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Date submitted2023-10-29
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Date accepted2024-04-08
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Date published2025-02-25
Evaluation of the impact of the distance determination function on the results of optimization of the geographical placement of renewable energy sources-based generation using a metaheuristic algorithm
- Authors:
- Andrei M. Bramm
- Stanislav A. Eroshenko
Since the United Power System was created electrical supply of remote and hard-to-reach areas remains one of the topical issues for the power industry of Russia. Nowadays, usage of various renewable energy sources to supply electricity at remote areas has become feasible alternative to usage of diesel-based generation. It becomes more suitable with world decarbonization trends, the doctrine of energy security of Russia directives, and equipment cost decreasing for renewable energy sources-based power plants construction. Geological exploration is usually conducted at remote territories, where the centralized electrical supply can not be realized. Placement of large capacity renewable energy sources-based generation at the areas of geological expeditions looks perspective due to development of industrial clusters and residential consumers of electrical energy at those territories later on. Various metaheuristic methods are used to solve the task of optimal renewable energy sources-based generation geographical placement. The efficiency of metaheuristics depends on proper tuning of that methods hyperparameters, and high quality of big amount of meteorological and climatic data. The research of the effects of the calculation methods defining distance between agents of the algorithm on the optimization of renewable generation placement results is presented in this article. Two methods were studied: Euclidean distance and haversine distance. There were two cases considered to evaluate the effects of distance calculation method change. The first one was for a photovoltaic power plant with installed capacity of 45 MW placement at the Vagaiskii district of the Tyumen region. The second one was for a wind power plant with installed capacity of 25 MW at the Tungokochenskii district of the Trans-Baikal territory. The obtained results show low effects of distance calculation method change at average but the importance of its proper choose in case of wind power optimal placement, especially for local optima’s identification.
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Date submitted2023-11-10
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Date accepted2024-06-03
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Date published2025-02-25
Enhancing the interpretability of electricity consumption forecasting models for mining enterprises using SHapley Additive exPlanations
- Authors:
- Pavel V. Matrenin
- Alina I. Stepanova
The objective of this study is to enhance user trust in electricity consumption forecasting systems for mining enterprises by applying explainable artificial intelligence methods that provide not only forecasts but also their justifications. The research object comprises a complex of mines and ore processing plants of a company purchasing electricity on the wholesale electricity and power market. Hourly electricity consumption data for two years, schedules of planned repairs and equipment shutdowns, and meteorological data were utilized. Ensemble decision trees were applied for time series forecasting, and an analysis of the impact of various factors on forecasting accuracy was conducted. An algorithm for interpreting forecast results using the SHapley Additive exPlanation method was proposed. The mean absolute percentage error was 7.84 % with consideration of meteorological factors, 7.41 % with consideration of meteorological factors and a load plan formulated by an expert, and the expert's forecast error was 9.85 %. The results indicate that the increased accuracy of electricity consumption forecasting, considering additional factors, further improves when combining machine learning methods with expert evaluation. The development of such a system is only feasible using explainable artificial intelligence models.
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Date submitted2024-06-12
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Date accepted2024-07-18
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Date published2025-04-25
Development of parameters for an industry-specific methodology for calculating the electric energy storage system for gas industry facilities
- Authors:
- Ivan S. Tokarev
The issue of determining the main parameters of electric energy storage systems – power and energy intensity – is being considered, the determination of which is a fundamentally important task when introducing such devices into the power supply systems of enterprises for both technical (technological) and economic reasons. The work analyzes problems that can be solved by installing electricity storage systems at gas industry facilities. An industry-wide methodology has been developed for calculating the parameters of an electricity storage system based on traditional methods and methods aimed at minimizing the standardized cost of electricity with adaptation to the conditions of the gas industry. A distinctive feature of the presented methodology is the ability to determine the power and energy intensity of electricity storage systems when performing several functions. The methodology was tested at a typical gas industry facility – the Yarynskaya compressor station of OOO Gazprom Transgaz Ukhta, a characteristic feature of which is an autonomous power supply system. An example is given of calculating the electricity storage normalized cost using an improved LCOS indicator, which takes into account the effect of changing the fill factor of the electrical load schedule on the amount of gas consumption by a power plant for its own needs. To confirm the economic efficiency of introducing electricity storage systems calculated using the above methodology, calculations of the integral effect, net present value and efficiency index are presented.
