Decentralizing energy: prosumers, carbon incentives, and market behaviors
Date
2025
Authors
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Publisher
University of Delaware
Abstract
This dissertation investigates the behavioral, economic, and institutional dimensions of prosumer-centered transitions in peer-to-peer (P2P) energy trading systems. Through four interlinked studies, it provides a comprehensive exploration of how decentralized energy platforms can be designed to support household-level energy autonomy while advancing market efficiency and climate mitigation goals. The research is situated in the context of Mauritius, a small island developing state facing pressing challenges of energy security, affordability, and decarbonization, and combines empirical modeling, survey experimentation, and market design. ☐ Chapter 2 provides a comprehensive review of P2P electricity trading. It synthesizes current academic and practical developments in market design, pricing mechanisms, and enabling technologies. The review categorizes market designs into centralized, decentralized, and distributed structures, and compares four pricing approaches: optimization, game theory, auction-based systems, and reinforcement learning. It highlights how emerging technologies like blockchain, IoT, artificial intelligence, and advanced communication networks support P2P energy systems. Importantly, the paper identifies persistent challenges in social acceptance, scalability, and regulation, especially the social ontology of trading behavior. A STEP analysis (Social, Technological, Economic, Political) frames future research needs to enhance the scalability, equity, and trustworthiness of P2P markets. This review offers critical insights for researchers and practitioners seeking to align decentralized energy markets with digital and decarbonized energy transitions. ☐ Chapter 3 explores the behavioral underpinnings of household participation in P2P energy trading, focusing on the trade-off between energy autonomy and financial incentives. Drawing on a nationwide survey with 111 households and applying multilevel regression and cluster analysis, the study identifies three distinct trading behavior archetypes: autonomy-oriented prosumers who limit trading to preserve stored energy, price-driven prosumers who prioritize economic gain, and non-monotonic prosumers with inconsistent trading patterns. The findings highlight that market liquidity in decentralized energy systems is shaped not only by physical capacity but by psychosocial preferences, underscoring the importance of designing user-centric platforms that accommodate behavioral diversity. ☐ Chapter 4 proposes a novel conceptual extension to the P2P trading model – the P2P+C framework –which integrates carbon offset monetization into local energy exchange. The model builds on the premise that P2P trading displaces grid-based fossil fuel consumption, generating verifiable carbon savings that can be bundled and sold on voluntary or compliance carbon markets. This integration creates a dual revenue stream for prosumers: earnings from electricity sales and dividends from carbon credit revenue. The framework positions P2P+C as a tool to link local energy resilience with global climate finance, particularly in off-grid and underserved regions, thereby democratizing access to sustainability resources and enabling financial transfers from carbon buyers in the Global North to communities in the Global South. ☐ Chapter 5 empirically tests the behavioral impact of the P2P+C model using a within-subjects Difference-in-Differences (DiD) design embedded in multilevel regression analysis. The results show that introducing carbon revenue significantly enhances both willingness to trade and price responsiveness among prosumers. Carbon incentives were especially effective in shifting the behavior of autonomy-oriented and threshold-based participants, suggesting that environmental monetization can act as a behavioral modulator in energy decision-making. Importantly, the study finds that prosumer engagement is better predicted by traits like risk-taking and community orientation than by standard socio-demographic factors, signaling the need for more nuanced segmentation and incentive strategies in P2P system design. ☐ Taken together, these chapters demonstrate that P2P energy trading systems are not purely technological constructs but socio-technical ecosystems shaped by behavioral dynamics and policy frameworks. The dissertation makes three central contributions: (1) it unpacks the micro-level behavioral constraints that influence market-level outcomes; (2) it introduces a financially viable mechanism for integrating climate value into decentralized energy systems; and (3) it empirically validates the effectiveness of compound incentive structures in enhancing participation. The findings offer actionable insights for platform developers, energy regulators, and climate finance institutions aiming to scale decentralized, equitable, and climate-aligned energy systems.
Description
Keywords
Behavioral analysis, Carbon markets, Distributed energy resources, Empirical analysis, Peer-to-peer electricity trading, Statistical analysis