Surface pollution is a major cause of partial discharges in high voltage insulators in coastal cities, leading to degradation of their surface and accelerating their aging process, which may cause visible arcing, flashovers and system faults. Thus, this work provides a methodology for the assessment of the condition of insulators based on an instrument which generates a severity degree to help the electric utility team schedule maintenance routines for the structures that really need it. The instrument uses a Raspberry Pi board as the processing core, a PicoScope oscilloscope for the data acquisition and an antenna as a partial discharge sensor. The algorithms are implemented in Python, and use artificial intelligence tools, such as a convolutional network and a fuzzy inference system. Laboratory test methods for the simulation of the field pollution conditions were successfully used for the validation of the instrument, which showed a good correlation between the pollution level and t... [more]

Technological solutions allowing the increase of the technological efficiency of anaerobic methods of wastewater treatment are still under investigation. The weaknesses of these solutions can be limited by the use of active fillings. The aim of the present study was to determine the impact of fluidized active filling on the effectiveness of anaerobic treatment of sugar-industry effluent, the production efficiency and the qualitative composition of the biogas produced. High, comparable (p = 0.05) effluent treatment results were observed at tested organic load rates between 4.0 and 6.0 kg COD (Chemical Oxygen Demand)/m3·d. The COD removal rate reached over 74%, biogas yields ranged from 356 ± 25 to 427 ± 14 dm3/kg CODremoved and the average methane contents were approximately 70%. A significant decrease in effluent treatment efficiency and methane fermentation was observed after increasing the organic load rate to 8.0 kg COD/m3·d, which correlated with decreased pH and FOS/TAC (volatile... [more]

Studying the evolution of the efficiency of the electricity generation sector is a relevant task for policy makers, and requires the undesirable outputs derived from the activity to be considered in the evaluation. In this work, we propose a dynamic slack-based Data Envelopment Analysis (DEA) model that incorporates the assumption of weak disposability between the generation of electricity from fossil sources and the CO2 emissions caused by the sector to measure the technical efficiency of 24 Latin American and Caribbean countries in the period 2000−2016. The results show that, of the total number of countries studied, four are efficient overall, and four groupings of countries in relation to the levels of efficiency achieved are also identified. These results are important given that less-efficient countries can, through learning, increase their efficiency in electricity generation or emulate the future strategies proposed by the most efficient countries.

Presently, deep learning models are an alternative solution for predicting solar energy because of their accuracy. The present study reviews deep learning models for handling time-series data to predict solar irradiance and photovoltaic (PV) power. We selected three standalone models and one hybrid model for the discussion, namely, recurrent neural network (RNN), long short-term memory (LSTM), gated recurrent unit (GRU), and convolutional neural network-LSTM (CNN−LSTM). The selected models were compared based on the accuracy, input data, forecasting horizon, type of season and weather, and training time. The performance analysis shows that these models have their strengths and limitations in different conditions. Generally, for standalone models, LSTM shows the best performance regarding the root-mean-square error evaluation metric (RMSE). On the other hand, the hybrid model (CNN−LSTM) outperforms the three standalone models, although it requires longer training data time. The most sig... [more]

The backbone of a conventional electrical power generation system relies on hydro-thermal coordination. Due to its intrinsic complex, large-scale and constrained nature, the feasibility of a direct approach is reduced. With this limitation in mind, decomposition methods, particularly Lagrangian relaxation, constitutes a consolidated choice to “simplify” the problem. Thus, translating a relaxed problem approach indirectly leads to solutions of the primal problem. In turn, the dual problem is solved iteratively, and Lagrange multipliers are updated between each iteration using subgradient methods. However, this class of methods presents a set of sensitive aspects that often require time-consuming tuning tasks or to rely on the dispatchers’ own expertise and experience. Hence, to tackle these shortcomings, a novel Lagrangian multiplier update adaptative algorithm is proposed, with the aim of automatically adjust the step-size used to update Lagrange multipliers, therefore avoiding the nee... [more]