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Date submitted2021-05-12
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Date accepted2022-05-11
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Date published2023-07-19
Application of the cybernetic approach to price-dependent demand response for underground mining enterprise electricity consumption
The article considers a cybernetic model for the price-dependent demand response (DR) consumed by an underground mining enterprise (UGME), in particular, the main fan unit (MFU). A scheme of the model for managing the energy consumption of a MFU in the DR mode and the implementation of the cybernetic approach to the DR based on the IoT platform are proposed. The main functional requirements and the algorithm of the platform operation are described, the interaction of the platform with the UGME digital model simulator, on which the processes associated with the implementation of the technological process of ventilation and electricity demand response will be simulated in advance, is shown. The results of modeling the reduction in the load on the MFU of a mining enterprise for the day ahead are given. The presented solution makes it possible to determine in advance the necessary power consumption for the operation of the main power supply unit, manage its operation in an energy-saving mode and take into account the predicted changes in the planned one (e.g., when men hoisting along an air shaft) and unscheduled (e.g., when changing outdoor air parameters) modes. The results of the study can be used to reduce the cost of UGME without compromising the safety of technological processes, both through the implementation of energy-saving technical, technological or other measures, and with the participation of enterprises in the DR market. The proposed model ensures a guaranteed receipt of financial compensation for the UGME due to a reasonable change in the power consumption profile of the MFU during the hours of high demand for electricity, set by the system operator of the Unified Energy System.
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Date submitted2023-03-14
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Date accepted2023-06-20
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Date published2023-07-19
Forecasting planned electricity consumption for the united power system using machine learning
The paper presents the results of studies of the predictive models development based on retrospective data on planned electricity consumption in the region with a significant share of enterprises in the mineral resource complex. Since the energy intensity of the industry remains quite high, the task of rationalizing the consumption of electricity is relevant. One of the ways to improve control accuracy when planning energy costs is to forecast electrical loads. Despite the large number of scientific papers on the topic of electricity consumption forecasting, this problem remains relevant due to the changing requirements of the wholesale electricity and power market to the accuracy of forecasts. Therefore, the purpose of this study is to support management decisions in the process of planning the volume of electricity consumption. To realize this, it is necessary to create a predictive model and determine the prospective power consumption of the power system. For this purpose, the collection and analysis of initial data, their preprocessing, selection of features, creation of models, and their optimization were carried out. The created models are based on historical data on planned power consumption, power system performance (frequency), as well as meteorological data. The research methods were: ensemble methods of machine learning (random forest, gradient boosting algorithms, such as XGBoost and CatBoost) and a long short-term memory recurrent neural network model (LSTM). The models obtained as a result of the conducted studies allow creating short-term forecasts of power consumption with a fairly high precision (for a period from one day to a week). The use of models based on gradient boosting algorithms and neural network models made it possible to obtain a forecast with an error of less than 1 %, which makes it possible to recommend the models described in the paper for use in forecasting the planned electricity power consumption of united power systems.
