Consumption Planning Research Articles

Improving an electric power planning system in the commuter rail passenger complex

The transport industry is an energy intensive one, so power saving measures in transport in general, and railway transport in particular, deserve greater attention. It should be noted that the transport complex has developed a programme of measures aimed at power saving in the industry. Nevertheless, the issue of improving the electric power planning system for the commuter rail complex remains relevant. It is worth noting that the results of theoretical research, supplemented by the results of field-based scientific research, demonstrate the lack of a perfect approach to electric power consumption planning at present. Identification of bottlenecks in the existing electric power planning system is possible with application of general scientific and special methods and techniques, as follows: dialectical, logical, analytical, systemic and functional, comparative, economic and mathematical, a method of scientific abstraction, classification, grouping and comparison, analysis and synthesis, induction and deduction, a graphical method, a method of statistical analysis, together with private methods of economic sciences, providing reliability and objectivity of the scientific conclusions and results obtained. In this article the issue of transition from the existing electric power consumption planning system in the multiple unit rolling stock to the author’s planning system is considered; the evidential basis is presented by an example of the Regional Multiple Unit Rolling Stock Directorate. The proposed planning system provides an opportunity to calculate the standard values of electric power consumption in the multiple unit rolling stock promptly. The authors assert that the advantage of the proposed planning system is its calculation accuracy of one kilowatt consumed, as well as its transparency, resulting not only in the economic component of the Regional Directorate of Multiple Unit Facilities, but also in the passenger service quality. A compliance with the standards presented in this planning system implies a comfortable microclimate in commuter coaches.

Steroid use among male sports students in Germany

A large number of studies have already dealt with steroid consumption in leisure and popular sports. The aim of this explorative study was to give an insight into the anabolic steroid use among male sports students in Germany. Semi-structured face-to-face interviews with n = 5 participants, all steroid-users and fellow students recruited by the third author, were conducted. Through the interviews we explored data on individual perceptions of active users with academic background and access to expertise. The interview guide is based on international findings concerning doping/steroid abuse within the framework of social differentiation theory (Alexander & Colomy, 1990; Stichweh, 2012). The study's results indicate that it is primarily the health factor that influences the planning, execution and control of steroid consumption among male sports students. Physical appearance forms a constant reason for substitution, besides the subjectively perceived pressure of physical performance inside and outside high-performance sports. However, explorative data reveal that universities’ performance requirements do not lead to steroid use.

Анализ влияния эффективности использования материалдьных запасов на величину материальных затрат

The most important condition for maintaining the competitiveness of an enterprise in any industry and field of activity is the ability to use the assets or resources at its disposal as efficiently as possible. Material and production stocks occupy a significant share in the structure of assets. Material stocks form the material (material) basis of the product for the production of which they are used. For manufacturing enterprises, it is important to increase the efficiency of the use of raw materials and basic materials, since these costs make up a significant part of the structure of the cost of production. A slight reduction in material costs during the production of each unit of production allows you to get a significant effect. The state and efficiency of the use of material reserves, as the most significant part of working capital, is one of the main conditions for the successful operation of a manufacturing enterprise.The main indicators that characterize the efficiency of production in terms of the use of material resources are material consumption and material output. Reducing the material consumption of products characterizes the economical use of all types of resources and ensures production growth and cost reduction. Economic analysis is an integral part of the information base on the state and use of material reserves, which deepens the search for reserves to increase production efficiency. The article deals with the main aspects of inventory analysis and its methodological support. On the basis of special methods and techniques (factor analysis, coefficient method), the results of the analysis of the efficiency of the use of material resources on the basis of general and particular indicators of material yield and material intensity are presented. The main directions of improving the planning of material consumption of production and control of material costs are considered on the basis of the introduction of progressive norms for the expenditure of material resources; improving the efficiency of the use of production waste; improving analytical work at the enterprise in order to assess the timeliness of providing the enterprise with material reserves and the efficiency of their use (factor analysis of material output).

Particulate matter concentration and health risk assessment for a residential building during COVID-19 pandemic in Abha, Saudi Arabia.

