The study of the rates of innovative development of various sectors of the modern economy makes it possible to determine the existence of a scientific and practical problem, eliciting the need for urgent identification of the reasons for non-innovative development of Oil and Gas Companies and development of the directions for innovation development. Based on a number of methods, including methods of graphical analysis, time series forecasting, construction of linear trends, correlation analysis and scenario forecasting, the authors stated the fact of the serious depth of the problem of innovative insufficiency in the oil sector in comparison with other sectors and they built six scenarios for the development of these companies. The applied methods made it possible to not only come to the conclusion that with the current level of investment in R&D in the oil and gas sector, Oil Companies may find themselves in difficult conditions, especially if breakthrough technologies show themselves... [more]

In Rwanda, most small-scale hydropower systems are connected to the national grid to supply additional generation capacity. The Rwandan rivers are characterized by low flow-rates and a majority of plants are below 5 MW generation capacity. The purpose of this study is to provide a scientific overview of positive and negative factors affecting the sustainability of small-scale hydropower plants in Rwanda. Based on interviews, field observation, and secondary data for 17 plants, we found that the factors contributing to small-scale hydropower plant sustainability are; favorable regulations and policies supporting sale of electricity to the national grid, sufficient annual rainfall, and suitable topography for run-of-river hydropower plants construction. However, a decrease in river discharge during the dry season affects electricity production while the rainy season is characterized by high levels of sediment and soil erosion. This shortens turbine lifetime, causes unplanned outages, and... [more]

Non-intrusive load monitoring (NILM) is an important research direction and development goal on the distribution side of smart grid, which can significantly improve the timeliness of demand side response and users’ awareness of load. Due to rapid development, deep learning becomes an effective way to optimize NILM. In this paper, we propose a novel load identification method based on long short term memory (LSTM) on deep learning. Sequence-to-point (seq2point) learning is introduced into LSTM. The innovative combination of the LSTM and the seq2point brings their respective advantages together, so that the proposed model can accurately identify the load in process of time series data. In this paper, we proved the feature of reducing identification error in the experimental data, from three datasets, UK-DALE dataset, REDD dataset, and REFIT dataset. In terms of mean absolute error (MAE), the three datasets have increased by 15%, 14%, and 18% respectively; in terms of normalized signal ag... [more]

The paper presents the novel HF-GEN method for determining the characteristics of Electrical Appliance (EA) operating in the end-user environment. The method includes a measurement system that uses a pulse signal generator to improve the quality of EA identification. Its structure and the principles of operation are presented. A method for determining the characteristics of the current signals’ transients using the cross-correlation is described. Its result is the appliance signature with a set of features characterizing its state of operation. The quality of the obtained signature is evaluated in the standard classification task with the aim of identifying the particular appliance’s state based on the analysis of features by three independent algorithms. Experimental results for 15 EAs categories show the usefulness of the proposed approach.

Data-driven models, either simplified or detailed, have been extensively used in the literature for energy assessment in buildings and districts. However, the uncertainty of the estimated parameters, especially of thermal masses in resistance−capacitance (RC) models, still remains a significant challenge, given the wide variety of buildings functionalities, typologies, structures and geometries. Therefore, the sensitivity analysis of the estimated parameters in RC models with respect to different geometric characteristics is necessary to examine the accuracy of identified models. In this work, heavy- and light-structured buildings are simulated in Transient System Simulation Tool (TRNSYS) to analyze the effects of four main geometric characteristics on the total heat demand, maximum heat power and the estimated parameters of an RC model (4R3C), namely net-floor area, windows-to-floor ratio, aspect ratio, and orientation angle. Executing more than 700 simulations in TRNSYS and comparing... [more]

Accurately estimating the online state-of-charge (SOC) of the battery is one of the crucial issues of the battery management system. In this paper, the gas−liquid dynamics (GLD) battery model with direct temperature input is selected to model Li(NiMnCo)O2 battery. The extended Kalman Filter (EKF) algorithm is elaborated to couple the offline model and online model to achieve the goal of quickly eliminating initial errors in the online SOC estimation. An implementation of the hybrid pulse power characterization test is performed to identify the offline parameters and determine the open-circuit voltage vs. SOC curve. Apart from the standard cycles including Constant Current cycle, Federal Urban Driving Schedule cycle, Urban Dynamometer Driving Schedule cycle and Dynamic Stress Test cycle, a combined cycle is constructed for experimental validation. Furthermore, the study of the effect of sampling time on estimation accuracy and the robustness analysis of the initial value are carried out... [more]

