Big Data and Energy Security: Impacts on Private Companies, National Economies and Societies

The importance of energy security for the successful functioning of private companies, national economies, and the overall society cannot be underestimated. Energy is a critical infrastructure for any modern society, and its reliable functioning is essential for all economic sectors and for the well-being of everybody. Uncertainty in terms of the availability of information, namely reliable data to make predictions and to plan for investment as well as for other actions of stakeholders in the energy markets is one of the factors with the highest influence on energy security. This uncertainty can be connected with many factors, such as the availability of reliable data or actions of stakeholders themselves. For example, the recent outbreak of the COVID-19 pandemic revealed negative impacts of uncertainty on decision-making processes and markets. At the time point when the market participants started to receive real-time information about the situation, the energy markets began to ease. This is one scenario where Big Data can be used to amplify information to various stakeholders to prevent panic and to ensure market stability and security of supply. Considering the novelty of this topic, our methodology is based on the meta-analysis of existing studies in the area of impacts of energy security on private companies, the national economy, and society. The results show that, in a fast-paced digital world characterized by technological advances, the use of Big Data technology provides a unique niche point to close this gap in information disparity by levering the use of unconventional data sources to integrate technologies, stakeholders, and markets to promote energy security and market stability. The potential of Big Data technology is yet to be fully utilized. Big Data can handle large data sets characterized by volume, variety, velocity, value, and complexity. Our conclusion is that the challenge for energy markets is to leverage this technology to mine available socioeconomic, political, geographic, and environmental data responsibly and to provide indicators that predict future global supply and demand. This information is crucial for energy security and ensuring global economic prosperity.

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Big Data and Energy Security: Impacts on Private Companies, National Economies and Societies

10.21203/rs.3.rs-505894/v1 ◽

2021 ◽

Author(s):

Hossein Hassani ◽

Nadejda Komendantova ◽

Daniel Kroos ◽

Stephan Unger ◽

Mohammad Reza Yeganegi

Keyword(s):

Big Data ◽

Energy Security ◽

Energy Markets ◽

Reliable Data ◽

Environmental Data ◽

Data Set ◽

Private Companies ◽

Market Stability ◽

National Economies ◽

Big Data Technology

Abstract The importance of energy security for successful functioning of private companies, national economies, and the overall society should not be underestimated. Energy is a critical infrastructure for any modern society, and its reliable functioning is essential for all economic sectors and for the well-being of everybody. Uncertainty in terms of the availability of information, reliable data to make predictions and to plan for investment as well as for other actions of stakeholders at the energy markets is one of the factors, which has the highest influence on energy security. This uncertainty can be connected with many factors such as the availability of reliable data or the actions of stakeholders themselves. For example, the recent outbreak of the COVID-19 pandemic revealed negative impacts of uncertainty on decision-making processes and markets. At the time point when the market participants started to receive real-time information about the situation, the energy markets began to ease. This is one scenario where Big Data can be used to amplify information to various stakeholders to prevent panic and to ensure market stability and security of supply. In a fast-paced digital world characterized by technological advances, the use of Big Data technology provides a unique niche point to close this gap in information disparity by levering the use of unconventional data sources to integrate technologies, stakeholders, and markets to promote energy security and market stability. The potential of Big Data technology is yet to be fully utilized. Big Data can handle large data set characterized by volume, variety, velocity, value, and complexity. The challenge for energy markets is to leverage this technology to mine available socioeconomic, political, geographic, and environmental data responsibly as well as to provide indicators that predict future global supply and demand. This information is crucial for energy security and ensuring global economic prosperity.

