To improve access to affordable, reliable and sustainable energy in rural areas of the global south, off-grid systems using renewable generation and energy storage are often proposed. However, solution design is often technology-driven, with insufficient consideration of social and cultural contexts. This leads to a risk of unintended consequences and inappropriate systems that do not meet local needs. To address this problem, this paper describes the application of a capabilities-led approach to understanding a community’s multi-dimensional energy poverty and assessing their needs as they see them, in order to better design suitable technological interventions. Data were collected in Tlamacazapa, Mexico, through site visits and focus groups with men and women. These revealed the ways in which constrained energy services undermined essential capabilities, including relating to health, safety, relationships and earning a living, and highlighted the specific ways in which improved energy... [more]

Air classification (AC) is a cost-effective technology that separates the energy-dense light ash fraction (LAF) from the inorganic-rich high ash fraction (HAF) of corn stover. HAF could be upgraded into energy-dense solid fuel by hydrothermal carbonization (HTC). However, HTC is a high-temperature, high-pressure process, which requires additional energy to operate. In this study, three different scenarios (i.e., AC only, HTC only, and integrated AC−HTC) were investigated for the energy recovery of corn stover. AC was performed on corn stover at an 8 Hz fan speed, which yielded 84.4 wt. % LAF, 12.8 wt. % HAF, and 2.8 wt. % below screen particles. About 27 wt. % ash was reduced from LAF by the AC process. Furthermore, HTC was performed on raw corn stover and the HAF of corn stover at 200, 230, and 260 °C for 30 min. To evaluate energy recovery, solid products were characterized in terms of mass yield, ash yield, ultimate analysis, proximate analyses, and higher heating value (HHV). The r... [more]

Novel drivetrain concepts such as electric direct drives can improve vehicle dynamic control due to faster, more accurate, and more flexible generation of wheel individual propulsion and braking torques. Exact and robust estimation of vehicle state of motion in the presence of unknown disturbances, such as changes in road conditions, is crucial for realization of such control systems. This article shows the design, tuning, implementation, and test of a state estimator with individual tire model adaption for direct drive electric vehicles. The vehicle dynamics are modeled using a double-track model with an adaptive tire model. State-of-the-art sensors, an inertial measurement unit, steering angle, wheel speed, and motor current sensors are used as measurements. Due to the nonlinearity of the vehicle model, an Unscented Kalman Filter (UKF) is used for simultaneous state and parameter estimation. To simplify the difficult task of UKF tuning, an optimization-based method using real-vehicle... [more]

An efficient cooling system for data centers can boost the working efficiency of servers and promote energy savings. In this study, a laboratory experiment and computational fluid dynamics (CFD) simulation were performed to explore the performance of a two-phase cooling system. The coefficient of performance (COP) and partial power usage effectiveness (pPUE) of the proposed system was evaluated under various IT (Information Technology) loads. The relationship between the interval of the two submerged servers and their surface temperatures was evaluated by CFD analysis, and the minimum intervals that could maintain the temperature of the server surfaces below 85 °C were obtained. Experimental results show that as server power increases, COP increases pPUE decreases. In one experiment, the COP increased from 19.0 to 26.7, whereas pPUE decreased from 1.053 to 1.037. The exergy efficiency of this system ranges from 12.65% to 18.96%, and the tank side accounts for most of the exergy destruc... [more]

Particulate matter (soot) emissions from combustion processes have damaging health and environmental effects. Numerical techniques with varying levels of accuracy and computational time have been developed to model soot formation in flames. High-fidelity soot models come with a significant computational cost and as a result, accurate soot modelling becomes numerically prohibitive for simulations of industrial combustion devices. In the present study, an accurate and computationally inexpensive soot-estimating tool has been developed using a long short-term memory (LSTM) neural network. The LSTM network is used to estimate the soot volume fraction (fv) in a time-varying, laminar, ethylene/air coflow diffusion flame with 20 Hz periodic fluctuation on the fuel velocity and a 50% amplitude of modulation. The LSTM neural network is trained using data from CFD, where the network inputs are gas properties that are known to impact soot formation (such as temperature) and the network output is... [more]