Since most of our industries use induction motors, it is essential to develop condition monitoring systems. Nowadays, industries have power quality issues such as sag, swell, harmonics, and transients. Thus, a condition monitoring system should have the ability to detect various faults, even in the presence of power quality issues. Most of the fault diagnosis and condition monitoring methods proposed earlier misidentified the faults and caused the condition monitoring system to fail because of misclassification due to power quality. The proposed method uses power quality data along with starting current data to identify the broken rotor bar and bearing fault in induction motors. The discrete wavelet transform (DWT) is used to decompose the current waveform, and then different features such as mean, standard deviation, entropy, and norm are calculated. The neural network (NN) classifier is used for classifying the faults and for analyzing the classification accuracy for various cases. T... [more]

In this paper the D-decomposition technique is investigated as a source of non-linear boundaries used with the Genetic Algorithm (GA) search of a PI voltage compensator gains of the boost converter operating in Continuous Conduction Mode (CCM). The well known and appreciated boost converter has been chosen as a test object due to its right-half plane zero in the control-to-output (c2o) voltage transfer function. The D-decomposition, as a technique relying on the frequency sweeping, clearly indicates not only the global stability but, in its extended version, regions satisfying the required gain (GM) and phase (PM) margins. Such results are in form of easy to interpret functions KI=f(KP). The functions are easy to convert to the GA constraints. The GA search, with three different performance indexes as the fitness functions, is applied to a control structure with time delays basing on identified c2o voltage transfer functions. The identification took place in an experiment and in simula... [more]

This research focuses on problem identification due to faults in power transformers during operation by using dissolved gas analysis such as key gas, IEC ratio, Duval triangle techniques, and fuzzy logic approaches. Then, the condition of the power transformer is evaluated in terms of the percentage of failure index and internal fault determination. Fuzzy logic with the key gas approach was used to calculate the failure index and identify problems inside the power transformer. At the same time, the IEC three-gas ratio and Duval triangle are subsequently applied to confirm the problems in different failure types covering all possibilities inside the power transformer. After that, the fuzzy logic system was applied and validated with DGA results of 244 transformers as reference cases with satisfactory accuracy. Two transformers were evaluated and practically confirmed by the investigation results of an un-tanked power transformer. Finally, the DGA results of a total of 224 transformers w... [more]

The paper presents the results of a study concerned with the hydrodynamics of an annular downward multiphase flow of gas and two mutually non-mixing liquids through a vertical pipe with a diameter of 12.5 mm. The air, oil and water were used as working media in this study with changes in superficial velocities in the ranges of jg = 0.34−52.5 m/s for air, jo = 0.000165−0.75 m/s for oil, and jw = 0.02−2.5 m/s for water, respectively. The oil density and viscosity were varied within the ranges of ρo = 859−881 kg/m3 and ηo = 29−2190 mPas, respectively. The research involved the identification of multiphase flow patterns and determination of the void fraction of the individual phases. New flow patterns have been identified and described for the gravitational flow conditions of a two-phase water−oil liquid and a three-phase air−water−oil flow. New flow regime maps and equations for the calculation of air, oil and water void fractions have been developed. A good conformity between the calcula... [more]

Distributed photovoltaic power stations are an effective way to develop and utilize solar energy resources. Using high-resolution remote sensing images to obtain the locations, distribution, and areas of distributed photovoltaic power stations over a large region is important to energy companies, government departments, and investors. In this paper, a deep convolutional neural network was used to extract distributed photovoltaic power stations from high-resolution remote sensing images automatically, accurately, and efficiently. Based on a semantic segmentation model with an encoder-decoder structure, a gated fusion module was introduced to address the problem that small photovoltaic panels are difficult to identify. Further, to solve the problems of blurred edges in the segmentation results and that adjacent photovoltaic panels can easily be adhered, this work combines an edge detection network and a semantic segmentation network for multi-task learning to extract the boundaries of ph... [more]

The paper undertakes the problem of proper structuring of multi-criteria decision support models. To achieve that, a methodological framework is proposed. The authors’ framework is the basis for the relevance analysis of individual criteria in any considered decision model. The formal foundations of the authors’ approach provide a reference set of Multi-Criteria Decision Analysis (MCDA) methods (TOPSIS, VIKOR, COMET) along with their similarity coefficients (Spearman correlation coefficients and WS coefficient). In the empirical research, a practical MCDA-based wind farm location problem was studied. Reference rankings of the decision variants were obtained, followed by a set of rankings in which particular criteria were excluded. This was the basis for testing the similarity of the obtained solutions sets, as well as for recommendations in terms of both indicating the high significance and the possible elimination of individual criteria in the original model. When carrying out the ana... [more]

