Ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Transmission electron microscopy (TEM) and stability analysis. Five calibrated k-type thermocouples were mounted on the surface of the test section. Analytical data related to heat transfer properties of the synthesized nanofluid for the heat exchanger, incorporated with the closed circular tube test section were collected. The addition of ZnO solid nanoparticles in the EG@DW mixture enhanced the value of thermal conductivity and other thermophysical characteristics of the nanofluids. Maximum thermal conductivity was observed at 45 °C for using 0... [more]

Heat transfer analysis of the pulsatile flow of a hybrid nanofluid through a constricted channel under the impact of a magnetic field and thermal radiation is presented. Hybrid nanofluids form a new class of nanofluids, distinguished by the thermal properties and functional utilities for improving the heat transfer rate. The behaviors of a water-based copper nanofluid and water-based copper plus a single-wall carbon nanotube, i.e., (Cu−SWCNT/water), hybrid nanofluid over each of velocity, wall shear stress, and temperature profiles, are visualized graphically. The time-dependent governing equations of the incompressible fluid flow are transformed to the vorticity-stream function formulation and solved numerically using the finite difference method. The laminar flow simulations are carried out in 2D for simplicity as the flow profiles are assumed to vary only in the 2D plane represented by the 2D Cartesian geometry. The streamlines and vorticity contours are also shown to demonstrate th... [more]

The Atacama Desert receives the highest levels of solar irradiance in the world with an annual average of 2500 kWh/m2 for the global horizontal irradiance and 3500 kWh/m2 for the direct normal irradiance. One of the challenges is the large portion of ultraviolet light. This part of the spectrum be detrimental for the encapsulant materials, reducing their lifetime. To develop a module adapted to the Atacama Desert conditions, it is imperative to have standardized information from first-hand about the typical faults experienced by photovoltaic modules operating in the desert. This work reports on the design and implementation of the Inspection Data Collection Tool to evaluate crystalline silicon-based moules operating in desert climates. The tool brings together novel features of compatibility with current standards, efficient mobile-type instrumentation (equipment and tools), clear procedures/protocols for non-expert users and low development costs. A total of 95 modules were inspected... [more]

This article reports an investigation into ferrite and nanocrystalline materials for the medium-frequency transformer of a dual active bridge DC-DC converter, which plays a key role in the converter’s efficiency and power density. E65 MnZn ferrite cores and toroidal and cut nanocrystalline cores are selected for the construction of 20-kHz transformers. Transformer performance is evaluated with a 1.1-kW (42−54 V)/400 V dual active bridge DC-DC converter with single-phase shift and extended phase shift modulations. The experimental results indicate that the toroidal nanocrystalline transformer had the best performance with an efficiency range of 98.5−99.2% and power density of 12 W/cm3, whereas the cut-core nanocrystalline transformer had an efficiency range of 98.4−99.1% with a power density of 9 W/cm3, and the ferrite transformer had an efficiency range of 97.6−98.8% with a power density of 6 W/cm3. A small mismatch in the circuit parameters is found to cause saturation in the nanocrys... [more]

An essential line of worldwide research towards a sustainable energy future is the materials and processes for carbon dioxide capture and storage. Energy from fossil fuels combustion always generates carbon dioxide, leading to a considerable environmental concern with the values of CO2 produced in the world. The increase in emissions leads to a significant challenge in reducing the quantity of this gas in the atmosphere. Many research areas are involved solving this problem, such as process engineering, materials science, chemistry, waste management, and politics and public engagement. To decrease this problem, green and efficient solutions have been extensively studied, such as Carbon Capture Utilization and Storage (CCUS) processes. In 2015, the Paris Agreement was established, wherein the global temperature increase limit of 1.5 °C above pre-industrial levels was defined as maximum. To achieve this goal, a global balance between anthropogenic emissions and capture of greenhouse gase... [more]