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Monitoring and Operation Analysis on Power Environment of Computer Room Based on Big Data

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.864.258 ◽

2017 ◽

Vol 864 ◽

pp. 258-263

Author(s):

Li Bo Cai ◽

Wei Zhang ◽

Li Xin Zhao ◽

Xu Bin Yang ◽

Long Chen

Keyword(s):

Big Data ◽

Environmental Data ◽

Security Technology ◽

Operation Analysis ◽

External Data ◽

Decision Module ◽

Enhance Efficiency ◽

Monitoring Module ◽

Remote Inspection ◽

Big Data Technology

Based on the requirement of the Reduce of power information network failures, the power environment monitoring system based on big data is designed and implemented. The system includes five application modules: acquisition and monitoring module, resource management module, analysis and decision module, alarm center module and configuration management module. An improvement of Apriori algorithm by the unique design array which is used for data analysis can enhance efficiency of the algorithm. The system based on Big Data technology, by the efficient analysis of power data, environmental data, main data and external Data, to achieve a comprehensive perception of monitoring and operation analysis on power environment of computer room based on big data, intelligent auxiliary user decisions. Through research and implementation of the project, we can realize real-time monitoring of the video and the environment of the substation, besides we can locate and prevent the various alarms (fire, flooding and theft, etc.) timely. Providing effective technical support for staff remote inspection and troubleshooting. The project can prevent accidents, combat crime, protect property, ensure that the system is stable, and make the substation security technology improving to a new level.

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Application and Architecture of Power Dispatching & Distribution System Using Big Data Technology

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1070-1072.1425 ◽

2014 ◽

Vol 1070-1072 ◽

pp. 1425-1429

Author(s):

Rong Chang Yuan ◽

Hu Yan ◽

Xiao Ming Zhou ◽

Fang Chun Di ◽

Li Xin Li

Keyword(s):

Big Data ◽

Smart Grid ◽

System Architecture ◽

Distribution System ◽

Data System ◽

Environmental Data ◽

Distribution Data ◽

Complex Data ◽

Power Dispatching ◽

Big Data Technology

As the new energy resources including scenery storage have been well accessed into power grid, the operation process of power dispatching and distribution involves the massive, multi type, high complex data which contain the real-time data, plan data, warning and monitoring data, environmental data. Nowadays, the application of big data focused on single analysis of structured and semi-structured data. And the deep learning analysis hasn’t been concerned, transforming power gird data into knowledge is the inevitable trend in the development of smart grid. In this paper, the power dispatching and distribution data were analyzed in detail from the data source, data characteristics, the trend of application etc. According to the new requirement of smart grid now and in the future, the potential application with big data technology was studied in the field of smart grid and the reference opinions was provide by intelligent analysis and decision which are accurate, security, economic, comprehensive optimal features. Finally, to meeting requirement of the power dispatching & distribution data analysis, power dispatching and distribution data system architecture was designed which is an integrated software/hardware, storage-computation-communication trinity. And it was proved that power dispatching and distribution data system architecture have strong supporting, service and safety ability.

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PSYCHOLOGICAL ASPECTS OF USING BIG DATA TECHNOLOGY IN THE CONTEXT OF DISTANCE LEARNING

Yaroslavl Pedagogical Bulletin ◽

10.20323/1813-145x-2020-5-116-177-183 ◽

2020 ◽

Vol 116 (5) ◽

pp. 177-183

Author(s):

Tatiyana V. Bugaichuk ◽

◽

Polina A. Polyakova ◽

Keyword(s):

Big Data ◽

Distance Learning ◽

Education System ◽

Negative Impact ◽

Well Being ◽

Data Sets ◽

Educational Organizations ◽

Amount Of Information ◽

Training Systems ◽

Big Data Technology

The issue of studying a person's abilities to perceive a large amount of information during the period of distance learning is poorly understood and extremely relevant. The problem of our research is the identification of modern technologies for supporting education system specialists in working with a large amount of information, the ability to perceive and analyze it, as well as reducing the level of information fatigue among educational workers during distance learning, since the digitalization of education has an intense negative impact on mental processes of employees, on their psychological and social well-being. The article describes the results of a theoretical study of the interdisciplinary convergence of the indicated problem, expanding the understanding of Big Data technology through the psychology of abilities and the psychology of education. At the same time, the authors of the article note the increasing role of Big Data technology in the modern conditions of a pandemic and distance learning. Big Data technology or «Big Data» means a certain system of methods and some algorithms for working with large amounts of data. These data sets are aimed at acquiring a qualitatively new understanding of what this information carries. Now there are four main directions of the formation of large volumes of data in the education system. These are online training systems, internal information systems of educational organizations, information about employees and the requirements of the organization's management to potential employees, information about students. Having studied the main directions of Big Data development when processing large amounts of various information, we found links with the implementation of Big Data methods, tools and technologies in the field of education and the efficiency of employees. The authors identified and studied an important function of Big Data in the period of distance learning – it is the creation of psychological well-being of employees of the education system and the leveling of the problem of information fatigue.