The paper presents the characteristics of the original optoelectronic system for measuring the values of hydrodynamics of two-phase downward gas-very viscous liquid flow. The measurement methods and results of the research on selected values describing gas−oil two-phase flow are presented. The study was conducted in vertical pipes with diameters of 12.5, 16, 22, and 54 mm. The research was conducted with the superficial velocities of air jg = 0−29.9 m/s and oil jl = 0−0.254 m/s, which corresponded to the values of gas stream density gg = (0−37.31) kg/(m2s) and of liquid gl = (0.61−226.87) kg/(m2s), in order to determine the influence of air and oil streams on the character of liquid films. The variations in oil viscosity were applied in the range ηl = (0.055−1.517) Pas. The study results that were obtained with optical probes along with computer image analysis system revealed vast research opportunities in terms of the identification of gas−liquid two-phase downward flow structures tha... [more]

Poor indoor air quality (IAQ) in schools is associated with impacts on pupils’ health and learning performance. We aimed to identify the factors that affect IAQ in primary schools. The following objectives were set: (a) to develop a questionnaire to assess the prevalence of factors in primary schools, (b) to conduct content validity of the questionnaire, and (c) to assess the prevalence of factors that affect the IAQ in Slovenian primary schools. Based on the systematic literature review, we developed a new questionnaire to identify factors that affect the IAQ in primary schools and conducted its validation. The questionnaires were sent to all 454 Slovenian primary schools; the response rate was 78.19%. The results show that the most important outdoor factors were the school’s micro location and the distance from potential sources of pollution, particularly traffic. Among the indoor factors, we did not detect a pronounced dominating factor. Our study shows that the spatial location of... [more]

The prevalence of batch and batch-like operations, in conjunction with the continued resurgence of artificial intelligence techniques for clustering and classification applications, has increasingly motivated the exploration of the applicability of deep learning for modeling and feedback control of batch and batch-like processes. To this end, the present study seeks to evaluate the viability of artificial intelligence in general, and neural networks in particular, toward process modeling and control via a case study. Nonlinear autoregressive with exogeneous input (NARX) networks are evaluated in comparison with subspace models within the framework of model-based control. A batch polymethyl methacrylate (PMMA) polymerization process is chosen as a simulation test-bed. Subspace-based state-space models and NARX networks identified for the process are first compared for their predictive power. The identified models are then implemented in model predictive control (MPC) to compare the cont... [more]

A Duval triangle is a diagram used for fault type identification in dissolved-gas analysis of oil-filled high-voltage transformers and other electrical apparatus. The proportional concentrations of three fault gases (such as methane, ethylene, and acetylene) are used as coordinates to plot a point in an equilateral triangle and identify the fault zone in which it is located. Each point in the triangle corresponds to a unique combination of gas proportions. Diagnostic pentagons published by Duval and others seek to emulate the triangles while incorporating five fault gases instead of three. Unfortunately the mapping of five gas proportions to a point inside a two-dimensional pentagon is many-to-one; consequently, dissimilar combinations of gas proportions are mapped to the same point in the pentagon, resulting in mis-diagnosis. One solution is to replace the pentagon with a four-dimensional simplex, a direct generalization of the Duval triangle. In a comparison using cases confirmed by... [more]

Innovative lighting and dynamic sound systems as well as adaptive object mapping solutions constitute a rapidly developing branch of lighting technology and multimedia technology. In order to make it possible to adjust the content to specific objects in the scene, it is necessary to correctly identify them and place them in the accepted frame of reference. Dynamic identification and tracking of objects can be carried out based on two particular types of input data: data from markers installed on objects and data from digital recording systems, founding the operation on infrared (IR), visible light (RGB) and the most advanced RGB-D (RGB and depth) analysis. Most systems used today are those that use various types of markers. This paper presents the advantages and disadvantages of such solutions as well as a target system for dynamic identification and mapping of objects and the human body based on the analysis of data from digital RGB-D cameras. Analyses of identification times, impleme... [more]

To identify critical parameters upon variable operational temperatures in a planar SOFC, an experimentally agreeable model was established. The significance of temperature effect on the performance of SOFC components was investigated, and the effect of activation energy during the development of intermediate electrode materials was evaluated. It is found the ionic conductivity of electrolytes is identified to be unavoidably concerned in the development of the intermediate-temperature SOFC. The drop of the ionic conductivity of the electrolyte decreases the overall current density 63% and 80% at temperatures reducing to 700 °C and 650 °C from 800 °C. However, there exists a critical value on the defined ratio between the electric resistance of the electrolyte in the overall internal resistance of SOFC, above which the further increase in the ionic conductivity would not significantly improve the performance. The lower the operational temperature, the higher critical ratio of the electri... [more]

Reducing emissions of pollutants from transport is clearly one of the main challenges of the constantly developing world. Because the environmental impact of different means of transport is significant, it is necessary to cut down on fossil fuels and turn to more eco-friendly solutions, e.g., electric vehicles. Almost all European countries are now adapting their transport policies to this new paradigm. Nonetheless, due to large economic disparities, these processes are currently at different levels of implementation in Western and Eastern Europe. The main focus is on private electric cars and more traditional means of transport, rather than water trams. This article presents possible means of developing water tram lines in Gdańsk served by hybrid or full-electric vehicles. The analysis presented herein reflects the multidimensional nature of the issue. The article provides data on the socio-economic situation in the city, technical issues related to the implementation of such tram lin... [more]

