2023
DOI: 10.3390/en16176272
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A Pragmatic Framework for Data-Driven Decision-Making Process in the Energy Sector: Insights from a Wind Farm Case Study

Konstantinos Konstas,
Panos T. Chountalas,
Eleni A. Didaskalou
et al.

Abstract: In an era of big data, organizations increasingly aim to adopt data-driven decision-making processes to enhance their performance. This paper investigates the data-driven decision-making process by developing a framework tailored for application in the energy sector. The proposed framework integrates interdisciplinary approaches to comprehensively address the “data, information, knowledge” triad, applying it to both operational and maintenance decision-making. Designed to be managerially focused rather than te… Show more

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Cited by 4 publications
(2 citation statements)
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“…It emphasizes the need for policy frameworks that are managerially focused, enabling employees across various roles to contribute effectively to the decision-making process. Such frameworks are essential for solving problems, predicting trends, and discovering new opportunities in the energy sector (Konstas et al, 2023). Kormpakis et al (2023) highlight the importance of a security framework in the digitization of the energy sector, particularly for role-based access management.…”
Section: Policy Framework Influencing Geo-data Applicationmentioning
confidence: 99%
“…It emphasizes the need for policy frameworks that are managerially focused, enabling employees across various roles to contribute effectively to the decision-making process. Such frameworks are essential for solving problems, predicting trends, and discovering new opportunities in the energy sector (Konstas et al, 2023). Kormpakis et al (2023) highlight the importance of a security framework in the digitization of the energy sector, particularly for role-based access management.…”
Section: Policy Framework Influencing Geo-data Applicationmentioning
confidence: 99%
“…The inherent intermittency of wind and solar resources leads to fluctuations in power output, which, if not managed effectively, can result in grid instability and operational inefficiencies. This volatility exacerbates the complexities of balancing energy supply and demand, leading to curtailment of renewable generation or reliance on conventional backup sources, hindering the overarching goal of a clean and reliable energy transition (Chountalas PT, 2023) [3] Conventional deterministic forecasting methods often fall short in adequately addressing the uncertainties inherent in renewable energy generation. Consequently, there is an exigent need for sophisticated control methodologies capable of adapting to dynamic conditions and optimizing the operation of hybrid power systems comprising hydro, wind, and solar resources.…”
Section: Introductionmentioning
confidence: 99%