Supervisory Control and Data Acquisition (SCADA) systems are essential for reliable communication and control of smart grids. However, in the cyber-physical realm, it becomes highly vulnerable to cyber-attacks like False Data Injection (FDI) into the measurement signal which can circumvent the conventional detection methods and interfere with the normal operation of grids, which in turn could potentially lead to huge financial losses and can have a large impact on public safety. It is imperative to have an accurate state estimation of power consumption for further operational decision-making.This work presents novel forecasting-aided anomaly detection using an CNN-LSTM based auto-encoder sequence to sequence architecture to combat against false data injection attacks. We further present an adaptive optimal threshold based on the consumption patterns to identify abnormal behaviour. Evaluation is performed on real-time energy demand consumption data collected from the Australian Energy M... [more]

In this paper, we explore the improvement of the aerodynamic characteristics of wind turbine blades under stall conditions using passive flow control with slots. The National Renewable Energy Laboratory (NREL) Phase II rotor, for which detailed simulations and experimental data are available, served as a baseline for assessing the flow control system effects. The position and configuration of the slot used as a flow control system were determined using CFD analysis. The 3D-RANS equations are solved with ANSYS FLUENT using the k-ω SST turbulence closure model. The pressure coefficient for different wind speeds for the baseline configuration is compared to the available experimental data. The comparison shows that CFD results were better for the attached flow. The current work consists of a 3-D CFD modeling of a rotating blade equipped with different flow control systems: single-slot (S-S) and two-slots (T-S). The computation provides a better understanding of the influence of these flow... [more]

The energy use intensity (EUI) of convenience stores was substantially higher than that of office buildings and hotels, due to a compact footprint but a high density of equipment yielded a higher EUI. As a result, it is critical to assess and maintain the state of the convenience store in order to obtain a lower EUI and reduce energy consumption. This study utilizes a convenience store to evaluate energy consumption and perform a CFD simulation to see how the environment influences by cold storage showcase (CSS) equipment. On the basis of field testing and on-site web-based monitoring data, a survey of baseline information through data collecting and energy benchmarking data has been provided and extensively examined. According to energy monitoring, the convenience store’s highest electricity use is 23,055 kWh in June, and the lowest power consumption is 15,216 kWh in February. The CFD simulation results revealed that the temperature near the CSS can be 3−5 °C lower than in other regio... [more]

The thermophysical properties of a working-fluid play an important role in the process of stirring-heating. The heating process of stirring is accompanied by two processes: the friction between the solid mechanism and the working-fluid and the viscous dissipation of the working liquid. Traditionally, the sensible heat of water-based working-fluids is low, while that of oil-based working-fluids is higher, but the load capacity is relatively low. In order to find a balance between the two, an optimal stirring working-fluid should be selected. In this study, an experimental method was used to study the heating process of 30 kinds of working-fluids. The numerical evaluation model of the effects of thermophysical properties on the comprehensive evaluation index of heat (CEIH) was established by multiple linear regression methods, and a computational fluid dynamics (CFD) tool was used to analyze the heat generation and flow field of different working-fluids in the stirring-heating device. Th... [more]

The generation of synthetic vibration signals enables the testing of novel machine diagnostic methods without the costly introduction of real failures. One of major goals of vibration-based condition monitoring is the early detection of bearing faults. This paper presents a novel modeling technique based on the combination of the known mechanical properties of a modeled object (phenomenological part) and observation of a real object (behavioral part). The model uses the real pulse response of bearing housing, along with the external instantaneous machine speed profile. The presented method is object-oriented, so it is applicable to a large group of machinery.

The transition toward high shares of non-programmable renewable energy sources in the power grid requires an increase in the grid flexibility to guarantee grid reliability and stability. This work, developed within the EU project Grasshopper, identifies hydrogen Fuel Cell (FC) power plants, based on low temperature PEM cells, as a source of flexibility for the power grid. A dynamic numerical model of the flexible FC system is developed and tested against experimental data from a 100-kW pilot plant, built within the Grasshopper project. The model is then applied to assess the flexible performance of a 1 MW system in order to optimize the scale-up of the pilot plant to the MW-size. Simulations of load-following operation show the flexibility of the plant, which can ramp up and down with a ramp rate depending only on an externally imposed limit. Warm-up simulations allow proposing solutions to limit the warm-up time. Of main importance are the minimization of the water inventory in the sy... [more]

The efficient use of renewable energy is receiving more and more attention in the context of “carbon neutrality” and “carbon peaking”. For a long time, biomass has been used less efficiently as a renewable energy source, but with the development of fluidized biomass gasification technology, it can play an increasing role in industrial production. A fluidized bed biomass gasifier has a strong nonstationary process due to its complex energy−mass exchange, and analysis of its complex reaction process and products has relied on experiments for a long time. This paper uses a Euler−Euler two-fluid model to establish a three-dimensional CFD model of the fluidized bed biomass gasifier, on which factors affecting syngas generation are analyzed. The simulation shows that increasing the initial bed temperature can effectively improve syngas production, while increasing the air equivalent is not beneficial for syngas production.