Steelmaking is responsible for approximately one third of total industrial carbon dioxide (CO2) emissions. Hydrogen (H2) direct reduction (H-DR) may be a feasible route towards the decarbonization of primary steelmaking if H2 is produced via electrolysis using fossil-free electricity. However, electrolysis is an electricity-intensive process. Therefore, it is preferable that H2 is predominantly produced during times of low electricity prices, which is enabled by the storage of H2. This work compares the integration of H2 storage in four liquid carriers, methanol (MeOH), formic acid (FA), ammonia (NH3) and perhydro-dibenzyltoluene (H18-DBT), in H-DR processes. In contrast to conventional H2 storage methods, these carriers allow for H2 storage in liquid form at moderate overpressures, reducing the storage capacity cost. The main downside to liquid H2 carriers is that thermochemical processes are necessary for both the storage and release processes, often with significant investment and o... [more]

A triboelectric generator (TEG) is a simple coupling combined with triboelectrification and electrostatic induction, which can convert mechanical energy into electrical energy and have the potential for self-powered device application. In this study, TEGs are fabricated consisting of a conductive textile (CT) layer (a fabric woven with polyester and stainless steel) and a polydimethylsiloxane (PDMS) layer. The CT friction layer is also used as a conductive electrode and designed with various surface morphologies, including unpatterned, dots, and lines with 1 and 2 cm spacings. Experimental results show that the TEG with an unpatterned CT layer produces an output voltage of 54.6 V and an output current of 5.46 µA. The patterned surfaces increase the effective contact area and friction effect between the CT and PDMS layers and hence enhance the output voltage and current to 94.4 V and 9.44 µA. Compared to the unpatterned CT layer, the pattern use of 1 cm spaced lines, 2 cm spaced lines,... [more]

This paper proposes a new hybrid islanding detection method for grid-connected photovoltaic system (GCPVS)-based microgrid. In the presented technique, the suspicious islanding event is initially recognized whilst the absolute deviation of the point of common coupling (PCC) voltage surpasses a threshold. After an intentional delay, a transient disturbance is injected into the voltage source inverter’s d-axis reference current to decline the active power output. As a result, the PCC voltage reduces in islanding operating mode whilst its variation is negligible in the grid presence. Therefore, the simultaneous drop of PCC voltage and active power output is used as an islanding detection criterion. The effectiveness of the proposed algorithm is investigated for various islanding and non-islanding scenarios for a practical distribution network with three GCPVSs. The simulation results in MATLAB/Simulink show successful islanding detection with a small non-detection zone within 300 ms witho... [more]

Nowadays, the heat transfer enhancement in electronic cabinets with heat-generating elements can be achieved using the phase change materials and finned heat sink. The latter allows to improve the energy transference surface and to augment the cooling effects for the heat sources. The present research deals with numerical analysis of phase change material behavior in an electronic cabinet with an energy-generating element. For an intensification of heat removal, the complex finned heat sink with overall width of 10 cm was introduced, having the complicated shape of the fins with width of 0.33 cm and height H = 5 cm. The fatty acid with melting temperature of 46 °C was considered as a phase change material. The considered two-dimensional challenge was formulated employing the non-primitive variables and solved using the finite difference method. Impacts of the volumetric heat flux of heat-generating element and sizes of the fins on phase change material circulation and energy transferen... [more]

The global increase in energy needs and environmental awareness for a more efficient energy use have boosted building rehabilitation to decrease energy consumption. The installation of solar control films (SCFs) in buildings with large glazing façades makes it possible to reduce excessive solar gains through the glazing. The main purpose of the work is to assess, with field experimental data, the thermal and luminous performances of double-glazing units with SCFs installed in office rooms, in Lisbon. An experimental campaign was carried out simultaneously in three adjacent offices: one with a highly reflective SCF (external installation), one with a reflective SCF (internal installation) and one without an SCF. The exterior SCF showed the best thermal performance with reductions in the peak indoor air temperature of up to 6.9 and 2.3 °C during the representative days of the heating and cooling periods, respectively, increasing thermal comfort mainly during the cooling period. The inter... [more]

