Exploring near-optimal energy systems with stakeholders: a novel approach for participatory modelling

arXiv:2501.0528024.23 citationsh-index: 6
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This work addresses the need for more inclusive energy planning by enabling stakeholders to explore a continuum of designs without predefined scenarios, but the contribution is incremental as it applies existing near-optimal methods to participatory modelling.

The authors developed a participatory modelling framework using near-optimal energy system designs to engage stakeholders, allowing them to explore trade-offs interactively. In a case study of Longyearbyen, participants consistently deviated from cost-optimal solutions, balancing emissions, costs, and vulnerability.

Involving people in energy systems planning can increase the legitimacy and socio-political feasibility of energy transitions. Participatory research in energy modelling offers the opportunity to engage with stakeholders in a comprehensive way, but is limited by how results can be generated and presented without imposing assumptions and discrete scenarios on the participants. To this end, we present a methodology and a framework, based on near-optimal modelling results, that can incorporate stakeholders in a holistic and engaging way. We confront stakeholders with a continuum of modelling-based energy system designs via an interactive interface allowing them to choose essentially any combination of components that meet the system requirements. Together with information on the implications of different technologies, it is possible to assess how participants prioritise different aspects in energy systems planning while also facilitating learning in an engaging and stimulating way. We showcase the methodology for the remote Arctic settlement of Longyearbyen and illustrate how participants deviate consistently from the cost optimum. At the same time, they manage to balance different priorities such as emissions, costs, and system vulnerability leading to a better understanding of the complexity and intertwined nature of decisions.

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