Building and its environment are in focus owing to health impact attributed to indoor air quality. This study was carried out to assess indoor air quality in terms of particulate matter (PM) and carbon dioxide in a residential building, during COVD-19 pandemic lockdown from March 25 to April 23, 2020, Abha, Saudi Arabia. The PM concentration range for kitchen, bedroom, and hall were 40,000–81000 μg/m3 (PM0.3), 15,000–26000 μg/m3 (PM0.5), 4000–6000 μg/m3 (PM1), 1100–1500 μg/m3 (PM2.5), 160–247 μg/m3 (PM5), and 60–95 μg/m3 (PM10). The results of this study suggest that bedroom needs to be ventilated as CO2 concentration was reaching 700 ppm during sleep hours. PM concentration was exceeding 300 μg/m3 (unhealthy) for all particle sizes of PM0.3, PM0.5, PM1, and PM2.5 except for PM10 which was also above safe limits (0–50 μg/m3). Also, with influential habit (aromatic smoke), these concentrations increased 2–28 times for PM. The hazard quotient value greater than 1 revealed potential health risk to the inhabitants. Hence, future studies are needed for developing indoor air quality guidelines for residential buildings in Saudi Arabia and better planning and management of energy consumption.

Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting

Many real-world applications require the prediction of long sequence time-series, such as electricity consumption planning. Long sequence time-series forecasting (LSTF) demands a high prediction capacity of the model, which is the ability to capture precise long-range dependency coupling between output and input efficiently. Recent studies have shown the potential of Transformer to increase the prediction capacity. However, there are several severe issues with Transformer that prevent it from being directly applicable to LSTF, including quadratic time complexity, high memory usage, and inherent limitation of the encoder-decoder architecture. To address these issues, we design an efficient transformer-based model for LSTF, named Informer, with three distinctive characteristics: (i) a ProbSparse self-attention mechanism, which achieves O(L log L) in time complexity and memory usage, and has comparable performance on sequences' dependency alignment. (ii) the self-attention distilling highlights dominating attention by halving cascading layer input, and efficiently handles extreme long input sequences. (iii) the generative style decoder, while conceptually simple, predicts the long time-series sequences at one forward operation rather than a step-by-step way, which drastically improves the inference speed of long-sequence predictions. Extensive experiments on four large-scale datasets demonstrate that Informer significantly outperforms existing methods and provides a new solution to the LSTF problem.

Short-Term Electricity Consumption Forecasting Based on the EMD-Fbprophet-LSTM Method

Short-term electricity consumption data reflects the operating efficiency of grid companies, and accurate forecasting of electricity consumption helps to achieve refined electricity consumption planning and improve transmission and distribution transportation efficiency. In view of the fact that the power consumption data is nonstationary, nonlinear, and greatly influenced by the season, holidays, and other factors, this paper adopts a time-series prediction model based on the EMD-Fbprophet-LSTM method to make short-term power consumption prediction for an enterprise's daily power consumption data. The EMD model was used to decompose the time series into a multisong intrinsic mode function (IMF) and a residual component, and then the Fbprophet method was used to predict the IMF component. The LSTM model is used to predict the short-term electricity consumption, and finally the prediction value of the combined model is measured based on the weights of the single Fbprophet and LSTM models. Compared with the single time-series prediction model, the time-series prediction model based on the EMD-Fbprophet-LSTM method has higher prediction accuracy and can effectively improve the accuracy of short-term regional electricity consumption prediction.

Which renewable energy consumption is more efficient by fuzzy EDAS method based on PESTLE dimensions?

The facilities that energy delivers to social life and economic activities render it indispensable. Hence, it is equally critical that the energy cycle must have a sustainable structure. Therefore, it is an indisputable fact that developing and performing correct and consistent energy policies is vitally necessary. Energy consumption planning includes a continuous process to reassess existing and potential alternative energy approaches and strategies. The public and private decision-makers in charge of planning and managing energy consumption policies must adapt their strategies to novel and superior alternative resources according to sustainability and efficiency criteria. In this paper, the fuzzy EDAS method is used to address the best renewable energy consumption by taking political, economic, social, technological, legal, and environmental (PESTLE) dimensions into account. The analysis of the paper indicates the most efficient renewable energy consumption is sourced by geothermal, solar, wind, hydroelectricity, and biomass, respectively. By further investigation, it is concluded that the most optimum renewable energy consumption alternatives based on PESTLE dimensions are geothermal and solar energies.