The paper describes an installation for the degradative depolymerization of polyolefin materials obtained from wastes, hereinafter also referred to as depolymerization for simplicity. The plant, on an industrial scale, is one of the few operating in Poland. However, it is one of the most modern plants in this industry. Design solutions, construction of particular technological lines, compliance with national and EU regulations and the high level of process safety were described in this paper as well as compared to other plants of this type in Poland. Different solutions were presented in drawings and photos of the plant and in fragmentary technological diagrams. The types of waste and the methods of their processing by the plant were also characterized in accordance with the applicable regulations. The waste throughput is from 2000 to 4000 kg/h, while the efficiency of the depolymerization installation itself is 1500 kg/h. The industrial-scale depolymerization process is carried out in... [more]

With only less than 10% recovery, the primary production of hydrocarbon from shale reservoirs has redefined the energy equation in the world. Similar to conventional reservoirs, Enhanced Oil Recovery (EOR) techniques could be devised to enhance the current recovery factors. However, shale reservoirs possess unique characteristics that significantly affect the fluid properties. Therefore, we are adopting a molecular simulation approach that is well-suited to account for these effects to evaluate the performance of three different gases, methane, carbon dioxide and nitrogen, to recover the hydrocarbons from rough pore surfaces. Our hydrocarbon systems consists of either a single component (decane) or more than one component (decane and pentane). We simulated cases where concurrent and countercurrent displacement is studied. For concurrent displacement (injected fluids displace hydrocarbons towards the production region), we found that nitrogen and methane yielded similar recovery; howeve... [more]

In order to study the evolution of the mechanical properties and macromolecular structures in different macerals of tectonically deformed coal (TDC), vitrinite and inertinite samples were handpicked from six block TDCs in the same coal seam with an increasing deformation degree (unaltered, cataclastic, porphyroclast, scaly and powdery coal). The micro mechanical properties were tested by the nanoindentation experiment and the macromolecular structures were measured using 13C nuclear magnetic resonance (NMR) and Fourier transform infrared spectroscopy (FTIR). The results show that the range of hardness and elastic modulus of inertinite is 0.373−1.517 GPa and 4.339−12.158 GPa, respectively, which is significantly higher than that of vitrinite with values of 0.278−0.456 GPa and 4.857−7.810 GPa, respectively. From unaltered coal to powdery coal, the hardness of vitrinite and inertinite gradually decreases, with the difference between these macerals becomes smaller and the elastic modulus o... [more]

In this work, issues related to the application of the D-decomposition technique to selection of the controller parameters for a drive system with flexibility are presented. In the introduction the commonly used control structures dedicated to two-mass drive systems are described. Then the mathematical model as well as control structure are introduced. The considered structure has only basic feedbacks from the motor speed and PI type controller. Due to the order of the closed-loop system, the free location of the system’s poles is not possible. Large oscillations can be expected in responses of the plant. In order to improve the characteristics of the drive, the tuning methodology based on the D-decomposition technique is proposed. The initial working point is selected using an analytical formula. Then the value of controller proportional gain is decreasing, until the required value of overshoot is obtained. In the paper different advantages of the D-decomposition technique are present... [more]

Cities constitute three quarters of global energy consumption and the built environment is responsible for significant use of final energy (62%) and greenhouse gas emissions (55%). Energy has now become a strategic issue for local authorities (LAs) and can offer savings when budget cuts have threatened the provision of core services. Progressive LAs are exploring energy savings and carbon reduction opportunities as part of the sustainable and smart city agenda. This paper explores the role of citizens in smart city development as “buildings don’t use energy: people do”. Citizens have the potential to shape transitions towards smart and sustainable futures. This paper contributes to the growing evidence base of citizen engagement in low carbon smart cities by presenting novel insights and practical lessons on how citizen engagement can help in smart city development through co-creation with a focus on energy in the built environment. A case study of Nottingham in the UK, a leading smart... [more]