The majority of marine hydrates are buried in unconsolidated or poorly consolidated marine sediments with limited cementation and strength. As a result, hydrate decomposition during production may cause significant subsidence of the formation, necessitating a halt in production. The numerical model of unconsolidated hydrate formation, based on geomechanics, was established in order to elucidate the depressurization production process. The sensitive factors of unconsolidated hydrate production were determined by analyzing the influence of formation parameters and production parameters on gas production. Then, a safety formation subsidence was proposed in this paper, and the appropriate well type and parameters for the safe and efficient production of hydrates in unconsolidated formations of various saturations were determined. The sensitivity of gas production to the formation parameters was in the order of formation porosity, hydrate saturation, and buried depth, while the effects of t... [more]

The modelling of surges within PV (photovoltaic) installations has been the subject of much research in recent years. However, accurate simulations cannot be performed unless each and every component within a PV installation is modelled in sufficient detail. The bypass diodes within a PV module are frequently omitted from such simulations. When included, they are often represented by oversimplified models. This article addresses this need by presenting SPICE (Simulation Program with Integrated Circuit Emphasis) models for three Schottky diodes, chosen due to their suitability for use as bypass diodes. These models are the combination of DC (direct current) large-signal and AC (alternating current) small-signal sub-models, which are integrated such that the resulting full circuital models allow for accurate simulations involving large-signal transient stimuli. Two types of experimental setups, one incorporating a DC current−voltage curve sweep, and the other involving VNA-based (vector... [more]

In view of the flow instability problem caused by the strong shock wave and secondary flow in the channel of the high-load counter-rotating compressor, this paper adopts the design method of coupling aerodynamic optimization technology and CFD and establishes a three-dimensional aerodynamic optimization design platform for the blade channel based on an artificial neural network and genetic algorithm. The aerodynamic optimization design and internal flow-field diagnosis of a high-load counter-rotating compressor with a 1/2 + 1 aerodynamic configuration are carried out. The research indicates that the optimized blade channel can drive and adjust the flow better, and the expected supercharging purpose and efficient energy conversion process are achieved by controlling the intensity of the shock wave and secondary flow in the channel. The total pressure ratio at the design point of the compressor exceeds 2.9, the adiabatic efficiency reaches 87%, and the aerodynamic performance is excellen... [more]

This study aims to develop a predictive and reliable data-driven model for forecasting the fluid production (oil, gas, and water) of existing wells and future infill wells for CO2-enhanced oil recovery (EOR) and CO2 storage projects. Several models were investigated, such as auto-regressive (AR), multilayer perceptron (MLP), and long short-term memory (LSTM) networks. The models were trained based on static and dynamic parameters and daily fluid production while considering the inverse distance of neighboring wells. The developed models were evaluated using walk-forward validation and compared based on the quality metrics, span, and variation in the forecasting horizon. The AR model demonstrates a convincing generalization performance across various time series datasets with a long but varied forecasting horizon across eight wells. The LSTM model has a shorter forecasting horizon but strong generalizability and robustness in forecasting horizon consistency. MLP has the shortest and mos... [more]

As a new energy source, gas hydrates have attracted worldwide attention, but their exploration and development face enormous challenges. Thus, it has become increasingly crucial to identify hydrate distribution accurately. Electrical resistivity tomography (ERT) can be used to detect the distribution of hydrate deposits. An ERT inversion network (ERTInvNet) based on a deep neural network (DNN) is proposed, with strong learning and memory capabilities to solve the ERT nonlinear inversion problem. 160,000 samples about hydrate distribution are generated by numerical simulation, of which 10% are used for testing. The impact of different deep learning parameters (such as loss function, activation function, and optimizer) on the performance of ERT inversion is investigated to obtain a more accurate hydrate distribution. When the Logcosh loss function is enabled in ERTInvNet, the average correlation coefficient (CC) and relative error (RE) of all samples in the test sets are 0.9511 and 0.109... [more]