Hybrid and Ensemble Methods of Two Days Ahead Forecasts of Electric Energy Production in a Small Wind Turbine

The ability to forecast electricity generation for a small wind turbine is important both on a larger scale where there are many such turbines (because it creates problems for networks managed by distribution system operators) and for prosumers to allow current energy consumption planning. It is also important for owners of small energy systems in order to optimize the use of various energy sources and facilitate energy storage. The research presented here addresses an original, rarely predicted 48 h forecasting horizon for small wind turbines. This topic has been rather underrepresented in research, especially in comparison with forecasts for large wind farms. Wind speed forecasts with a 48 h horizon are also rarely used as input data. We have analyzed the available data to identify potentially useful explanatory variables for forecasting models. Eight sets with increasing data amounts were created to analyze the influence of the types and amounts of data on forecast quality. Hybrid, ensemble and single methods are used for predictions, including machine learning (ML) solutions like long short-term memory (LSTM), multi-layer perceptron (MLP), support vector regression (SVR) and K-nearest neighbours regression (KNNR). Original hybrid methods, developed for research of specific implementations and ensemble methods based on hybrid methods’ decreased errors of energy generation forecasts for small wind turbines in comparison with single methods. The “artificial neural network (ANN) type MLP as an integrator of ensemble based on hybrid methods” ensemble forecasting method incorporates an original combination of predictors. Predictions by this method have the lowest mean absolute error (MAE). In addition, this paper presents an original ensemble forecasting method, called “averaging ensemble based on hybrid methods without extreme forecasts”. Predictions by this method have the lowest root mean square error (RMSE) error among all tested methods. LSTM, a deep neural network, is the best single method, MLP is the second best one, while SVR, KNNR and, especially, linear regression (LR) perform less well. We prove that lagged values of forecasted time series slightly increase the accuracy of predictions. The same applies to seasonal and daily variability markers. Our studies have also demonstrated that using the full set of available input data and the best proposed hybrid and ensemble methods yield the lowest error. The proposed hybrid and ensemble methods are also applicable to other short-time generation forecasting in renewable energy sources (RES), e.g., in photovoltaic (PV) systems or hydropower.

Perfection of metal consumption planning at hotextruded pipes production

Production of pipes by the method of hot extrusion is characterized by high level of resource capacity and considerable cost of original raw materials. In this connection wastes and metal loss have a considerable effect on the products cost. This factor stipulates the importance of objective and scientifically based planning of metal consumption. Some peculiarities effecting on the level of wastes and metal loss during pipe production at hot extrusion facilities considered. Methodical approaches to planning and assessing metal consumption at the manufacturing of hot-extruded pipes based on the computational and analytical method are outlined. The advantage of using the computational and analytical method of metal consumption rationing was shown. An explanation of the features of the implementation of the computational and analytical method used for modern rationing using information processing systems based on electronic computers is given. The basic materials of the instruction on the rationing of the consumption of ferrous metals at the production of steel pipes, used for a single-stage production scheme, are presented, noting its advantages and disadvantages. The historical aspects of research in the field of rationing of metal consumption at the TMK Group plants considered. A detailed list of literature sources is provided, including corporate materials of TMK Group, used to create programs for metal consumption rationing at the production of hot-extruded pipes at PED-2 of VTZ. The elements of the developed mathematical model used to create a software product are given. The complex of functional capabilities of the program is described, which are necessary for the operative automated calculation of particular consumption coefficients, consumption rates and structure of metal wastes by technological stages. A conclusion is made about the effect of the implementation of the obtained model, expressed in the organization of the process of technical rationing that meets the current requirements. This process of technical rationing makes it possible to establish scientifically and technologically based individual rates of metal consumption, reflecting the objective state of the processes of production of hot-extruded pipes.

