Unpacking uncertainty in the modelling process for energy policy making

TL;DR

This paper examines how energy system models can overly constrain policy options by overestimating certainty, and advocates for reflexive methodologies to improve robustness and inclusiveness in energy policy modelling.

Contribution

It introduces and demonstrates reflexive modelling practices like NUSAP, diagnostic diagrams, and sensitivity auditing to address overconfidence in energy system models.

Findings

Reflexive practices improve model robustness.

Case studies show enhanced stakeholder engagement.

Methodologies help identify uncertainties and biases.

Abstract

This paper explores how the modelling of energy systems may lead to undue closure of alternatives by generating an excess of certainty around some of the possible policy options. We exemplify the problem with two cases: first, the International Institute for Applied Systems Analysis (IIASA) global modelling in the 1980s; and second, the modelling activity undertaken in support of the construction of a radioactive waste repository at Yucca Mountain (Nevada, USA). We discuss different methodologies for quality assessment that may help remedy this issue, which include NUSAP (Numeral Unit Spread Assessment Pedigree), diagnostic diagrams, and sensitivity auditing. We demonstrate the potential of these reflexive modelling practices in energy policy making with four additional cases: (i) stakeholders evaluation of the assessment of the external costs of a potential large-scale nuclear accident in Belgium in the context of the ExternE (External Costs of Energy) project; (ii) the case of the ESME (Energy System Modelling Environment) for the creation of UK energy policy; (iii) the NETs (Negative Emission Technologies) uptake in Integrated Assessment Models (IAMs); and (iv) the Ecological Footprint (EF) indicator. We encourage modellers to widely adopt these approaches to achieve more robust and inclusive modelling activities in the field of energy modelling.