For assessment of the insulation performance of high-voltage (HV) equipment installed in extra-high-voltage (EHV) systems, switching impulse voltage tests are performed in an HV testing laboratory. The waveform parameters of the switching impulse voltages are defined by peak voltage (Up), time to crest (Tp), and time to half (T2) according to IEC 60060-1. In this paper, a new, simplified, and accurate approach used for determination of the waveform parameters of the switching impulse voltages is presented. The formula used in the evaluation of Tp was derived from analytically simulated two-exponential waveforms, where Tp and T2 are in the ranges of 20 μs to 300 μs and 1000 μs to 4000 μs, respectively. The accuracy of the proposed approach was validated by the waveforms collected from the test waveform data generator (TDG) provided by IEC 61083-2, simulations, and experiments. It is found that the accuracy of the proposed approach is relatively higher than the expressions provided by IE... [more]

This paper proposes a novel network anomaly detection framework based on data balance and feature selection. Different from the previous binary classification of network intrusion, the network anomaly detection strategy proposed in this paper solves the problem of multiple classification of network intrusion. Regarding the common data imbalance of a network intrusion detection set, a resampling strategy generated by random sampling and Borderline SMOTE data is developed for data balance. According to the features of the intrusion detection dataset, feature selection is carried out based on information gain rate. Experiments are carried out on three basic machine learning algorithms (K-nearest neighbor algorithm (KNN), decision tree (DT), random forest (RF)), and the optimal feature selection scheme is obtained.

The shift toward electric mobility in Germany is a major component of the German climate protection program. In this context, public charging is growing in importance, especially in high-density urban areas, which causes an additional load on the distribution grid. In order to evaluate this impact and prevent possible overloads, realistic models are required. Methods for implementing such models and their application in the context of grid load are research topics that are only minorly addressed in the literature. This paper aims to demonstrate the entire process chain from the selection of a modelling method to the implementation and application of the model within a case study. Applying a stochastic approach, charging points are modelled via probabilities to determine the start of charging, plug-in duration, and charged energy. Subsequently, load profiles are calculated, integrated into an energy system model and applied in order to analyze the effects of a high density of public cha... [more]

With the development of power plant units of higher capacity and with improved parameters, the proportion of high-capacity units for generating power has increased; this requires large capacity units to take responsibility for power-grid peak shaving. When the boiler operates at low loads, the working fluid in the boiler water wall tubes is subjected to high heat flux in the furnace, which can cause heat transfer deterioration, tube overheating or even leakage. Therefore, it is particularly important to study the reliability of the boiler hydrodynamic cycle during peak shaving (low load operation). This study takes a 1000 MW ultra-supercritical single-reheat Π type boiler with single furnace and double tangential firing as the research object. A furnace Computational Fluid Dynamics (CFD) and hydrodynamic coupling analysis model is established and verified according to the actual operating conditions on site. The calculation results show that the simulated value is in good agreement wit... [more]

Epoxy insulators are widely used in Gas-Insulated Transmission Lines (GILs), playing a significant role in electrical insulation and mechanical support. The metal particles generated during the production and operation of the equipment aggravate surface charge accumulation on the insulator, causing surface flashover. Therefore, it is necessary to study the suppression strategy of charge accumulation. In this paper, a downsized disc insulator was taken as the research object to investigate the effect of zoning coating on charge suppression with the presence of a linear aluminum metal particle under negative DC voltage. The zoning coating method was achieved by painting coatings with different conductivities in three areas on the insulator surface to regulate the charge. The inhibition mechanism of zoning coating on the charge accumulation in the presence of a linear metal particle was analyzed with the assistance of numerical simulation. The results showed that negative charges were acc... [more]

Thermodynamic models are usually employed to predict formation condition of hydrates. However, these thermodynamic models usually require a large amount of calculations to approach phase equilibrium. Additionally, parameters included in the thermodynamic model need to be calibrated based on the experimental data, which leads to high uncertainties in the predicted results. With the rapid development of artificial intelligence (AI), machine learning as one of sub-discipline has been developed and been widely applied in various research area. In this work, machine learning was innovatively employed to predict the formation condition of natural gas hydrates to overcome the high computation cost and low accuracy. Three data-driven models, Random Forest (RF), Naive Bayes (NB), Support Vector Regression (SVR) were tentatively used to determine the formation condition of hydrate formed by pure and mixed gases. Experimental data reported in previous work were taken to train and test the machine... [more]

The application of energy-efficiency strategies in buildings is a hot topic around the world; in some countries, there are regulations with more or less degree of compliance, but in most countries located in the tropical zone, there are no regulations, and it is not easy to transfer regulations of countries outside of tropical zone. For countries located in tropical zones, the implementation of strategies to reduce the heat flow from outside to inside buildings is a key point. As a case study, the Dominican Republic (DR) was chosen, and during 2020, an analysis focusing on buildings of the tertiary level was carried out with the goal of using scientific methodology focused on tropical climates that allows for a significant reduction in energy consumption by implementing Energy Efficiency Strategies (EESs) that are available, with minimal intrusion into the building and low cost. The study includes, as parts of the proposed methodology, the characterization of building parks, including... [more]