The paper critically reviews the current state of the art in flow inside sidewall gaps of hydraulic pumps and turbines. It describes the consequences of the presence of this type of flow in turbomachinery and then relates it to other physical phenomena that determine the behavior, operating characteristics, and overall performance of the machine. Despite the small dimensions of the rotor-stator spaces, the flow in these regions can significantly affect the overall flow field and, consequently, efficiency. The circulation of the fluid inside the gaps and secondary flow that is caused by rotating elements influences the disk friction losses, which is of great importance, especially in the case of low specific speed pumps and turbines. The flow pattern affects the pressure distribution inside a machine and, thus, generates axial thrust. The presence of secondary flow also significantly changes the rotordynamics and can bring about undesirable vibrations and acoustics issues. This article... [more]

A large-eddy simulation (LES) of a gaseous hydrogen/liquid oxygen (GH2/LOX) single-injector rocket combustor is performed in this study. The Redlich−Kwong−Peng−Robinson (RK−PR) equation of state is used to simulate the real-gas effect under high-pressure conditions, and the steady laminar flamelet model (SLFM) is implemented to simulate fast chemistry, such as a H2/O2 reaction. From the numerical simulation, the characteristics of time-averaged flow and flame fields are obtained, and their relationship with the real-gas effect is investigated. It is possible to investigate unsteady flame features and the mixing mechanism of propellants in detail by examining multiple snapshots of the field contour. Another purpose of the study is to investigate the differences in flow and flame structures according to the variation in the turbulent Schmidt number. By comparing the simulation result with the natural OH* emission image and temperature profiles from experimental data, the appropriate rang... [more]

This study introduces e-mobility for humanitarian purposes and presents the first investigation of innovative e-mobility transport solutions (e.g., e-bike, e-stretcher, and drone) for mountain rescue. In practice, it is largely unclear which e-mobility transport solutions might be suitable and what selection attributes are to be considered. The subsequent study supports the technology selection process by identifying and measuring relevant selection attributes to facilitate the adoption of e-mobility in this domain. For the purpose of this study, a multi-method research approach that combines qualitative and quantitative elements was applied. In the first step, results of a systematic search for attributes in literature were combined with inputs gained from unstructured expert interviews and discussions. The perceived importance of the identified selection attributes was then measured by analyzing survey data of 341 rescue workers using the best-worst scaling methodology. Finally, the... [more]

Cold-chain products are time-sensitive and perishable and pose the risk of failure if they are transported to a distant location. Thus, there is a need to analyze their quality during distribution so that the customers may receive optimal-quality products. To address this issue, this study integrates inspection strategies with the sustainable distribution system of multi-quality multiple-cold-chain products. A bi-objective model of cost and emission is proposed under the constraints of heterogeneous vehicle and time window. Furthermore, this study intends to address the following questions: which inspection strategy helps to ensure the potency of delivered products, and what is the impact of quality differentiation on the value of objective functions? A set of meta-heuristics is used for implementing the model using a rich panel of experiments. The results reveal that the quality conditions of different products impact the solutions of cost and emissions. Moreover, the conformity strat... [more]

The etching of Si wafers significantly influences the efficiency of photovoltaic devices. Texturing can effectively decrease front surface reflection and improve device performance. Saw damage removal (SDR) is necessary to yields uniform random pyramidal surfaces without the appearance of saw marks, it entails significant consumption of chemical solutions and complicated cleaning steps. Herein, an alternative process of pre-texturing thermal treatment was carried out at 800 °C for 10 min, followed by anisotropic texturing, and a uniform pyramidal surface over a large area of the textured surface was obtained without saw marks. Compared with that of as-cut mono-Si wafers (30.7%), the weighted average reflectance of the samples textured with or without thermal treatment decreased to 11.2% and 11.9%, respectively, and further to 3% and 3.4%, respectively, when anti-reflection coatings were applied. In addition, saw marks on the wafer surface were used as gettering sites during thermal tre... [more]