Bridges are a critical piece of infrastructure in the network of road and rail transport system. Many of the bridges in Norway (in Europe) are at the end of their lifespan, therefore regular inspection and maintenance are critical to ensure the safety of their operations. However, the traditional inspection procedures and resources required are so time consuming and costly that there exists a significant maintenance backlog. The central thrust of this paper is to demonstrate the significant benefits of adapting a Unmanned Aerial Vehicle (UAV)-assisted inspection to reduce the time and costs of bridge inspection and established the research needs associated with the processing of the (big) data produced by such autonomous technologies. In this regard, a methodology is proposed for analysing the bridge damage that comprises three key stages, (i) data collection and model training, where one performs experiments and trials to perfect drone flights for inspection using case study bridges t... [more]

Real-time multiparameter identification has been widely investigated in relation to high-performance control and fault diagnosis of salient-pole permanent magnet synchronous motors (PMSMs). However, it is rank-deficient for simultaneously estimating flux, resistance, and dq-axis inductances based on one steady state under maximum torque per ampere (MTPA) control, which will cause the ill-convergence problem in the results. This paper proposes a new method to solve the rank deficiency problem in the multiparameter identification of salient-pole PMSMs in systems where the motor working conditions do not change frequently. For this type of system, a second steady state is constructed in order to meet the full-rank conditions for multiparameter identification and minimize the torque ripple. Furthermore, in order to reduce the influence of inductance variations, a better shift direction from the first steady state to the second is ensured based on the analysis of the theoretical error. Simu... [more]

The COVID-19 outbreak and ensuing social distancing behaviors resulted in substantial reduction on traffic, making this a unique experiment on observing the air quality. Such an experiment is also supplemental to the smart city concept as it can help to identify whether there is a delay on air quality improvement during or after a sharp decline on traffic and to determine what, if any, factors are contributing to that time lag. As such, this study investigates the immediate impacts of COVID-19 causing abrupt declines on traffic and NO2 concentration in all Florida Counties through March 2020. Daily tropospheric NO2 concentrations were extracted from the Sentinel-5 Precursor satellite and vehicle mile traveled (VMT) estimates were acquired from cell phone mobility records. It is observed that overall impacts of the COVID-19 response in Florida have started in the first half of the March 2020, two weeks earlier than the official stay-at-home orders, and resulted in 54.07% and 59.68% decr... [more]

An integrated geological and geophysical approach is presented for the recognition of unconventional targets in the Miocene formations of the Carpathian Foredeep, southern Poland. The subject of the analysis is an unconventional reservoir built of interlayered packets of sandstone, mudstone and claystone, called a “heterogeneous sequence”. This type of sequence acts as both a reservoir and as source rock for hydrocarbons and it consists of layers of insignificant thickness, below the resolution of seismic data. The interpretation of such a sequence has rarely been based on seismic stratigraphy analysis; however, such an approach is proposed here. The subject of interpretation is high-quality seismic data of high resolution that enable detailed depositional analysis. The reconstruction of the depositional history was possible due to the analysis of flattened chronostratigraphic horizons (Wheeler diagram). The identification of depositional positions in a sedimentary basin was the first... [more]

In this paper, a series arc was simulated under resistive load and motor load, which are mainly used in small ships, and the arc signal was analyzed using discrete wavelet transform. After calculating the correlation coefficient between the single arc pulse and the wavelet, Biorthogonal (bior) 3.1 was selected as the optimal mother wavelet, and the signal was analyzed using multiresolution analysis. From the results, arc signals were distributed in the detail components D2, D3, D4 and D5, corresponding to a frequency range of 19.5−312.5 kHz, with the optimal arc signal extracted based on these values. In addition, in order to distinguish between arc and normal conditions, signal energy was analyzed. By applying the magnitude and signal energy analysis method, the DC series arc generated in the power distribution system of a shipboard was identified.

The electric vehicle has become an important development direction of the automobile industry, and the lithium-ion power battery is the main energy source of electric vehicles. The accuracy of state of charge (SOC) estimation directly affects the performance of the vehicle. In this paper, the first order fractional equivalent circuit model of a lithium iron phosphate battery was established. Battery capacity tests with different charging and discharging rates and open circuit voltage tests were carried out under different ambient temperatures. The conversion coefficient of charging and discharging capacity and the simplified open circuit voltage model considering the hysteresis characteristics of the battery were proposed. The parameters of the first order fractional equivalent circuit model were identified by using a particle swarm optimization algorithm with dynamic inertia weight. Finally, the recursive formula of a fractional extended Kalman filter was derived, and the battery SOC... [more]