Speaker
Description
Renewable energy is fundamental to achieving a sustainable future, as it enhances energy security and environmental sustainability, while supporting long-term economic development. Future energy systems are expected to rely increasingly on renewable energy and to transition from conventional centralized infrastructures toward cleaner, decentralized energy (DE) systems. These DE systems are typically characterized by distributed generation based on various renewable resources, including small-scale hydropower, solar, wind, biomass, biogas, and geothermal energy. Despite their growing importance, the technical performance, economic viability, and broader societal and environmental impacts of DE systems have not yet been comprehensively evaluated. Furthermore, the widespread deployment of renewable energy technologies continues to face numerous challenges across generation, distribution, and consumption. Addressing these challenges is crucial for accelerating the transition toward resilient and sustainable energy systems.
Evaluating the performance and impact of DE systems requires a structured and consistent way to handle a wide range of technical, economic, social and environmental factors. This inherently constitutes a multiple criteria decision analysis (MCDA) problem, requiring the evaluation of various quantitative and qualitative factors under uncertainty, drawing on both numerical data and expert judgement. Building upon a comprehensive review of the concepts, current developments, emerging trends, benefits and challenges with DE systems, this research develops an integrated multi-criteria performance modelling and impact analysis framework for multi-vector DE systems. The Evidential Reasoning (ER) approach is employed to represent and aggregate a wide range of performance indicators, encompassing both quantitative and qualitative attributes, while explicitly capturing uncertainty and incomplete information. By providing a systematic and transparent mechanism for performance modelling and impact assessment, the proposed framework can support a wide range of stakeholders, including policymakers, energy suppliers, network operators, consumers, and investors, in assessing performance and support decisions related to the planning, evaluation, deployment, and operation of DE systems.
| Keywords | Performance Modelling; Renewable Energy; MCDA; Evidential Reasoning |
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| Participation in the SNSF Early-Stage Researcher Support and Award Scheme | I am submitting a regular presentation and would like to participate in the SNSF Early-Stage Researcher Support and Award Scheme. |