Optimal management of thermal energy storage in a building is essential to provide predictable energy flexibility to a smart grid. Active technologies such as Electric Thermal Storage (ETS) can assist in building heating load management and can complement the building’s passive thermal storage capacity. The presented paper outlines a methodology that utilizes the concept of Building Energy Flexibility Index (BEFI) and shows that implementing Model Predictive Control (MPC) with dedicated thermal storage can provide predictable energy flexibility to the grid during critical times. When the utility notifies the customer 12 h before a Demand Response (DR) event, a BEFI up to 65 kW (100% reduction) can be achieved. A dynamic rate structure as the objective function is shown to be successful in reducing the peak demand, while a greater reduction in energy consumption in a 24-hour period is seen with a rate structure with a demand charge. Contingency reserve participation was also studied and... [more]

The biggest obstacle to using a permanent magnet synchronous generator (PMSG) for a floating offshore wind turbine (FOWT) is the weight. A superconducting synchronous generator (SCSG) can be an alternative to this problem. In this paper, first, the weight and volume of a 10 MW class PMSG and SCSG for a large floating offshore wind farm (FOWF) were compared. Reflecting this, the economic feasibility of a 200 MW class FOWF based on a semi-submersible platform was compared and analyzed. The levelized cost of energy (LCOE) was used to compare the economics of the two types of FOWF, and the LCOE of the SCSG type FOWF was 6 (USD/MWh) more expensive than that of the PMSG type FOWF. However, if the superconducting wire price is reduced by 40% compared to the current price, the economic feasibility of the SCSG type FOWF can be secured. Considering only the weight, the SCSG type FOWF is far superior to the PMSG type FOWF. With the trend of falling superconducting wire prices and improving critic... [more]

This paper presents the possibilities of adapting active mines to generate green energy after their closure using their resources and/or infrastructure. For this purpose, firstly, the temporal horizon of selected mines in Poland was determined, its basic assumption being the analysis of the current state. In the research, 18 mining plants operating within 12 mines in the Upper Silesian Coal Basin (USCB) were analyzed. The analyzed mines belong to three of the five largest hard coal producers in Poland, and the main object of exploitation is hard coal of energy types. Severe restrictions or even abandonment of further investments in the development of the coal mining industry were taken into consideration (regarding the construction of new shafts or the development of new exploitation levels). When determining the temporal horizon, the challenges that hamper the exploitation based at the levels of natural hazards and depth of exploitation in each mine were considered. Secondly, the crit... [more]

The effective prediction of gas concentration and the reasonable formulation of corresponding safety measures have important significance for improving the level of coal mine safety. To improve the accuracy of gas concentration prediction and enhance the applicability of the models, this paper starts with actual coal mine production monitoring data, improves the accuracy of gas concentration prediction through multi-parameter fusion prediction, and constructs a recurrent neural network (RNN)-based multi-parameter fusion prediction of coal face gas concentration. We determined the performance evaluation index of the model’s prediction method; used the grid search method to optimize the hyperparameters of the batch size; and used the number of neurons, the learning rate, the discard ratio, the network depth, and the early stopping method to prevent overfitting. The gas concentration prediction models—based on RNN and PSO-SVR and PSO-Adam-BP neural networks—were compared and analyzed expe... [more]

Gas turbine inlet air-cooling (TIAC) is an established technology for augmenting gas turbine output and efficiency, especially in hot regions. TIAC using evaporative cooling is suitable for hot, dry regions; however, the cooling is limited by the ambient wet-bulb temperature. This study investigates two-stage evaporative TIAC under the harsh weather of Riyadh city. The two-stage evaporative TIAC system consists of indirect and direct evaporative stages. In the indirect stage, air is precooled using water cooled in a cooling tower. In the direct stage, adiabatic saturation cools the air. This investigation was conducted for the GE 7001EA gas turbine model. Thermoflex software was used to simulate the GE 7001EA gas turbine using different TIAC systems including evaporative, two-stage evaporative, hybrid absorption refrigeration evaporative and hybrid vapor-compression refrigeration evaporative cooling systems. Comparisons of different performance parameters of gas turbines were conducted... [more]

