Short-Term Forecasting Methodology for Energy Demand in Residential Buildings and the Impact of the COVID-19 Pandemic on Forecasts

The article highlights the impact of information technology on the economic security of regions and threats to economic security of the region that arise from the use of information technology. The system of economic security of the region in the context of development and application of information technologies is considered, which should include the following elements: diagnostics and identification of the existing state of economic security of the region; identification of threats to the economic security of the region from the use of information technology by business entities and from trends and problems in the development of the IT sector in the region; assessment of identified threats; development of effective mechanisms for their prevention; ensuring the increase of the level of economic security of the region with observance of the balance of national, regional and local interests; monitoring the level of economic security of the region. The main tasks of monitoring the economic security of the region in the context of development for the use of information technology are analyzed: monitoring the state of development of the IT sphere of the region and the level of ICT use in the activities of enterprises; timely detection of changes occurring in the IT sphere of the region and in the activities of economic entities of the region in the process of using information technology, and the reasons that caused them; prevention of negative trends leading to the formation and development of tensions in the IT sphere and socio-economic space of the region to prevent threats to its economic security; implementation of short-term forecasting of trends in the most important processes in the IT sphere of the region and in the functioning of economic entities from other sectors of the economy, due to the widespread use of IT in commercial, management and production activities; assessment of the effectiveness of methods, organizational structures and processes of managing the economic security of the region in terms of information development of society and the deep penetration of IT in various areas of management and economic activity at the regional level. The principles of monitoring the economic security of the region in the context of development and application of information technologies are revealed. The requirements to be met by the mechanism of economic security of the region, related to the intensification of informatization processes and the development of the IT sphere, are described. The functions that should be performed by the mechanism of economic security of the region (MESR) related to the intensification of informatization processes and the development of the IT sphere are substantiated. The main groups of computer crimes with the use of information computer technologies are identified, which have an extremely sharp impact on the economic condition of both a particular enterprise and the region as a whole.

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Forecasting Imminent Deaths

10.31219/osf.io/ymw4t ◽

2021 ◽

Author(s):

Silvia Rizzi ◽

James W Vaupel

Keyword(s):

Short Term ◽

Excess Death ◽

Economic Changes ◽

Behavioral Healthcare ◽

Policy Interventions ◽

Short Term Mortality ◽

Short Term Forecasting ◽

Mortality Forecasts ◽

The Impact ◽

Death Count

We introduce a new method for making short-term mortality forecasts of a few months, illustrating it by estimating how many deaths might have happened if some major shock had not occurred. We apply the method to assess excess mortality from March to June 2020 in Denmark and Sweden as a result of the first wave of the coronavirus pandemic, associated policy interventions and behavioral, healthcare, social and economic changes. We chose to compare Denmark and Sweden because reliable data were available and because the two countries are similar but chose different responses to covid-19: Denmark imposed a rather severe lockdown; Sweden did not. We make forecasts by age and sex to predict expected deaths if covid-19 had not struck. Subtracting these forecasts from observed deaths gives the excess death count. Excess deaths were lower in Denmark than Sweden during the first wave of the pandemic. The later/earlier ratio we propose for shortcasting is easy to understand, requires less data than more elaborate approaches, and may be useful in many countries in making both predictions about the future and the past to study the impact on mortality of coronavirus and other epidemics. In the application to Denmark and Sweden, prediction intervals are narrower and bias is less than when forecasts are based on averages of the last five years, as is often done. More generally, later/earlier ratios may prove useful in short-term forecasting of illnesses and births as well as economic and other activity that varies seasonally or periodically.