Simulation based studies for operational energy system analysis play a significant role in evaluation of various new age technologies and concepts in the energy grid. Various modelling approaches already exist and in this original paper, four models representing these approaches are compared in two real-world hybrid energy system scenarios. The models, namely TransiEnt, µGRiDS, and OpSim (including pandaprosumer and mosaic) are classified into component-oriented or system-oriented approaches as deduced from the literature research. The methodology section describes their differences under standard conditions and the necessary parameterization for the purpose of creating a framework facilitating a closest possible comparison. A novel methodology for scenario generation is also explained. The results help to quantify primary differences in these approaches that are also identified in literature and qualify the influence of the accuracy of the models for application in a system-wide analy... [more]

(1) Background: The present development of transport networks focusses on the better management of fuels and energy and the preservation of the environment. To fulfill these desiderates, some countries have already reconsidered the deployment plans of new highways. This research studies the feasibility of less polluting, quasi-self-powered, intelligent highway infrastructure functional blocks accommodating functions for the future introduction of smart wireless sensor grids and connected autonomous vehicles. Subject of investigation are the possibilities of energy harvesting, and the intelligent management of resources. (2) Methods: the research investigates the main technologies for energy harvesting and recommends an optimal solution. It also proposes a framework for the intelligent, AI-based management of energy and the use of an optimized backup solution relying on 5G beamforming for energy supply of the local wireless sensing network devices; (3) Results: recommendations are made... [more]

The variation in the two-phase flow parameters in a cylindrical body of new geometry and principle of operation are considered for a device for separating solids from air flow, solving the problem of numerical flow modeling. The aim of this research was to analyze the changes in the parameters of a multi-channel cylindrical cyclone in a mathematical model and to compare it with the results of the examined physical model. Studies on the numerical modeling of cyclones are reviewed, and models and equations for complex vortex flow description are applied. Differential equations were numerically solved by the finite volume method using the standard turbulence models of k−ε and RNG k−ε. Numerical modeling of the velocities, pressures, and volumes of both phases of the two-phase flow was performed. The simulation of the volume distribution of the second phase (glass particles) in the cyclone structure at flow rates of 10.9 m/s, 13.9 m/s, and 21.9 m/s was performed. The values obtained were c... [more]

Saving energy while maintaining a high-quality internal environment is an increasingly important scientific and technological challenge in the building sector. This paper presents the results from a long-term study on thermal comfort in a passive house situated in the south of Poland. The building was constructed in 2010 with the use of prefabricated, lightweight technology. The main energy source is a ground source heat pump which powers the floor heating and DHW. The building is also equipped with a mechanical ventilation system with heat recovery and a ground source heat exchanger. A lightweight building structure which has active systems with limited capabilities (especially for cooling) is a combination which increases the difficulty of maintaining a proper inner environmental condition. Extensive experimental investigations on hygrothermal performance and energy use have been carried out in the building for several years. The measurement results, such as inner air temperature and... [more]

A variety of mathematical models are available to estimate the thermal performance of buildings. Nevertheless, mathematical models predict the thermal performance of buildings that might differ from the actual performance. The hot box is a widely-used test apparatus to assess the actual thermal performance of various building envelope components (walls, roofs, windows) in the laboratory. This paper presents the process of designing, constructing, and calibrating a unique small-scale hot box apparatus. Despite its smaller metering area (1.0 m × 1.0 m), this apparatus met the key requirements (below ±0.25 °C fluctuations in chambers’ air temperature, and below 2.0% variation from the point-to-point temperature in reference to the temperature difference across the specimen) as prescribed in the ASTM C1363 and ISO 8990 standards. The walls of this apparatus are uniquely constructed using vacuum insulation panels or VIPs. The efficient and novel use of VIPs and workmanship during the constr... [more]

This paper describes the simulative approach to calibrate an already extremely highly turbocharged industrial diesel engine for higher low-speed torque. The engine, which is already operating at its cylinder-pressure maximum, is to achieve close to 30 bar effective mean pressure through suitable calibration between the compression ratio, piston-bowl shape and injection strategy. The basic idea of the study is to lower the compression ratio for even higher injection masses and boost pressures, with the resulting disadvantages in the area of emissions and fuel consumption being partially compensated for by optimizations in the areas of piston shape and injection strategy. The simulations primarily involve the use of the 3D CFD software Converge CFD for in-cylinder calibration and a fully predictive 1D full-engine model in GT Suite. The simulations are based on a two-stage turbocharged 1950 cc four-cylinder industrial diesel engine, which is used for validation of the initial simulation.... [more]