Designing district-scale energy systems with renewable energy sources is still a challenge, as it involves modeling of multiple loads and many options to combine energy system components. In the current study, two different energy system scenarios for a district in Montreal/Canada are compared to choose the most cost-effective and energy-efficient energy system scenario for the studied area. In the first scenario, a decentral energy system comprised of ground-source heat pumps provides heating and cooling for each building, while, in the second scenario, a district heating and cooling system with a central heat pump is designed. Firstly, heating and cooling demand are calculated in a completely automated process using an Automatic Urban Building Energy Modeling System approach (AUBEM). Then, the Integrated Simulation Environment Language (INSEL) is used to prepare a model for the energy system. The proposed model provides heat pump capacity and the number of required heat pumps (HP), t... [more]

In power systems, high renewable energy penetration generally results in conventional synchronous generators being displaced. Hence, the power system inertia reduces, thus causing a larger frequency deviation when an imbalance between load and generation occurs, and thus potential system instability. The problem associated with this increase in the system’s dynamic response can be addressed by various means, for example, flywheels, supercapacitors, and battery energy storage systems (BESSs). This paper investigates the application of BESSs for primary frequency control in power systems with very high penetration of renewable energy, and consequently, low levels of synchronous generation. By re-creating a major Australian power system separation event and then subsequently simulating the event under low inertia conditions but with BESSs providing frequency support, it has been demonstrated that a droop-controlled BESS can greatly improve frequency response, producing both faster reactio... [more]

A small rotating detonation engine (RDE) model and the corresponding experimental setup were constructed for the experimental investigation of the detonation propagation characteristics and thrust performance of a circular RDE. Experiments were conducted at a range of 0.3−2.5 equivalence ratio with a total mass flow rate of less than 180.0 g/s using a C2H4/O2 mixture. Irregularly unstable detonative combustion occurs immediately after the detonation initiation, which includes initiation, propagation, decaying, and the merging of detonation waves. Following this, periodically unsteady detonative combustion occurs in the circular channel, resulting in the stable operation of the RDE. During stable operation, two detonation waves are predominant, rotating along the wall at a speed lower than the Chapman−Jouguet (CJ) detonation speed. The characteristic velocity efficiency is approximately 73% on average. The low characteristic velocity efficiency is presumed to be caused by the unoptimize... [more]

In this paper, a brief survey of measurable factors affecting the adoption of cybersecurity enhancement methods in the smart grid is provided. From a practical point of view, it is a key point to determine to what degree the cyber resilience of power systems can be improved using cost-effective resilience enhancement methods. Numerous attempts have been made to the vital resilience of the smart grid against cyber-attacks. The recently proposed cybersecurity methods are considered in this paper, and their accuracies, computational time, and robustness against external factors in detecting and identifying False Data Injection (FDI) attacks are evaluated. There is no all-inclusive solution to fit all power systems requirements. Therefore, the recently proposed cyber-attack detection and identification methods are quantitatively compared and discussed.

(1) Background: This paper proposes a strategy coupling Demand Response Program with Dynamic Thermal Rating to ensure a transformer reserve for the load connection. This solution is an alternative to expensive grid reinforcements. (2) Methods: The proposed methodology firstly considers the N-1 mode under strict assumptions on load and ambient temperature and then identifies critical periods of the year when transformer constraints are violated. For each critical period, the integrated management/sizing problem is solved in YALMIP to find the minimal Demand Response needed to ensure a load connection. However, due to the nonlinear thermal model of transformers, the optimization problem becomes intractable at long periods. To overcome this problem, a validated piece-wise linearization is applied here. (3) Results: It is possible to increase reserve margins significantly compared to conventional approaches. These high reserve margins could be achieved for relatively small Demand Response... [more]