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Introduced flow variability and its propagation downstream of hydropower stations in Sweden

10.5194/egusphere-egu21-14166 ◽

2021 ◽

Author(s):

Maria Elenius ◽

Göran Lindström

Keyword(s):

Time Series ◽

Energy Demand ◽

Ecological Impact ◽

Ecological Impacts ◽

Low Flow ◽

Seasonal Forecasts ◽

Short Term ◽

Swedish Model ◽

The Impact ◽

Hydropower Stations

Hydropower provides a low-carbon solution to a large portion of Sweden&#8217;s energy demand, which is increasingly important in order to combat climate change. However, associated flow regulations introduce variability of the flow on the daily, weekly and seasonal time scales, driven by the varying energy demand. Additional variability is introduced when compensating for the shifting wind energy production. The Water framework directive requires all EU member states to evaluate the ecological impact from anthropogenic activities, such as hydropower. Ecological impacts must also be assessed when all hydropower permissions in Sweden are renewed over the coming 20 years. Because different species are sensitive to different longevity of high- and low-flow periods, it is important to understand the introduced variability of flow in terms of its dominant periods, and how quickly these perturbations are attenuated downstream of regulations.In this work, time-series of flow from hydrological simulations with HYPE are analyzed with the Fourier transform to examine the amplitudes of perturbations of different periods, and their decay downstream of hydropower stations. HYPE is a catchment-based model that simulates rainfall-runoff as well as water quality processes. The Swedish model application has been developed over the past decade and covers all of Sweden. Seasonal regulations are modeled with calibrated input parameters, whereas short-term regulations are introduced with station updates from observations that are available at or close to the majority of hydropower regulations. Very high accuracy has been proven between the updated sub-catchments. This, together with a verified model for natural flow, gives us a unique opportunity to study the impact of hydropower on dominant periods and their decay over the entire country, as well as the mechanisms that govern this decay.In many sub-catchments, especially in large regulated rivers in northern Sweden, Fourier analysis of daily time series results in dominance of the 7-day period. The exponential decay rate of this and other modes is presented for all Sweden and analyzed in terms of land use and other parameters. Short periods decay faster than long ones. Periods of one month or longer are amplified in the downstream direction in most of Sweden.Apart from aid in ecological assessments, our analysis can be used to introduce short-term regulations in hydrological simulators, for either deterministic forecasts (the 7-day mode typically has a minimum value on Sundays) or for stochastic seasonal forecasts where it will impact indicators such as the number of days below or above a threshold.

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A Hybrid Short-Term Forecasting Model of Passenger Flow on High-Speed Rail considering the Impact of Train Service Frequency

Mathematical Problems in Engineering ◽

10.1155/2017/1828102 ◽

2017 ◽

Vol 2017 ◽

pp. 1-9 ◽

Cited By ~ 5

Author(s):

Qingying Lai ◽

Jun Liu ◽

Yongji Luo ◽

Minshu Ma

Keyword(s):

Hybrid Model ◽

Traffic Management ◽

High Speed ◽

Short Term ◽

High Speed Rail ◽

Passenger Flow ◽

Proposed Model ◽

Service Frequency ◽

Short Term Forecasting ◽

The Impact

Short-term forecasting of OD (origin to destination) passenger flow on high-speed rail (HSR) is one of the critical tasks in rail traffic management. This paper proposes a hybrid model to explore the impact of the train service frequency (TSF) of the HSR on the passenger flow. The model is composed of two parts. One is the Holt-Winters model, which takes advantage of time series characteristics of passenger flow. The other part considers the changes of TSF for the OD in different time during a day. The two models are integrated by the minimum absolute value method to generate the final hybrid model. The operational data of Beijing-Shanghai high-speed railway from 2012 to 2016 are used to verify the effectiveness of the model. In addition to the forecasting ability, with a definite formation, the proposed model can be further used to forecast the effects of the TSF.

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Comparing the impact of presence patterns on energy demand in residential buildings using measured data and simulation models

Building Simulation ◽

10.1007/s12273-019-0539-z ◽

2019 ◽

Vol 12 (6) ◽

pp. 985-998 ◽

Cited By ~ 5

Author(s):

Elena Cuerda ◽

Olivia Guerra-Santin ◽

J. J. Sendra ◽

Fco. Javier Neila González

Keyword(s):

Energy Demand ◽

Residential Buildings ◽

Simulation Models ◽

Measured Data ◽

The Impact

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Enhancement of a Short-Term Forecasting Method Based on Clustering and kNN: Application to an Industrial Facility Powered by a Cogenerator