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Date submitted2022-05-13
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Date accepted2022-09-24
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Date published2022-11-03
Rapid detection of coal ash based on machine learning and X-ray fluorescence
Real-time testing of coal ash plays a vital role in the chemical, power generation, metallurgical, and coal separation sectors. The rapid online testing of coal ash using radiation measurement as the mainstream technology has problems such as strict coal sample requirements, poor radiation safety, low accuracy, and complicated equipment replacement. In this study, an intelligent detection technique based on feed-forward neural networks and improved particle swarm optimization (IPSO-FNN) is proposed to predict coal quality ash content in a fast, accurate, safe，and convenient manner. The data set was obtained by testing the elemental content of 198 coal samples with X-ray fluorescence (XRF). The types of input elements for machine learning (Si, Al, Fe, K, Ca, Mg, Ti, Zn, Na, P) were determined by combining the X-ray photoelectron spectroscopy (XPS) data with the change in the physical phase of each element in the coal samples during combustion. The mean squared error and coefficient of determination were chosen as the performance measures for the model. The results show that the IPSO algorithm is useful in adjusting the optimal number of nodes in the hidden layer. The IPSO-FNN model has strong prediction ability and good accuracy in coal ash prediction. The effect of the input element content of the IPSO-FNN model on the ash content was investigated, and it was found that the potassium content was the most significant factor affecting the ash content. This study is essential for real-time online, accurate, and fast prediction of coal ash.
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Date submitted2021-09-22
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Date accepted2021-11-30
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Date published2021-12-27
Possibilities for creating Russian high-tech bottomhole assembly
Development of high-tech well electronic measuring systems is aimed at creating modern equipment: telemetry, well geophysical measurement equipment, the architecture of which is divided into basic (with measurement channels for gamma logging and inductive resistance) and advanced (with radioactive, acoustic, magnetic resonance and thermobarometric measurement channels, including azimuthal methods of investigation). Over-the-bit measurement modules, rotary steerable systems are being developed and channels for transmitting data to the surface are being improved. Vice versa, specialized surface equipment with highly integrated software is being created. Different measurement modules are manufactured by different companies, which creates uncertainties in the possibility of interfacing the manufacturers' measurement modules into a single well measurement system. The article presents an analysis of the readiness of Russian oil service companies to produce well and surface equipment for drilling Russian directional oil and gas wells, meeting modern requirements for accuracy, lifetime and operating conditions. The possibility of creating a fully Russian well high-tech equipment and the required resources, risks and measures to mitigate them when creating a modern well measurement system are considered.
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Date submitted2021-04-19
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Date accepted2021-10-18
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Date published2021-12-16
Mutual spectral densities calculation of the moments of resistance on the peat milling unit working bodies
- Authors:
- Konstantin V. Fomin
When performing technological operations in the peat industry, various units with milling-type working bodies are used. They differ in design, layout, number and type of cutting elements, operating modes, and may have one or more working bodies. During operation, random forces and moments act on the cutters, which have a dramatically variable nature, which is associated with the periodic interaction of the knives with the peat deposit, its structural heterogeneity, variations in the milling depth, physical and mechanical properties of peat, the rotational speed of the cutter and the movement speed of the machine. In this case, significant dynamic loads arise in the structural elements, which leads to a decrease in their reliability, deterioration of the energy characteristics of the engine operation and technical and economic indicators of use. In the dynamic analysis of drive elements, when using machines with several working bodies, it is necessary to know both spectral and mutual spectral load densities. For their calculation, expressions were obtained that take into account the physical and mechanical properties of peat, the operating modes of the unit and their probabilistic characteristics, as well as the design features of the working body. The expressions are obtained for the case when there are several working bodies with the same diameters and the number of knives in the cutting plane. In this case, the number of planes, width, type of cutting element and type of cutting (locked, semi-locked, etc.) may differ. As an example of using the developed approaches, the calculation of spectral and mutual spectral densities of moments on cutters and loads in the drive elements of the machine for surface-layer milling MTF-14 is presented.