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Strategic threats to energy security as risks of quality of people's life

National Interests Priorities and Security ◽

10.24891/ni.16.4.730 ◽

2020 ◽

Vol 16 (4) ◽

pp. 730-744

Author(s):

V.I. Loktionov

Keyword(s):

Quality Of Life ◽

Energy Security ◽

Well Being ◽

Scientific Methods ◽

Analysis And Synthesis ◽

General Scientific ◽

And Performance ◽

Economic Well Being ◽

The Way

Subject. The article reviews the way strategic threats to energy security influence the quality of people's life. Objectives. The study unfolds the theory of analyzing strategic threats to energy security by covering the matter of quality of people's life. Methods. To analyze the way strategic threats to energy security spread across cross-sectoral commodity and production chains and influences quality of people's living, I applied the factor analysis and general scientific methods of analysis and synthesis. Results. I suggest interpreting strategic threats to energy security as risks of people's quality of life due to a reduction in the volume of energy supply. I identified mechanisms reflecting how the fuel and energy complex and its development influence the quality of people's life. The article sets out the method to assess such quality-of-life risks arising from strategic threats to energy security. Conclusions and Relevance. In the current geopolitical situation, strategic threats to energy security cause long-standing adverse consequences for the quality of people's life. If strategic threats to energy security are further construed as risk of quality of people's life, this will facilitate the preparation and performance of a more effective governmental policy on energy, which will subsequently raise the economic well-being of people.

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A New Rockburst Experiment Data Compression Storage Algorithm based on Big Data Technology

Intelligent Automation & Soft Computing ◽

10.31209/2019.100000111 ◽

2019 ◽

pp. 561-573

Author(s):

Yu Zhang ◽

Yan-Ge Wang ◽

Yan-Ping Bai ◽

Yong-Zhen Li ◽

Zhao-Yong Lv ◽

...

Keyword(s):

Big Data ◽

Data Compression ◽

Experiment Data ◽

Big Data Technology

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Using Big Data Technology For Prediction Of Quiz Difficulty Level In E-learning Systems

10.34279/0923-008-004-014 ◽

2018 ◽

pp. 176

Author(s):

Hiba A. Abu Alsaad ◽

Rana Riad K. Al Taie

Keyword(s):

Big Data ◽

Learning Systems ◽

Difficulty Level ◽

E Learning ◽

Big Data Technology

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Validity of the “Big Data Tendency in Education” Scale as a Tool Helping to Reach Inclusive Social Development

Sustainability ◽

10.3390/su12135470 ◽

2020 ◽

Vol 12 (13) ◽

pp. 5470 ◽

Cited By ~ 2

Author(s):

Antonio Matas-Terrón ◽

Juan José Leiva-Olivencia ◽

Pablo Daniel Franco-Caballero ◽

Francisco José García-Aguilera

Keyword(s):

Big Data ◽

Inclusive Education ◽

Sustainable Development Goals ◽

Sustainable Society ◽

Education Students ◽

The Sustainable Development ◽

Research Goal ◽

Development Goals ◽

Nonprobability Sample ◽

Big Data Technology

Big Data technology can be a great resource for achieving the Sustainable Development Goals in a fair and inclusive manner; however, only recently have we begun to analyse its impact on education. This research goal was to analyse the psychometric characteristics of a scale to assess opinions that educators in training have about Big Data besides their related emotions. This is important, as it will be the educators of the future who will have to manage with Big Data at school. A nonprobability sample of 337 education students from Peru and Spain was counted. Internal consistency, as well as validity, were analysed through exploratory and confirmatory factorial analysis. The results show good psychometric values, highlighting as relevant a latent structure of six factors that includes emotional and cognitive dimensions. As a result, the profile defining the participants in relation to Big Data was identified. Finally, the implications of the Big Data for Inclusive Education in a sustainable society are discussed.

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