Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/190586
Título: Blockchain Interoperability in Decentralized Energy Systems: A Performance Comparison of On-Chain and Cross-Chain Transactions in Cosmos-Based Microgrids
Autor: Himmelsbach, Jannik
Orientador: Naranjo-Zolotov, Mijail Juanovich
Palavras-chave: Blockchain Interoperability
Peer-to-Peer Energy Trading
Microgrid
Decentralized Energy Resources
Cosmos
Inter-Blockchain Communication Protocol (IBC)
SDG 7 - Affordable and clean energy
SDG 9 - Industry, innovation and infrastructure
SDG 11 - Sustainable cities and communities
SDG 12 - Responsible production and consumption
SDG 13 - Climate action
Data de Defesa: 29-Out-2025
Resumo: Blockchain interoperability is critical for decentralized peer-to-peer energy trading in interconnected microgrids, yet the performance trade-offs of single-chain versus multi-chain architectures remain poorly understood. This study evaluates the feasibility and efficiency of Cosmos-based blockchain setups for energy transactions, comparing on-chain execution with cross-chain transfers using the Hermes relayer. Through experimental simulations with synthetic energy data, cross-chain transactions demonstrated a 24% increase in gas costs compared to on-chain operations. However, absolute costs remained low, suggesting practical viability despite overheads. These findings highlight a trade-off: multi-chain architectures enable decentralized flexibility across microgrids at modest operational costs, though scalability and security require further optimization. The study provides a foundational framework for evaluating blockchain interoperability in energy systems, underscoring the need for future work integrating real-world datasets and heterogeneous blockchain ecosystems to advance resilient, decentralized energy markets.
Descrição: Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
URI: http://hdl.handle.net/10362/190586
Designação: Mestrado em Ciência de Dados e Métodos Analíticos Avançados, especialização em Data Science
Aparece nas colecções:NIMS - Dissertações de Mestrado em Ciência de Dados e Métodos Analíticos Avançados (Data Science and Advanced Analytics)

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