The German government is aiming to increase the share of renewable energies in the electricity supply to 80% in 2050. To date, however, neither the technical requirements nor the market requirements to implement this aim are provided: Germany is struggling to establish the technical requirements and the market requirements to meet this goal. As an important incentive mechanism, the German government has used and continues to use support measures, such as guaranteed feed-in tariffs, and continuously adapts these to market developments and requirements of the European Union. The purpose of the study is to outline a concept for the implementation of regional flexibility markets in Europe based on a thorough review of technical solutions. The method of a comprehensive review of research in regional flexibility markets of electricity, distribution, and pricing from the study is applied to summarize and discuss the opportunities, risks, and future potentials of grid distribution technology.... [more]

Power distribution networks are transitioning from passive towards active networks considering the incorporation of distributed generation. Traditional energy networks require possible system upgrades due to the exponential growth of non-conventional energy resources. Thus, the cost concerns of the electric utilities regarding financial models of renewable energy sources (RES) call for the cost and benefit analysis of the networks prone to unprecedented RES integration. This paper provides an evaluation of photovoltaic (PV) hosting capacity (HC) subject to economical constraint by a probabilistic analysis based on Monte Carlo (MC) simulations to consider the stochastic nature of loads. The losses carry significance in terms of cost parameters, and this article focuses on HC investigation in terms of losses and their associated cost. The network losses followed a U-shaped trajectory with increasing PV penetration in the distribution network. In the investigated case networks, increased... [more]

Solar irradiance forecasting is an inevitable and most significant process in grid-connected photovoltaic systems. Solar power is highly non-linear, and thus to manage the grid operation efficiently, with irradiance forecasting for various timescales, such as an hour ahead, a day ahead, and a week ahead, strategies are developed and analysed in this article. However, the single time scale model can perform better for that specific time scale but cannot be employed for other time scale forecasting. Moreover, the data consideration for single time scale forecasting is limited. In this work, a multi-time scale model for solar irradiance forecasting is proposed based on the multi-task learning algorithm. An effective resource sharing scheme between each task is presented. The proposed multi-task learning algorithm is implemented with a long short-term memory (LSTM) neural network model and the performance is investigated for various time scale forecasting. The hyperparameter estimation of... [more]

This paper aims to investigate the usage of waste from Absorbent Hygienic Products (AHP) as a fuel for gasification or pyrolysis, two attractive routes to obtain valuable products and dispose of this kind of waste. The study experimentally investigated the devolatilization of coarsely shredded materials from diapers, in a laboratory-scale bubbling fluidized bed made of sand, as a representative preparatory step of the above-mentioned thermochemical conversions. Two versions of shredded materials were considered: as-manufactured diapers (AHPam, as a reference), and the cellulosic fraction of sterilized used diapers (AHPus). Results were presented, obtained from physical-chemical characterization of AHPam and AHPus (TGA, CHNS/O, proximate and ultimate analyses, XRF, ICP-AES, SEM-EDS), as well as from their devolatilizations at 500−600−700−800 °C under two different atmospheres (air plus nitrogen, or pure nitrogen as a reference). Generally, temperature influenced syngas composition the m... [more]

An Energy Management System (EMS) that uses a Model Predictive Control (MPC) to manage the flow of the microgrids is described in this work. The EMS integrates both wind speed and solar radiation predictors by using a time series to perform the primary grid forecasts. At each sampling data measurement, the power of the photovoltaic system and wind turbine are predicted. Then, the MPC algorithm uses those predictions to obtain the optimal power flows of the microgrid elements and the main network. In this work, three time-series predictors are analyzed. As the results will show, the MPC strategy becomes a powerful energy management tool when it is integrated with the Double Exponential Smoothing (DES) predictor. This new scheme of integrating the DES method with an MPC presents a good management response in real-time and overcomes the results provided by the Optimal Power Flow method, which was previously proposed in the literature. For the case studies, the test microgrid located in th... [more]

This work proposes an automated reconfiguration system to manage two types of faults in any position inside the solar arrays. The faults studied are the short-circuit to ground and the open wires in the string. These faults were selected because they severely affect power production. By identifying the affected panels and isolating the faulty one, it is possible to recover part of the power loss. Among other types of faults that the system can detect and locate are: diode short-circuit, internal open-circuit, and the degradation of the internal parasitic serial resistance. The reconfiguration system can detect, locate the above faults, and switch the distributed commutators to recover most of the power loss. Moreover, the system can return automatically to the previous state when the fault has been repaired. A SIMULINK model has been built to prove this automatic system, and a simulated numerical experiment has been executed to test the system response to the faults mentioned. The resu... [more]

