Smart Grid Systems: Addressing Privacy Threats, Security Vulnerabilities, and Demand–Supply Balance (A Review)

Iqra Nazir, Nermish Mushtaq and Waqas Amin ()
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Iqra Nazir: School of Information and Control Engineering, Southwest University of Science and Technology, Mianyang 621010, China
Nermish Mushtaq: School of Information and Control Engineering, Southwest University of Science and Technology, Mianyang 621010, China
Waqas Amin: School of Information and Control Engineering, Southwest University of Science and Technology, Mianyang 621010, China

Energies, 2025, vol. 18, issue 19, 1-77

Abstract: The smart grid (SG) plays a seminal role in the modern energy landscape by integrating digital technologies, the Internet of Things (IoT), and Advanced Metering Infrastructure (AMI) to enable bidirectional energy flow, real-time monitoring, and enhanced operational efficiency. However, these advancements also introduce critical challenges related to data privacy, cybersecurity, and operational balance. This review critically evaluates SG systems, beginning with an analysis of data privacy vulnerabilities, including Man-in-the-Middle (MITM), Denial-of-Service (DoS), and replay attacks, as well as insider threats, exemplified by incidents such as the 2023 Hydro-Québec cyberattack and the 2024 blackout in Spain. The review further details the SG architecture and its key components, including smart meters (SMs), control centers (CCs), aggregators, smart appliances, and renewable energy sources (RESs), while emphasizing essential security requirements such as confidentiality, integrity, availability, secure storage, and scalability. Various privacy preservation techniques are discussed, including cryptographic tools like Homomorphic Encryption, Zero-Knowledge Proofs, and Secure Multiparty Computation, anonymization and aggregation methods such as differential privacy and k-Anonymity, as well as blockchain-based approaches and machine learning solutions. Additionally, the review examines pricing models and their resolution strategies, Demand–Supply Balance Programs (DSBPs) utilizing optimization, game-theoretic, and AI-based approaches, and energy storage systems (ESSs) encompassing lead–acid, lithium-ion, sodium-sulfur, and sodium-ion batteries, highlighting their respective advantages and limitations. By synthesizing these findings, the review identifies existing research gaps and provides guidance for future studies aimed at advancing secure, efficient, and sustainable smart grid implementations.

Keywords: blockchain; cybersecurity; data privacy; demand–supply balance; energy storage; homomorphic encryption; machine learning; peer-to-peer trading; pricing models; smart grid (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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