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Date submitted2020-01-09
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Date accepted2020-01-26
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Date published2020-02-25
Mining excavator working equipment load forecasting according to a fuzzy-logistic model
- Authors:
- V. S. Velikanov
Due to the fact that the loads occurring in the working equipment of mining excavators are determined by a large number of random factors that are difficult to represent by analytical formulas, for estimating and predicting loads the models must be introduced using non-standard approaches. In this study, we used the methodology of the theory of fuzzy logic and fuzzy pluralities, which allows to overcome the difficulties associated with the incompleteness and vagueness of the data in assessing and predicting the forces encountered in the working equipment of mining excavators, as well as with the qualitative nature of these data. As a result of computer simulation in the fuzzyTECH environment, data comparable with experimental studies were obtained to determine the level of loading of the main elements of the working equipment of mining excavators. Based on a representative sample, a statistical analysis of the data was performed, as a result of which the equation of linear multiple stress regression in the handle of mining excavators was obtained, which allows to make an accurate forecast of the loading of the working equipment of the excavator.
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Date submitted2019-06-19
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Date accepted2019-09-11
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Date published2020-02-25
Method for estimating the spectrum density of the resistance moment on the working body of a peat milling unit
- Authors:
- K. V. Fomin
The main source of dynamic loads in the drive elements and the design of the peat milling unit is the working body. The forces of external resistance arising in the process of performing a technological operation are sharply variable, random in nature. The article proposes a model of formation of the moment of resistance on the mill when interacting with peat. The case when there are several cutting planes with the same radius at the ends of the cutting elements is considered. When developing the model, it was taken into account that the operating conditions of the knives, determined by the type of cutting (blocked, semi-blocked, etc.), their width and type in each cutting plane can vary. Factors that determine the nature of loading, such as the frequency of interaction of the cutting elements with the fallow and the randomness of the operating conditions of the unit, lead to the presentation of the loads in the form of a sequence of pulses with random parameters. Expressions are obtained for determining the spectral density of the moment of resistance on the mill at the design stage, taking into account its design, operating modes, physico-mechanical properties of peat and their probabilistic characteristics. To illustrate the application of the developed approaches, a technique is presented for determining the spectral density of the moment on the working body of deep milling machines and in their drive elements based on a linear model. An example of calculation is given, and the obtained expressions are verified on the basis of experimental data. The probabilistic characteristics of the loads on the mill serve as initial information for the dynamic analysis of the drive system and the design of the unit, its strength analysis, the selection of optimal parameters and operating modes.
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Date submitted2016-09-06
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Date accepted2016-11-13
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Date published2017-02-22
Justified selection of a seam degassing technology to ensure safety of intensive coal mining
- Authors:
- S. V. Slastunov
- E. P. Yutyaev
The paper contains main aspects of methodological approach to objective analytic assessment of maximum permissible output of the mine faces from the viewpoint of gas factor. Analytic forecast is centered around the assessment of methane inflow into the face area from all possible sources, based on fundamental physical laws, modern tools of mathematical modeling and in-situ tests of main properties and state parameters of the gas-bearing coal formation. Objective and reliable estimation of permissible outputs is a starting point for justified selection of a seam degassing technology, that has to be based on time factor and predicted value of gas recovery from a coal seam to a degassing well. Recommendations have been formulated on the selection of degassing technology for the coal seam «Boldyrevsky» of the Kirov mine, based on the use of cutting-edge technological schemes (hydraulic fracture, carried out from development workings, etc.), successfully implemented on the mentioned site.