The tire pyrolysis oil is a waste-derived fuel with a lower cetane number and higher den-sity than diesel fuel, but this is a promising waste-based fuel for compression ignition en-gines. In the European Union, it is necessary to increase the bio-share of fuels, and the second-generation waste-derived blend components are essential for achieving the 2030 goals. The injection characteristics of tire pyrolysis oil and diesel oil were investigated on a Bosch solenoid type common rail (CR) injector. Six different premixed ratios were investi-gated, including in a low volume percentage 250 ppm and higher 10%, 20%, and 100% pyrolysis oil and 100% diesel oil. The simulation investigation was done in the AVL Fire software, the experimental investigations were done on a LDX CR injection test bench, and the videos were taken on an Olympus Ispeed 3 camera. The scope of the research was to record the flow pattern of the fuel mixture, flowing out of the high-pressure injector, from which the mixing... [more]

The operational reliability and high efficiency of modern electrical machines depend on the ability to transfer heat in the construction parts of the machine. Therefore, many authors study various thermal models and work on the development of effective heat dissipation. New insights and methods lead to improved techniques for the thermal design of electrical machines. This paper presents an experimentally validated thermal model of a permanent magnet synchronous motor (PMSM) with an improved slot winding model. It also deals with various approaches to homogenization and equivalent material properties of a tooth-coil winding sub-model. First, an algorithm for building a lumped-parameter thermal network (LPTN) of PMSM is described and its properties and problems are discussed. Subsequently, a sub-model of a slot with a winding based on the finite element method (FEM) is introduced. This sub-model is able to generate different conductor distributions based on probabilistic methods for a s... [more]

This paper analyzes the impact of the COVID-19 pandemic on economic growth and electricity consumption and investigates the hypothesis of the influence of this consumption on the gross domestic product (GDP) for Romania. Using time series on monthly electricity consumption and quarterly GDP and a multi-linear regression model, we performed an analysis of the evolution of these indicators for 2007−2020, a comparison between their behavior during the financial crisis vs. COVID-19 crisis, and empirically explore the relationships between GDP and electricity consumption or some of its components. The results of the analysis confirm that the shock of declining activity due to the COVID-19 pandemic had a severe negative impact on electric energy consumption and GDP in the first half of 2020, followed by a slight recovery. By using a linear regression model, long-term relationships between GDP and domestic and non-household electricity consumptions were found. The empirically estimated elasti... [more]

Intensive-stage fracturing in horizontal wells is a potentially new technology for reservoir stimulations of deep shale oil and gas. Due to a strong stress interaction among the dense fractures, the fracture geometry and stress field are very complicated, which are the bottlenecks of this technology. Aiming at simulating the intensive-stage fracturing, a coupled three-dimensional (3D) fracture model of multiple-fracture simultaneous propagation is proposed. The dynamic behavior of the fracture propagation and stress field was analyzed using this model. The perforation parameters were optimized for improving the fracture geometry equilibrium. The results showed that the exterior fractures of the multiple fractures penetrated by the horizontal well become the main fractures, while the interior fractures are drastically restrained. The exterior fracture widths increased with increasing injection time, while the interior fracture widths decreased with increasing injection time. An extruded... [more]

Since solid particles suspended in the fluid can cause wear in centrifugal pumps, intensive attention has been focused on the numerical prediction for the wear of flow parts in centrifugal pumps. However, most numerical studies have focused on only one wear model and a sphere particle model. The impact of particle shape on the wear of flow parts in centrifugal pumps is under-studied, particularly considering abrasive and impact wear simultaneously. In this work, the Computational Fluid Dynamics (CFD)-Discrete Element Method (DEM) coupling method with an abrasive and impact wear prediction model was adopted to study the wear characteristics of a centrifugal pump. Moreover, four regular polyhedron particles and a sphere particle with the same equivalent diameter but different sphericity were mainly analyzed. The results demonstrate that more particles move closer to the blade pressure side in the impeller passage, and particles tend to cluster in specific areas within the volute as spher... [more]

Here, we propose a new deep learning scheme to solve the energy time series prediction problem. The model implementation is based on the use of Long Short-Term Memory networks and Convolutional Neural Networks. These techniques are combined in such a fashion that inter-dependencies among several different time series can be exploited and used for forecasting purposes by filtering and joining their samples. The resulting learning scheme can be summarized as a superposition of network layers, resulting in a stacked deep neural architecture. We proved the accuracy and robustness of the proposed approach by testing it on real-world energy problems.