The need for fossil fuel alternatives keeps increasing. Bioethanol and biohydrogen have emerged as significant renewable options. However, these bioprocess routes have presented various challenges, which constantly impede commercialization. Most of these bottlenecks are hinged on feedstock logistics, low biofuel yield and enormous process costs. Meanwhile, a large output of renewable energy can be generated from mixed starch-based agricultural wastes due to their intrinsic bioenergy characteristics. This study, therefore, focuses on the production of bioethanol and biohydrogen from mixed starch-based agricultural wastes. The content further highlights the current challenges of their individual processes and elucidates the prospects for improvement, through an integrated biofuel approach. The use of mixed starch-based agricultural wastes as substrates for integrated bioethanol and biohydrogen production was proposed. Furthermore, the use of mixture-based experimental design for the dete... [more]

Methanol production via carbon dioxide (CO2) hydrogenation is a green chemical process, which can reduce CO2 emission. The operating conditions for minimum methanol production cost of three configurations were investigated in this work. An artificial neural network with Latin hypercube sampling technique was applied to construct model-represented methanol production. Price sensitivity was performed to study the impacts of the raw materials price on methanol production cost. Price sensitivity results showed that the hydrogen price has a large impact on the methanol production cost. In mathematical modeling using feedforward artificial neural networks, four different numbers of nodes were used to train artificial neural networks. The artificial neural network with eight numbers of nodes showed the most suitable configuration, which yielded the lowest percent error between the actual and predicted methanol production cost. The optimization results showed that the recommended process desig... [more]

Conventional circular double or triple tube type heat exchanger, DHE or THE, is one of the compact heat exchangers; a large number of studies have been performed to improve their heat transfer performance. The authors demonstrated that a petal-shaped special DHE with a large wet perimeter yields a high heat transfer efficiency, η. In this study, the DHE with six or five petals-, five shallow petals-, and circular-inner tubes were used. To further improve the η of the DHE, a THE with a petal-shaped inner tube along with the middle and outer circular tubes were used. Hot water flowed through the inner tube and cold water flowed through the middle and outer tubes as a counter current flow. The heat transfer was approximately equal; however, the flow resistance (pressure loss) of the outer tube of the DHE could be decreased using the middle and outer tubes under the same amount of cold water as the DHE; consequently, the η could be improved. In addition, the effect of changing the flow pat... [more]

Since the widespread deployment of non-dispatchable, intermittent, and highly variable power production from renewable energy sources (RES), the demand for flexible power production has been steadily growing. As new-built dispatchable power plants have not been very quickly adapted to the emerging flexible operation, this task has been addressed by existing plants as well. Existing solid-fuel thermal power plants have undergone an extensive study to increase their flexible operation. Thermodynamic process-modeling tools have been extensively used for plant modeling. Steady- and transient-state simulations have been performed under various operating regimes, supplying valuable results for efficient power-plant operation. Flexibility aspects regarding low-load operation and steady operational conditions are mostly investigated with steady-state simulations. Flexibility aspects related to variation over time such as ramping rates are investigated with transient simulations. The off-design... [more]

To promote the collaborative development of the bio-natural gas (BNG) industry and the integrated energy system (IES), this paper proposes a new commerce operation model considering the gas price adjustment mechanism for the IES with the utilization of bio-natural gas. The bi-level optimization model is used to simulate the clearing process within the open energy market framework, and the uncertainties of variable renewable energy output are modeled with a set of scenarios through the stochastic programming approach. In the upper-level model, the energy management center adjusts the bio-natural gas price rationally to minimize the expected total operating cost and release the price signal to the lower-level model; the lower-level model simulates the sub-markets clearing process to formulate detailed operation schemes. The bi-level model is transformed into a mathematical programming problem with equilibrium constraints (MPEC) through the Karush−Kuhn−Tucher (KKT) condition of the lower-... [more]

