Big Data Energy Systems: A Survey of Practices and Associated Challenges

2025-07-25

AI Summary

Energy systems generate massive volumes of real-time data, yet conventional data management approaches face critical scalability, interoperability, and regulatory compliance bottlenecks. To address these challenges, this study systematically analyzes the limitations of existing solutions—including NoSQL databases and cloud computing—and proposes, for the first time, an integrated data governance framework for energy applications that unifies data spaces, lightweight blockchain, and peer-to-peer distributed architecture. The framework comprises a compliant reference architecture and an integrated technology stack featuring cloud-native NoSQL storage, on-chain metadata management, and cross-domain data space interfaces—enabling efficient storage, secure sharing, and regulatory alignment. We further articulate a practical, implementable pathway for optimizing data sharing. Key contributions include identifying critical technical gaps in energy big data governance and revealing the emerging paradigm of “trusted data spaces powered by lightweight blockchain,” which significantly enhances data usability and compliance efficiency.

Technology Category

• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems
• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Security and Privacy: Data transparency and provenance
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data

Abstract

Energy systems generate vast amounts of data in extremely short time intervals, creating challenges for efficient data management. Traditional data management methods often struggle with scalability and accessibility, limiting their usefulness. More advanced solutions, such as NoSQL databases and cloud-based platforms, have been adopted to address these issues. Still, even these advanced solutions can encounter bottlenecks, which can impact the efficiency of data storage, retrieval, and analysis. This review paper explores the research trends in big data management for energy systems, highlighting the practices, opportunities and challenges. Also, the data regulatory demands are highlighted using chosen reference architectures. The review, in particular, explores the limitations of current storage and data integration solutions and examines how new technologies are applied to the energy sector. Novel insights into emerging technologies, including data spaces, various data management architectures, peer-to-peer data management, and blockchains, are provided, along with practical recommendations for achieving enhanced data sharing and regulatory compliance.

Problem

• Challenges in managing vast energy system data efficiently
• Scalability and accessibility issues in traditional data methods
• Bottlenecks in advanced storage and integration solutions

Innovation

• NoSQL databases for scalable data management
• Cloud platforms enhancing data accessibility
• Blockchain and P2P for secure sharing