Big Data analytics in Smart Grids for renewable energy networks: Systematic review of information and communication technology tools

Colmenares-Quintero, Ramón Fernando; Quiroga-Parra, Darío Jesús; Rojas, Natalia; Stansfield, Kim E.; Colmenares, Juan Carlos

doi:10.1080/23311916.2021.1935410

Cited by 16 publications

(4 citation statements)

References 26 publications

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“…This integrated geospatial database was applied through geospatial analysis, data analytics and Business Intelligence (BI) to develop the EBS V2G framework. BI allows the transformation of the data, analysis, assessments and optimization tools into meaningful insights, recommendations and plans that have practical applications for stakeholders to develop a successful EBS V2G system [39,40]. BI has been considered in previous research for renewable energy and V2G applications, but its application to ESB systems integrated with geospatial analysis has been limited [41][42][43].…”

Section: Methodsmentioning

confidence: 99%

Framework to Develop Electric School Bus Vehicle-to-Grid (ESB V2G) Systems Supplied with Solar Energy in the United States

Haces-Fernandez

2024

Energies

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Federal and state governments in the United States (US) are promoting the transition from traditional Diesel School Buses to Electric School Buses (ESBs). This would prevent the emission of deleterious air pollutants that affect students and communities while simultaneously contributing to a reduction in greenhouse gases, aiding in the fight against climate change. However, due to their significant size and long routes, ESBs require large batteries with significant electricity demand. If this additional electricity demand is supplied to hundreds of thousands of EBSs at peak consumption times, the strain on the grid may be detrimental, while transportation costs for schools could dramatically increase. Furthermore, if EBSs are charged using traditional hydrocarbon generation, the environmental benefits of these projects may be significantly reduced. Therefore, applying renewable energy presents a host of synergistic opportunities to reduce emissions while providing inexpensive electricity to schools. Solar energy is abundant in large portions of the US, potentially providing many schools with ample inexpensive and sustainable electricity to power their transportation equipment and meet other requirements at their facilities. This research developed a novel framework to integrate publicly available big data provided by federal and state agencies in the US, as well as National Laboratories, to provide stakeholders with actionable information to develop EBS grid-to-vehicle (V2G) systems across the US. Geographic Information Systems, data analytics and Business Intelligence were applied to assess and characterize solar energy generation and consumption patterns. The novel integration of the systems in the proposed framework provided encouraging results that have practical implications for stakeholders to develop successful and sustainable ESB V2G facilities. These results identified many schools across the US that would significantly benefit from the use of solar energy and be able to supply their local communities during idle times with renewable energy through V2G. The renewable energy resource would be capable of charging ESBs at a low cost for operational availability as required. The results indicate that the proposed ESB V2G system will provide significant benefits to both schools and their local communities. The feasibility of the proposed endeavor was validated by the results of the study, providing both school and solar energy stakeholders with insights into how to better manage such a complex system.

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Section: Methodsmentioning

confidence: 99%

Framework to Develop Electric School Bus Vehicle-to-Grid (ESB V2G) Systems Supplied with Solar Energy in the United States

Haces-Fernandez

2024

Energies

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“…The study underscores the advantages of smart grids in enhancing operational efficiency, reducing energy costs, and improving the reliability and sustainability of industrial electrical systems. The role of big data analytics in smart grids, particularly for renewable energy networks, is highlighted by Colmenares-Quintero et al (2021). Their systematic review of information and communication technology tools in smart grids reveals the growing importance of data analytics and business intelligence in the management of energy companies.…”

Section: Significance Of Smart Grids In the Industrial Landscapementioning

confidence: 99%

Smart Grids in Industrial Paradigms: A Review of Progress, Benefits, and Maintenance Implications: Analyzing the Role of Smart Grids in Predictive Maintenance and the Integration of Renewable Energy Sources, Along With Their Overall Impact on the Industri

Chinedu Alex Ezeigweneme,

Chinedu Nnamdi Nwasike,

Adedayo Adefemi

et al. 2024

Eng. sci. technol. j.