Program energetske efikasnosti HIP-Petrohemija Pančevo

Energy efficiency program of HIP-Petrohemija a.d. Pancevo 2020-2022 is a planning document that expresses the planning of energy consumption and improvement of energy efficiency of the system in the next three years, as compliance with the Law on Efficient Use of Energy (Official Gazette of RS, No. 25/2013) and in accordance with the goals of the Energy Development Strategy of the Republic of Serbia. In the period from 2013-2019, investment programs were implemented in HIPP and planned overhauls of all plants were realized, whereby several planned business projects were realized with the aim of raising energy efficiency. About 42 million euros were invested in capital projects and investment maintenance, while about 35 million euros were spent on current maintenance and plant overhaul, all financed from own sources. The set of measures and actions for risk management for the survival and sustainability of petrochemical plants are investments in strategic modernization projects and projects to increase production capacity with the installation of energy efficient equipment. The energy efficiency program references the implemented energy improvements in the previous period and the planned business improvements in the following period, all with the aim of continuously improving the energy efficiency of the HIP-Petrohemija plant.

МЕТОДИКА РАСЧЕТА ВОДОПОЛЬЗОВАНИЯ ДЛЯ ПРЕДПРИЯТИЙ ПО ПРОИЗВОДСТВУ МОЛОЧНЫХ ПРОДУКТОВ С УЧЕТОМ ПЕРЕРАБАТЫВАЕМОГО СЫРЬЯ И ПРОИЗВОДИМОЙ ПРОДУКЦИИ

Regulation of water use at industrial enterprises, especially at water-intensive enterprises, in a changing climate is an important economic and environmental task. One of the ways of sustainable water use at enterprises is the constant planning of water consumption and wastewater disposal in relation to the volumes and types of products produced. From a scientific point of view, at water-intensive enterprises, the most reasonable approach to optimizing water use is the development of individual technological standards for water use (water consumption and disposal). Dairy enterprises are quite water- intensive, the water use of which depends on a number of factors: assortment of raw materials for the production of products and types of products; diversification of production processes; the formation and processing of by-products, which often leads to an increase in the volume of wastewater formation in relation to the volume of water consumption; technologies for sanitizing equipment. Taking into account the specifics of production processes, a Methodology for calculating water use for enterprises for the production of dairy products, taking into account the processed raw materials and manufactured products, has been developed. The Methodology substantiates the need to change the terminology in terms of water use rationing, developed criteria for choosing two approaches to the development of individual technological standards for water use, detailed articles of water consumption and water disposal, and clarified certain parameters for their calculation. Approbation of the Methodology showed that the proposed approaches and individual parameters for calculating water use items allow the enterprise to more accurately predict the volumes of water consumption and wastewater disposal when planning production activities, which is especially important for water-intensive industries in conditions of limited available water resources.

Обоснование системы электроснабжения жизнеобеспечения спасательных формирований и пострадавшего населения при полевом размещении

Introduction. Increasing of number, scale and duration of the consequences of emergency situations associated with the violation of the conditions of normal living of people requires the creation of temporary field accommodation points for the affected population and rescue units. At the same time, electric power supply in field temporary accommodation facilities plays a crucial role in the complex of tasks and measures aimed at providing life to the injured population and rescue units. At the same time, there are no mobile autonomous sources of electric energy for providing life support to people in the field in the organizational and staff structure of rescue units, and the existing sources of electric energy in the complexes of equipment used in areas of emergency situations cannot be used for these purposes. Therefore, it is necessary to develop a scientific and methodological approach to determine necessary and sufficient number of sources of electric energy for the power supply of the life support of the injured population and rescue units when they are placed in field temporary accommodation points. The purpose of the study. Electric power supply of field temporary accommodation points for the injured population and rescue units, ensuring the required reliability of electric power supply, maximizing its efficiency in the conditions of possible resource constraints and minimizing the influence of the uncertainty factor in the planning of electricity consumption. Research methods. The main provisions of the calculation of electrical loads, system theory, set theory, probability theory and the apparatus of mathematical statistics. The results of the study. A methodology has been developed that allows to justify the power of electric energy sources for the power supply of field temporary accommodation points for the injured population and rescue units, rational options for the power supply system, the nomenclature and number of electric energy sources for the life support of people in the field; to calculate the electric network; to evaluate the operation of the power supply system, based on the probability of failure-free operation of the source of electric energy; to justify the composition of engineering means to ensure the creation of the power supply system. Conclusion. The scientific and methodological approach for determining the composition of electric energy sources for the power supply of life support for the injured population and rescue units when they are placed in field temporary accommodation points is justified, which also allows to resolve the contradiction between the need to organize the power supply of life support for people in temporary accommodation points and the lack of a reasonable structure of electric energy sources for these purposes. Keywords: temporary accommodation point, injured population, rescue formation, consumers, electric power supply, organization

