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Enhancing Energy Systems with Privacy-Aware Data Sharing and Collaborative Intelligence

Title: Enhancing Energy Systems with Privacy-Aware Data Sharing and Collaborative Intelligence
Authors: Boiarkin, V.
Publication Year: 2025
Collection: City University London: City Research Online
Subject Terms: T Technology; TA Engineering (General). Civil engineering (General); TK Electrical engineering. Electronics Nuclear engineering
Description: The growing demand for electricity and the increasing complexity of energy systems have necessitated innovative approaches to efficient, secure, and sustainable energy management. Energy systems are undergoing a transformative shift driven by Smart Grid technologies that integrate renewable energy sources and distributed energy sources, as well as advanced data-driven technologies. These innovations aim to enhance energy management, reduce environmental impact, and empower consumers as active participants in energy markets. However, traditional energy systems face challenges such as inefficiencies in pricing and energy trading, centralization risks, and data privacy concerns. Recent research highlights the limitations of centralized systems, emphasizing the need for secure, scalable, and user-centered approaches that preserve data privacy while enabling efficient energy management. Emerging technologies, such as blockchain, differential privacy, and federated learning, offer promising solutions to address these challenges. This work focuses on innovative pricing models for energy trading, advanced privacy-preserving techniques for data-sharing, and secure collaborative frameworks for energy demand forecasting to enhance the functionality, security, and equity of modern energy systems. To this end, several contributions are presented. The first contribution is a novel dynamic pricing model tailored for a microgrid of prosumers with photovoltaic panels. The proposed model introduces mathematical frameworks for determining equilibrium prices based on supply-demand ratios and incorporates mechanisms for calculating energy usage costs, profits, and penalties for participants who deviate from predicted energy profiles. The effectiveness of the model is validated using real-world energy profiles, showcasing its potential to reduce energy costs. The second contribution is a blockchain-based data-aggregation scheme for a microgrid of prosumers. This scheme ensures prosumers’ privacy by concealing their real energy usage ...
Document Type: thesis
File Description: text
Language: English
Relation: https://openaccess.city.ac.uk/id/eprint/36388/1/Boiarkin%20Thesis%202025%20PDF-A.pdf; Boiarkin, V. (2025). Enhancing Energy Systems with Privacy-Aware Data Sharing and Collaborative Intelligence. (Unpublished Doctoral thesis, City St George's, University of London)
Availability: https://openaccess.city.ac.uk/id/eprint/36388/
Accession Number: edsbas.3512F11
Database: BASE