Energies ◽

10.3390/en12234407 ◽

2019 ◽

Vol 12 (23) ◽

pp. 4407 ◽

Cited By ~ 2

Author(s):

Giulio Vialetto ◽

Marco Noro

Keyword(s):

Data Storage ◽

Energy Demand ◽

The Internet ◽

Model Parameters ◽

Industrial Facility ◽

Short Term ◽

K Nearest Neighbors ◽

Industrial Facilities ◽

Using Data ◽

Short Term Forecasting

In recent years, collecting data is becoming easier and cheaper thanks to many improvements in information technology (IT). The connection of sensors to the internet is becoming cheaper and easier (for example, the internet of things, IOT), the cost of data storage and data processing is decreasing, meanwhile artificial intelligence and machine learning methods are under development and/or being introduced to create values using data. In this paper, a clustering approach for the short-term forecasting of energy demand in industrial facilities is presented. A model based on clustering and k-nearest neighbors (kNN) is proposed to analyze and forecast data, and the novelties on model parameters definition to improve its accuracy are presented. The model is then applied to an industrial facility (wood industry) with contemporaneous demand of electricity and heat. An analysis of the parameters and the results of the model is performed, showing a forecast of electricity demand with an error of 3%.

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Energy demand of occupant’s spatial modification in residential buildings. Case study of Médéa, Algeria

Selected Scientific Papers - Journal of Civil Engineering ◽

10.1515/sspjce-2018-0002 ◽

2018 ◽

Vol 13 (s1) ◽

pp. 15-28

Author(s):

Boukarta Soufiane ◽

Berezowska-Azzag Ewa

Keyword(s):

Energy Demand ◽

Residential Buildings ◽

Negative Energy ◽

Transformation Process ◽

Energy Field ◽

End Use ◽

The Impact ◽

Social Uses ◽

Insulation Quality

AbstractHousing is rated as one of the most commonly consuming energy field in terms of energy end-use with 41%. Regarding the transformations dealt by dwellers for functional and social uses. The aim of this paper is: Firstly, to highlight the non-controlled transformation process made by the occupant in Algeria; Secondly, to explore the impact of the energy load of such spatial transformations. The question is approached in two tracks, (i) Through Ecotect software’s simulations (ii) and measurements through a collection of energy end-use data. Basically, the energy demand is bound to dwelling’s spatial and socioeconomic criteria. Three cases studied showed consequently 2 positive and 1 negative energy load, in which two explanations may be given: Insulation quality that occupant is lacking facilities to improve may be stated as a physical explanation, as well as for the socio economic one, the density per dwelling plays a major role, but it is the income which explains within the two approaches more than 87% of the energy end use.

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Short-term forecasts of expected deaths

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2025324118 ◽

2021 ◽

Vol 118 (15) ◽

pp. e2025324118

Author(s):

Silvia Rizzi ◽

James W. Vaupel

Keyword(s):

Short Term ◽

Excess Death ◽

Economic Changes ◽

Behavioral Healthcare ◽

Policy Interventions ◽

Short Term Mortality ◽

Short Term Forecasting ◽

Mortality Forecasts ◽

The Impact ◽

Death Count

We introduce a method for making short-term mortality forecasts of a few months, illustrating it by estimating how many deaths might have happened if some major shock had not occurred. We apply the method to assess excess mortality from March to June 2020 in Denmark and Sweden as a result of the first wave of the coronavirus pandemic; associated policy interventions; and behavioral, healthcare, social, and economic changes. We chose to compare Denmark and Sweden because reliable data were available and because the two countries are similar but chose different responses to COVID-19: Denmark imposed a rather severe lockdown; Sweden did not. We make forecasts by age and sex to predict expected deaths if COVID-19 had not struck. Subtracting these forecasts from observed deaths gives the excess death count. Excess deaths were lower in Denmark than Sweden during the first wave of the pandemic. The later/earlier ratio we propose for shortcasting is easy to understand, requires less data than more elaborate approaches, and may be useful in many countries in making both predictions about the future and the past to study the impact on mortality of coronavirus and other epidemics. In the application to Denmark and Sweden, prediction intervals are narrower and bias is less than when forecasts are based on averages of the last 5 y, as is often done. More generally, later/earlier ratios may prove useful in short-term forecasting of illnesses and births as well as economic and other activity that varies seasonally or periodically.