The traditional way to mitigate loss circulation in drilling operations is to use preventative and curative materials. However, it is difficult to quantify the amount of materials from every possible combination to produce customized rheological properties. In this study, machine learning (ML) is used to develop a framework to identify material composition for loss circulation applications based on the desired rheological characteristics. The relation between the rheological properties and the mud components for polyacrylamide/polyethyleneimine (PAM/PEI)-based mud is assessed experimentally. Four different ML algorithms were implemented to model the rheological data for various mud components at different concentrations and testing conditions. These four algorithms include (a) k-Nearest Neighbor, (b) Random Forest, (c) Gradient Boosting, and (d) AdaBoosting. The Gradient Boosting model showed the highest accuracy (91 and 74% for plastic and apparent viscosity, respectively), which can... [more]

The energy consumption for space cooling is growing faster than for any other end-use in buildings, more than tripling between 1990 and 2016. Energy efficiency is an important topic in the drive to reduce the consumption of electricity, particularly in air conditioning. This paper presents a simulation of an absorption cooling system with a parabolic trough collector under dynamic conditions using TRaNsient SYstem Simulation (TRNSYS) software. The thermal analysis seeks to evaluate a storage tank at three different configurations: (1) sensible heat, (2) latent heat, and (3) latent heat incorporating a tempering valve. The latent heat storage tank is a rectangular heat exchanger using MgCl2·6H2O as the phase change material, programmed in EES software; in addition, water and synthetic organic fluid were analyzed as heating fluids. The process was analyzed while varying the solar collector area from 20 to 40 m2 and the storage tank volume from 0.25 to 0.75 m3. The results showed that the... [more]

This research aims to bring together thermal modelling and machine learning approaches to improve the understanding on the operation and fault detection of a wind turbine gearbox. Recent fault detection research has focused on machine learning, black box approaches. Although it can be successful, it provides no indication of the physical behaviour. In this paper, thermal network modelling was applied to two datasets using SCADA (Supervisory Control and Data Acquisition) temperature data, with the aim of detecting a fault one month before failure. A machine learning approach was used on the same data to compare the results to thermal modelling. The results found that thermal network modelling could successfully detect a fault in many of the turbines examined and was validated by the machine learning approach for one of the datasets. For that same dataset, it was found that combining the thermal model losses and the machine learning approach by using the modelled losses as a feature in t... [more]

The paper analyzes the impact of energy consumption on the three pillars of sustainable development in 74 countries. The main methodological challenge in this research is the choice of a single integral indicator for assessing the social component of sustainable development. Disability-adjusted life year (DALY), ecological footprint, and GDP (Gross domestic product) are used to characterize the social, ecological, and economical pillars. The concept of physics, namely the concept of density (specific gravity), is used. It characterizes the ratio of the mass of a substance to its volume, i.e., reflects the saturation of a certain volume with this substance. Thus, to assess the relationship between energy consumption and the three foundations of sustainable development, it is proposed to determine the energy density of the indicators DALY, the ecological footprint, and GDP. The reaction to changes in energy consumption is described by the elasticity of energy density functions, calculate... [more]

Recently, micro-grids (MGs) have had a great impact on power system issues due to their clear environmental and economic advantages. This paper proposes an equilibrium optimizer (EO) technique for solving the energy management problem of MGs incorporating energy storage devices concerning the emissions from renewable energy sources (RES) of MGs. Because of the imprecision and uncertainties related to the RESs, market prices, and forecast load demand, the optimization problem is described in a probabilistic manner using a 2m + 1 point estimation approach. Then, the EO approach is utilized for solving the probabilistic energy management (EM) problem. The EM problem is described according to the market policy on the basis of minimizing the total operating cost and emission from RESs through optimal settings of the power generated from distributed generators (DGs) and grids connected under the condition of satisfying the operational constraints of the system. The proposed EO is evaluated b... [more]