Health behaviors and health services accessibility factors associated with diabetes: a propensity score matching analysis

ABSTRACT Background: Despite the increasing burden of diabetes in Turkey, there is a lack of information regarding behaviors and accessibility factors associated with diabetes. This study aims to explore diabetes prevalence and to identify the associated health behaviors and accessibility factors. Research design and methods: Data was gathered from TurkStat-Health Survey for the year 2014. 1996 individuals who had reported diabetes were matched to similar non-diabetes participants in terms of socio-demographic characteristics and comorbidities by using 1:1 nearest matching based on estimated propensity scores. Results: The weighted point prevalence of diabetes among adults was 8.98%. Compared with smokers, non-smokers were less likely to develop diabetes (OR:0.96; 95% CI:0.95–0.97). Individuals engaging in regular physical activity were less likely to have experienced diabetes than individuals not engaging in any physical activity (OR:0.51; 95% CI:0.41–0.52). Conclusions: Improving the health behaviors of individuals and promoting a culture of exercise, healthy food consumption and better planning of preventive services are necessary strategies to fight against diabetes in Turkey. Collaboration between health professionals will result in effective clinical decision making and the development of diabetes self-management programs.

Development of an algorithm for determining the optimal start time of oil wells to reduce the peak load

The subject of this work is the development of an algorithm for determining the start time of wells in the automatic re-activation mode to save power during peak hours. This measure is relevant for the consumer and for the energy-supplying organizations, because the redistribution of load on peak hours or night zones will provide the most economically balanced operation of the enterprise, and will allow the most efficient use of sources of electrical energy supply organization. The algorithm development will provide operational control and management of the operating mode of the considered equipment in automatic mode. Besides, this will reduce the influence of the human factor on the operation of these consumers and minimize deviations in the hourly planning of electricity consumption, as well as reduce the cost of paying for consumed power. The short-term prospect of implementing this development will ensure optimal power consumption of the periodic well stock during peak load hours, and, consequently, will provide savings in the material resources of the enterprise.

Wine-related lifestyle segmentation in the context of urban Indian consumers

PurposeThe purpose of this study is to understand consumers in the emerging wine market of India to ensure the best services. To this end, factors were identified to describe Indian wine consumer behavior and further segments for consumers were created based on the factors identified.Design/methodology/approachThe research design is descriptive in nature and based on primary data. Data was collected by a structured questionnaire from 232 respondents in five major cities of India (Mumbai, Delhi NCR, Bangalore, Pune and Hyderabad). The scale was mainly adopted from wine-related lifestyle approaches.FindingsThe principal component factor analysis resulted in six factors, namely, drinking ritual, consumption reason (social), consumption reason (mood, enjoyment and relaxation), consumption practice, consumption planning and quality. Cluster analysis resulted in a three-cluster solution. These clusters were named as cautious social drinker, loner regular drinker and highly engaged drinker based on the attributes possessed.Originality/valueThe segmentation of urban Indian wine consumers will be helpful for marketers to identity and describe the differences in attributes and behaviors, to create customized promotions to match the needs.