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Impact of Shape Factor on Energy Demand, CO2 Emissions and Energy Cost of Residential Buildings in Cold Oceanic Climates: Case Study of South Chile

Sustainability ◽

10.3390/su13179491 ◽

2021 ◽

Vol 13 (17) ◽

pp. 9491

Author(s):

Manuel Carpio ◽

David Carrasco

Keyword(s):

Co2 Emissions ◽

Shape Factor ◽

Energy Demand ◽

Architectural Design ◽

Residential Buildings ◽

Thermal Transmittance ◽

Energy Demands ◽

Oceanic Climate ◽

The Impact

The increase in energy consumption that occurs in the residential sector implies a higher consumption of natural resources and, therefore, an increase in pollution and a degradation of the ecosystem. An optimal use of materials in the thermal envelope, together with efficient measures in the passive architectural design process, translate into lower energy demands in residential buildings. The objective of this study is to analyse and compare, through simulating different models, the impact of the shape factor on energy demand and CO2 emissions depending on the type of construction solution used in the envelope in a cold oceanic climate in South Chile. Five models with different geometries were considered based on their relationship between exposed surface and volume. Additionally, three construction solutions were chosen so that their thermal transmittance gradually complied with the values required by thermal regulations according to the climatic zone considered. Other parameters were equally established for all simulations so that their comparison was objective. Ninety case studies were obtained. Research has shown that an appropriate design, considering a shape factor suitable below 0.767 for the type of cold oceanic climate, implies a decrease in energy demand, which increased when considering architectural designs in the envelope with high values of thermal resistance.

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CORRELATION-REGRESSION ANALYSIS OF THE COMPETITIVENESS OF ENTERPRISE PRODUCTS

Young Scientist ◽

10.32839/2304-5809/2020-10-86-50 ◽

2020 ◽

Vol 10 (86) ◽

Author(s):

Volodymyr Ulanchuk ◽

◽

Olena Zharun ◽

Serhiy Sokolyuk ◽

◽

...

Keyword(s):

Mathematical Model ◽

Regression Analysis ◽

Correlation Equation ◽

Regression Equation ◽

Short Term ◽

Flexible Tool ◽

Proposed Model ◽

Using Data ◽

Short Term Forecasting ◽

The Impact

The economic purpose of correlation-regression analysis is to determine the possible options for product competitiveness management, as well as an assessment of possible ways to achieve the desired result. The developed model can be used to improve planning and increase the level of product competitiveness. The forecast of results, though for the short term, gives the chance to learn about the prospects of obtaining the appropriate level of competitiveness of products in accordance with the degree of application of the impact on it. The forecast is dynamic and adapts to changes based on the latest data. The proposed model can be integrated into the existing decision support system to increase the competitiveness of products. In addition, correlation-regression analysis makes it possible to estimate the current situation using a regression equation. The mathematical reflection of the study of product competitiveness is the economic-mathematical model, which determines its functioning and assessment of changes in its effectiveness in the event of possible changes in the characteristics of economic activity. The parameters of economic models are estimated using the methods of mathematical statistics according to real statistical information. The task of correlation-regression analysis is to construct and analysis of the economic-mathematical model of the regression equation (correlation equation, which reflects the dependence of the resultant feature on several factor features and gives an estimate of the degree of connection density. Using data on the magnitude and direction of action of the analyzed factors, you can get the data that can be obtained to assess the relevant impact on the current level of product competitiveness. That is, such an analysis is a powerful and flexible tool for studying the relationships between product competitiveness indicators. The use of this method makes it possible to better understanding of the level of influence of factors on the competitiveness of products, and, accordingly, learn to manage the processes that take place, as well as more accurately predict their further interaction. These studies are important for the formation and implementation of management decisions to increase the competitiveness of products, because it narrows the choice of indicators with the greatest impact on its level. The ability to determine short-term forecasting of such impacts makes it possible to determine regional perspectives under the conditions of implemented measures.

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