The fast pyrolysis of coffee ground for bio-crude oil production was simulated in a tilted-slide reactor. The biochemical composition was derived by an extended biomass characterization method based on the elemental analysis. The simulation was performed in a steady-state and a Lagrangian multiphase model was adopted to describe the transport of sand and biomass particles together with a multistep kinetic mechanism for fast pyrolysis. When the secondary tar cracking reactions were not considered the volatile yield increased monotonically with temperature. The inclusion of secondary reactions could improve the prediction of volatile yield which turn to decrease at higher temperature. It was found that not only the maximum volatile yield but also the corresponding reactor temperature agreed well with the experimental results. At the temperature higher than 550 °C the trend of volatile yield is similar to that of experiment while it is larger at lower reactor temperature. The individual s... [more]

In 2008, the Chartered Institution of Building Services Engineers (CIBSE TM46 UC) presented an annual-fixed thermal energy benchmark of 240 kWh/m2/yr for university campus (UC) buildings as an attempt to reduce energy consumption in public buildings. However, the CIBSE TM46 UC benchmark fails to consider the difference between energy demand in warm and cold months, as the thermal performance of buildings largely depends on the ambient temperature. This paper presents a new generation of monthly thermal energy benchmarks (MTEBs) using two computational methods including mixed-use model and converter model, which consider the variations of thermal demand throughout a year. MTEBs were generated using five basic variables, including mixed activities in the typical college buildings, university campus revised benchmark (UCrb), typical operation of heating systems, activities impact, and heating degree days. The results showed that MTEBs vary from 24 kWh/m2/yr in January to one and nearly ze... [more]

A Chinese traditional narrow street, named Cold-Lane, can create a microclimatic zone that provides pedestrian thermal comfort under hot and humid climate conditions. This phenomenon was observed through experimental measurement during the summer of 2016. The heat transfer rate over the pedestrian body surface was calculated to reveal why pedestrians experience a cool sensation, and computational flow dynamics (CFD) simulation was carried out to study the influence of the street aspect ratio on the shading effect. It was found that the perception of thermal comfort can be attributed mainly to the radiation between the relatively cool surrounding walls and the human body, and the wind velocity has little effect on sensible heat dissipation. The cool horizontal and vertical surfaces in the street canyon are mainly due to the shading effect as a result of the small aspect ratio, which is a typical characteristic of the traditional Chinese street. The shading effect of the high walls on bo... [more]

In this study, dynamic simulations of a wind turbine were performed to predict its dynamic performance, and the results were experimentally validated. The dynamic simulation received time-domain wind speed and direction data and predicted the power output by applying control algorithms. The target wind turbine for the simulation was a 2 MW wind turbine installed in an onshore wind farm. The wind speed and direction data for the simulation were obtained from WindSim, which is a commercial computational fluid dynamics (CFD) code for wind farm design, and measured wind speed and direction data with a mast were used for WindSim. For the simulation, the wind turbine controller was tuned to match the power curve of the target wind turbine. The dynamic simulation was performed for a period of one year, and the results were compared with the results from WindSim and the measurement. It was found from the comparison that the annual energy production (AEP) of a wind turbine can be accurately pre... [more]

As the relative importance of renewable energy in electric power systems increases, the prediction of photovoltaic (PV) power generation has become a crucial technology, for improving stability in the operation of next-generation power systems, such as microgrid and virtual power plants (VPP). In order to improve the accuracy of PV power generation forecasting, a fair amount of research has been applied to weather forecast data (to a learning process). Despite these efforts, the problems of forecasting PV power generation remains challenging since existing methods show limited accuracy due to inappropriate cloud amount forecast data, which are strongly correlated with PV power generation. To address this problem, we propose a PV power forecasting model, including a cloud amount forecasting network trained with satellite images. In addition, our proposed model adopts convolutional self-attention to effectively capture historical features, and thus acquire helpful information from weathe... [more]