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This study provides a comprehensive analysis of the integration and impact of smart grids in the industrial sector, focusing on the evolution from traditional grids, the role of predictive maintenance, and the integration of renewable energy sources. The primary objectives were to understand how smart grids are reshaping industrial energy management and to assess their impact on efficiency, sustainability, and operational practices. A systematic literature review was employed as the methodology, utilizing electronic databases and academic journals to gather relevant literature from 2018 to 2023. The search strategy involved keywords related to smart grids, predictive maintenance, and renewable energy integration. Inclusion and exclusion criteria were established to ensure the relevance of the selected literature, which was then thematically synthesized to identify key trends and insights. Key findings indicate that smart grids mark a significant shift in energy management, offering enhanced efficiency, reliability, and sustainability. The integration of renewable energy sources addresses challenges like intermittency, contributing to environmental sustainability. Predictive maintenance within smart grids has emerged as a crucial strategy for improving operational efficiency and reducing maintenance costs. The study also highlights the economic and environmental impacts of smart grid technologies, underscoring their potential in promoting sustainable industrial practices. Finally, smart grids represent a pivotal advancement in industrial energy management. The study recommends continued innovation and strategic implementation to realize their full potential, with future research focusing on AI applications, emerging renewable sources, and policy frameworks in smart grid technologies. Keywords: Smart Grids, Predictive Maintenance, Renewable Energy, Industrial Efficiency.

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“…Research has been conducted on developing advanced techniques for detecting and preventing cyberattacks in smart grids [18,19]. This includes anomaly detection algorithms [20,21], intrusion detection systems (IDS) [22,23], machine-learning-based approaches [24,25], and data analytics to detect and respond to suspicious activities in real time [26,27]. Securing communication channels and implementing robust authentication mechanisms are crucial for protecting smart-grid infrastructure [28].…”

Section: Existing Researchmentioning

confidence: 99%

Cyberattacks in Smart Grids: Challenges and Solving the Multi-Criteria Decision-Making for Cybersecurity Options, Including Ones That Incorporate Artificial Intelligence, Using an Analytical Hierarchy Process

Bouramdane

2023

JCP

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Smart grids have emerged as a transformative technology in the power sector, enabling efficient energy management. However, the increased reliance on digital technologies also exposes smart grids to various cybersecurity threats and attacks. This article provides a comprehensive exploration of cyberattacks and cybersecurity in smart grids, focusing on critical components and applications. It examines various cyberattack types and their implications on smart grids, backed by real-world case studies and quantitative models. To select optimal cybersecurity options, the study proposes a multi-criteria decision-making (MCDM) approach using the analytical hierarchy process (AHP). Additionally, the integration of artificial intelligence (AI) techniques in smart-grid security is examined, highlighting the potential benefits and challenges. Overall, the findings suggest that “security effectiveness” holds the highest importance, followed by “cost-effectiveness”, “scalability”, and “Integration and compatibility”, while other criteria (i.e., “performance impact”, “manageability and usability”, “compliance and regulatory requirements”, “resilience and redundancy”, “vendor support and collaboration”, and “future readiness”) contribute to the evaluation but have relatively lower weights. Alternatives such as “access control and authentication” and “security information and event management” with high weighted sums are crucial for enhancing cybersecurity in smart grids, while alternatives such as “compliance and regulatory requirements” and “encryption” have lower weighted sums but still provide value in their respective criteria. We also find that “deep learning” emerges as the most effective AI technique for enhancing cybersecurity in smart grids, followed by “hybrid approaches”, “Bayesian networks”, “swarm intelligence”, and “machine learning”, while “fuzzy logic”, “natural language processing”, “expert systems”, and “genetic algorithms” exhibit lower effectiveness in addressing smart-grid cybersecurity. The article discusses the benefits and drawbacks of MCDM-AHP, proposes enhancements for its use in smart-grid cybersecurity, and suggests exploring alternative MCDM techniques for evaluating security options in smart grids. The approach aids decision-makers in the smart-grid field to make informed cybersecurity choices and optimize resource allocation.

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Big Data analytics in Smart Grids for renewable energy networks: Systematic review of information and communication technology tools

Cited by 16 publications

References 26 publications

Framework to Develop Electric School Bus Vehicle-to-Grid (ESB V2G) Systems Supplied with Solar Energy in the United States

Framework to Develop Electric School Bus Vehicle-to-Grid (ESB V2G) Systems Supplied with Solar Energy in the United States

Smart Grids in Industrial Paradigms: A Review of Progress, Benefits, and Maintenance Implications: Analyzing the Role of Smart Grids in Predictive Maintenance and the Integration of Renewable Energy Sources, Along With Their Overall Impact on the Industri

Cyberattacks in Smart Grids: Challenges and Solving the Multi-Criteria Decision-Making for Cybersecurity Options, Including Ones That Incorporate Artificial Intelligence, Using an Analytical Hierarchy Process

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