This paper reviews non-intrusive load monitoring (NILM) approaches that employ deep neural networks to disaggregate appliances from low frequency data, i.e., data with sampling rates lower than the AC base frequency. The overall purpose of this review is, firstly, to gain an overview on the state of the research up to November 2020, and secondly, to identify worthwhile open research topics. Accordingly, we first review the many degrees of freedom of these approaches, what has already been done in the literature, and compile the main characteristics of the reviewed publications in an extensive overview table. The second part of the paper discusses selected aspects of the literature and corresponding research gaps. In particular, we do a performance comparison with respect to reported mean absolute error (MAE) and F1-scores and observe different recurring elements in the best performing approaches, namely data sampling intervals below 10 s, a large field of view, the usage of generative... [more]

Despite coal being one of the major contributors of CO2, it remains a cheap and stable source of electricity. However, several countries have turned to solar energy in their goal to “green” their energy generation. Solar energy has the potential to displace coal with support from natural gas. In this study, an hourly power flow analysis was conducted to understand the potential, limitations, and implications of using solar energy as a driver for decommissioning coal power plants. To ensure the results’ robustness, the study presents a straightforward weather-driven scenario analysis that utilizes historical weather and electricity demand to generate representative scenarios. This approach was tested in Japan’s southernmost region, since it represents a regional grid with high PV penetration and a fleet of coal plants older than 40 years. The results revealed that solar power could decommission 3.5 GW of the 7 GW coal capacity in Kyushu. It was discovered that beyond 12 GW, solar power... [more]

The brushless doubly fed reluctance machine (BDFRM) is receiving an increased amount of attention from the research community thanks to its potential as an alternative drive for variable speed applications, both as motor and generator. Currently, the sizing of the BDFRM in the literature is based on the model of an ideal axially laminated rotor (ALR) and discrepancies are hidden in compensation factors which are in turn tuned with a finite element analysis (FEA). This paper proposes an analytical framework to accurately model the air gap field modulation, and by extension the torque density, of the BDFRM with ducted segmental rotor (DSR) and salient pole rotor (SPR). The results are verified with FEA and validated on a BDFRM prototype.

Piezoelectric energy harvesters have attracted much attention because they are crucial in portable industrial applications. Here, we report on a high-power device based on a magneto-mechanical piezoelectric energy harvester to scavenge the AC magnetic field from a power-line cable for industrial applications. The electrical output performance of the harvester (×4 layers) reached an output voltage of 60.8 Vmax, an output power of 215 mWmax (98 mWrms), and a power density of 94.5 mWmax/cm3 (43.5 mWrms/cm3) at an impedance matching of 5 kΩ under a magnetic field of 80 μT. The multilayer energy harvester enables high-output performance, presenting an obvious advantage given this improved level of output power. Finite element simulations were also performed to support the experimental observations. The generator was successfully used to power a wireless sensor network (WSN) for use on an IoT device composed of a temperature sensor in a thermal power station. The result shows that the magnet... [more]

Rational decision-making requires assessing the advantages and disadvantages of options, including nonmarket effects (such as environmental effects). This also applies to strategic decision-making in the industrial sector to select alternative renewable energy source (RES). Often, a variety of criteria can be used to select a renewable energy source, whereas no ideal family of criteria for renewable energy selection for industry has been defined in the literature. It was concluded that there is a need to support the actions of industrial development based on RES, which will contribute significantly to overcoming the limitations of the negative effect on the environment in terms of greenhouse gas emissions. There is a clear need for a systematic and polyvalent multicriteria approach to planning in industry. Therefore, a method for choosing the preferred renewable source of electricity for industry has been developed, which considers key criteria of RES choice: Expert opinions, the costs... [more]