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Date submitted2016-09-04
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Date accepted2016-11-14
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Date published2017-02-22
Methodology of reducing rock bump hazard during room and rillar mining of North Ural deep bauxite deposits
- Authors:
- D. V. Sidorov
The article describes practical experience of using room and pillar mining (RAPM) under conditions of deep horizons and dynamic overburden pressure. It was identified that methods of rock pressure control efficient at high horizons do not meet safety requirements when working at existing depths, that is explained by changes in geodynamic processes during mining. With deeper depth, the geodynamic processes become more intensive and number of pillar and roof failures increase. When working at 800 m the breakage of mine structures became massive and unpredictable, which paused a question of development and implementation of tools for compliance assessment of used elements of RAPM and mining, geological, technical and geodynamic conditions of North Ural bauxite deposits and further development of guidelines for safe mining under conditions of deep horizons and dynamic rock pressure. It describes reasons of mine structure failures in workings depending on natural and man-caused factors, determines possible hazards and objects of geomechanic support. It also includes compliance assessment of tools used for calculations of RAPM structures, forecast and measures for rock tectonic bursts at mines of OAO “Sevuralboksitruda” (SUBR). It describes modernization and development of new geomechanic support of RAPM considering natural and technogenic hazards. The article presents results of experimental testing of new parameters of RAPM construction elements of SUBR mines. It has data on industrial implementation of developed regulatory and guideline documents at these mines for identification of valid parameters of RAPM elements at deep depths.
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Date submitted2015-12-28
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Date accepted2016-02-12
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Date published2016-12-23
Impact of the load curve on losses In the power supply network of the company
- Authors:
- Ya. E. Shklyarskii
- S. Pirog
In the recent years, the researchers and experts in the field of energetics often mention in their publications a need to reduce power transmission losses. Among different ways to accomplish this goal the method of the company load leveling stands out due to its simplicity, accessibility and efficiency. The paper proposes a new assessment factor for additional power losses in distribution network. It is known that dispersion of the load curve correlates with the amount of power losses, which is why the proposed factor is put in a position of dependency on the shape of the load curve of the company. It is demonstrated that the proposed factor can help to identify without any strain a need in technical measures for levelling the load curve of the company and to assess efficiency thereof.
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Date submitted2015-12-10
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Date accepted2016-02-18
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Date published2016-12-23
Engineering and technical measures to improve reliability of power supply to construction facilities
- Authors:
- P. S. Orlov
The paper examines an issue of ensuring reliable power supply to construction facilities, proposes ways to reduce losses in distribution networks and improve power supply reliability. The primary focus is on increasing the transmission capability of power distribution networks and improving power supply reliability and safety of single-phase electricity consumers. Engineering and technical proposal belongs to the field of electrical engineering and in particular concerns power supply to single-phase consumers from three-phase networks, including construction industry consumers, and can be used in three-phase three-, four- and five-wives alternating current power distribution networks.
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Date submitted2014-12-07
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Date accepted2015-02-23
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Date published2015-12-25
Bump hazard evaluation of a rock mass area as a result of its seismic acoustic activity registration
- Authors:
- V. V. Nosov
Ore production in deep rock-bump hazardous mines is closely connected with the need to in-crease workers’ safety, which demands heavy costs of taking preventive shockproof actions and applying expensive protection systems against mountain blows. The article considers a resource forecasting technique and a bump hazard evaluation method for a rock mass area, based on a mi-cromechanical model, which registers acoustic emission of heterogeneous materials, and empirical data, obtained as a result of acoustic signals registration with the help of the model, aimed at seis-mic-acoustic activity evaluation at «Taimir» and «Oktyabrsky» rock mass areas, belonging to Norylsk industrial region.
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Date submitted2009-08-02
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Date accepted2009-10-29
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Date published2010-02-01
Forecasting the power consumption of mines on the basis of stochastic time-series models
- Authors:
- A. A. Chernysh
- O. B. Shonin
The paper is devoted to building up time series models to forecast the power consumption of a mine. The results discussed are obtained using various linear filter models and artificial neural network. The wavelet transform of the raw time series is shown to be an efficient technique to increase the forecasting accuracy.
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Date submitted2009-07-27
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Date accepted2009-09-15
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Date published2010-04-22
Geomechanical problems in the forecast of stress-strain state of underground stations of the metro at a great depth
- Authors:
- P. A. Demenkov
- I. E. Dolgiy
- V. I. Ochkurov
Forecast of stress and strain state of deep underground metro stations is considered in this article. A complex approach to study of static work of the metro stations including the in situ testing at different stages of their construction and numerical modeling with finite element method is shown.