Big Data and Energy Poverty Alleviation

Hassani, Hossein; Yeganegi, Mohammad Reza; Beneki, Christina; Unger, Stephan; Moradghaffari, Mohammad

doi:10.3390/bdcc3040050

Cited by 32 publications

(21 citation statements)

References 85 publications

(103 reference statements)

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“…En cuanto a la metodología, este aporte forma parte del universo de estudios sobre la cuestión social y ambiental a partir de la aplicación de técnicas de análisis de grandes datos. En este sentido, dialoga directamente con trabajos que evalúan la situación de vulnerabilidad y privación en hogares con respecto a la disponibilidad de energéticos residenciales, su calidad y uso (Chévez, Barbero, Martini, & Discoli, 2017;Hassani, Yeganegi, Beneki, Unger, & Moradghaffari, 2019;Wang, Li, Yuan, & Sun, 2017). En este sentido, el trabajo contribuye a los nuevos estudios de pobreza a partir de la aplicación de métodos y técnicas de análisis de grandes datos y agrupamiento (Hassani et al, 2019;Njuguna & McSharry, 2017), entre los que se cuenta con experiencias de análisis de pobreza energética y también la definición de indicadores de pobreza y vulnerabilidad.…”

Section: Discussionunclassified

Caracterización de hogares para el desarrollo socialmente inclusivo de la energía solar residencial en Argentina mediante el empleo de métodos de clustering

Durán

Condorí

2020

Ingeo

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Se propone la realización de un análisis de composición socio-económica y energética de los hogares argentinos, con el objetivo de generar información que sirva para la definición de políticas de desarrollo en energía solar con una óptica de inclusión y desarrollo social. Para ello, se aplicaron métodos de clustering y análisis de grandes datos, en particular k-means, two step cluster, y análisis de factores principales, a una base de datos construida a partir de datos del Instituto Nacional de Estadísticas y Censos, Secretaría de Energía de la Nación, Ente Regulador Nacional del Gas, Solar and Wind Energy Resource Assessment y National Renewable Energy Laboratory. Como resultado, se evidencian hogares con problemáticas similares con respecto al acceso a los energéticos y otros derechos básicos, el impacto del costo de la energía y el recurso solar disponible. Estas agrupaciones han sido mapeadas al nivel de radio censal, la unidad geográfica y de análisis más pequeña del censo argentino. Así, se concluye con la definición de perspectivas de acción para el desarrollo energético y socialmente inclusivo de cada una de las agrupaciones de hogares, tanto rurales como urbanos.

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Section: Discussionunclassified

Caracterización de hogares para el desarrollo socialmente inclusivo de la energía solar residencial en Argentina mediante el empleo de métodos de clustering

Durán

Condorí

2020

Ingeo

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“…As a consequence, although it seems reasonable to believe that some EP affected households consumption patterns could be identified through smart technologies, if big data is to be used, much more than just smart metering in the hands of utilities should be analyzed [38].…”

Section: Discussion / Conclusionmentioning

confidence: 99%

Smart Meters Tackling Energy Poverty Mitigation: Uses, Risks and Approaches

Casals

Herrero

Barbero

et al. 2020

2020 IEEE Electric Power and Energy Conference (EPEC)

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Big data analysis is becoming an increasing field of interest for research to analyse, identify and predict final user's behaviour. For this reason, in the energy sector, smart metering is generally used to find new business opportunities and, theoretically, it is said that it could also help to fight energy poverty issues. Nonetheless, when tackling social injustice issues, the deployment of massive technology might also bring other side effects. This study analyses the capability of smart metering to mitigate energy poverty in Europe according to the current approaches of projects and the risks it might bring to the more vulnerable layers of our society.

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“…Although big data solutions are well developed for forecasting some risk factors (like weather conditions), there are not many solutions for other forecasting other risk factors. For instance, forecasting socio-economic variables affecting energy demand is a challenge itself [43].…”

Section: Practical Issues and Challengesmentioning

confidence: 99%

“…As an immediate consequence of increased energy prices or disruption in energy supply, the rate of energy poverty increases in society. Accordingly, it increases social distress, healthcare costs and affects households' ability to provide work force and contribute to the economy [43].…”

Section: Practical Issues and Challengesmentioning

confidence: 99%

“…Policymakers need to have a comprehensive understanding of energy risk factors and energy supply situations, to choose between policies and approaches. For instance, if the policymakers choose to invest in renewable energy sources for long term energy supply, they should first investigate the availability and sufficiency of such resources [43].…”

Section: Practical Issues and Challengesmentioning

confidence: 99%

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

Hassani

Komendantova

Kroos³

et al. 2021

Preprint

Self Cite

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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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Big Data and Energy Poverty Alleviation

Cited by 32 publications

References 85 publications

Caracterización de hogares para el desarrollo socialmente inclusivo de la energía solar residencial en Argentina mediante el empleo de métodos de clustering

Caracterización de hogares para el desarrollo socialmente inclusivo de la energía solar residencial en Argentina mediante el empleo de métodos de clustering

Smart Meters Tackling Energy Poverty Mitigation: Uses, Risks and Approaches

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

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