Automatic Stockpile Extraction and Measurement Using 3D Point Cloud and Multi-Scale Directional Curvature

With the rapid increase of power supply demand, a large amount of stockpiles of coal have been formed during the process of coal excavation and transportation between the mines, ports, power plants and etc. Quantitative parameters, especially the volume of stockpile are important for the planning of coal production and consumption. Although laser scanning can collect the dense 3D coordinates of the stockpile surface for its quantification, stockpiles of coal have irregular shape, size, height, and base conditions, and may be overlapped with each other, which makes it hard to measure the different stockpiles automatically and accurately. This paper proposes an algorithm to extract and measure the stockpiles from the 3D point cloud data using the multi-scale directional curvature. Firstly, the second-order directional curvature analysis along multiple directions and at multiple scales is proposed to extract the distinctive ridge of crest in the point cloud of stockpiles. Then, starting with the crest points, a competitive growing strategy is proposed to accurately locate the points of slope in the stockpile. Finally, the stockpile’s volume is calculated by reconstructing the complete points of crest and slope with many meshes and triangular prisms through the subsurface fitting and surface reconstruction. Experiments on both the synthetic and real point cloud of stockpiles demonstrate that the proposed algorithm can extract the stockpiles with the average accuracy over 93.5% and measure the volume of stockpiles with the average precision over 93.7%. It is promising for automatically measuring the stockpiles like sand, soybean, etc., and facilitating the scientific storage and transportation management, as well as the maintenance of safety inventory during operation.

МОДЕЛЬ ПЛАНУВАННЯ ЕНЕРГОСПОЖИВАННЯ МЕТАЛУРГІЙНОГО ПІДПРИЄМСТВА

Розроблено багаторівневу модель енергоспоживання металургійного підприємства, яка дозволяє оцінити ефективність відібраних до реалізації енергозберігаючих проектів, об'єктивно оцінити частку кожного енергоресурсу в загальному потоці, визначити енергоємність окремого виробництва, цеху, всього підприємства, скорегувати стратегічний напрям в управлінні енергоресурсами. За допомогою моделі можливе вирішення цілого ряду завдань, серед яких оцінка раціональності та ефективності існуючої на підприємстві структури енергоспоживання, прогнозування очікуваних рівнів енерговитрат при зміні технології, сортаменту і якості продукції та порівняння різних технологій і обладнання з точки зору енергоефективності, оптимальне управління потоками енергоносіїв з урахуванням зміни умов виробництва

Approximate CPU Design for IoT End-Devices with Learning Capabilities

With the rise of Internet of Things (IoT), low-cost resource-constrained devices have to be more capable than traditional embedded systems, which operate on stringent power budgets. In order to add new capabilities such as learning, the power consumption planning has to be revised. Approximate computing is a promising paradigm for reducing power consumption at the expense of inaccuracy introduced to the computations. In this paper, we set forth approximate computing features of a processor that will exist in the next generation low-cost resource-constrained learning IoT devices. Based on these features, we design an approximate IoT processor which benefits from RISC-V ISA. Targeting machine learning applications such as classification and clustering, we have demonstrated that our processor reinforced with approximate operations can save power up to 23% for ASIC implementation while at least 90% top-1 accuracy is achieved on the trained models and test data set.

Optimal fuel consumption planning and energy management strategy for a hybrid energy system with pumped storage

Optimal fuel consumption planning and energy management strategy for a hybrid energy system with pumped storage

Optimal fuel consumption planning and energy management strategy for a hybrid energy system with pumped storage

Energy management system is very critical for solving the energy problem in remote areas, especially autonomous systems that uses diesel generators. The fuel cost increases due to transport over long distances makes it unsustainable system. for that an optimal sizing of the hybrid microgrid energy system (HMGES) with an energy management control (EMC) strategy was proposed in this work for an isolated site in southern Algeria, which consisting of photovoltaic (PV) source, diesel generator (DG), with a power hydroelectric storage (PHS) system in order to increase the reliability. The HMGES based on renewable energy is profitable for supplying the domestics and agricultural demand. This work evaluates three different standalone systems that used to guarantee the supply of energy for the isolated Saharan zone. The HMGES with EMC system not only decrease the harmful CO2 emission due to the less consumption of fuel, but also reduce the system cost comparison with the (DG and PV/DG) standalone systems, which are the objectives function of this study.