Breaking gridlock: Design and implementation of a Multi-Criteria Decision Assessment (MCDA) for sustainable electricity development in Ontario
The expansion and composition of the electricity grid is of paramount importance to the electrification of the economy and achieving climate change mitigation goals. However, electricity system planning is an increasingly wicked problem involving many stakeholder groups and combining technical, economic, environmental, and social dimensions. The complicated decision-making environment requires structured tools to chart an optimal development strategy for the future. This dissertation presents a multi-criteria decision assessment (MCDA) specifically designed to explore zero emission development scenarios for the Canadian Province of Ontario, although the methodology is applicable to other jurisdictions.
The MCDA was implemented in a user-friendly spreadsheet to improve accessibility and enable broad stakeholder engagement. Decision makers were presented with a baseline case and five scenario alternatives. Users were then asked to rank ten criteria according to their relative importance and an algebraic formula was used to assign criteria weights. The PROMETHEE method was used to generate a solution hierarchy, and users were prompted to evaluate if the solution hierarchy aligned with their expectations and values.
Twelve respondents participated in the consultation process. The scenarios involving more hydropower, wind and solar energy were broadly the most preferred solutions across all stakeholders. Conversely, both scenarios involving natural gas were clearly unacceptable. Cost, resilience, technological and commercial maturity, and energy security were deemed the most important criteria across all respondents. By comparison, societal acceptance and employment were deemed the least important. The results of the study were analysed in an attempt to identify stakeholder typologies and highlight demographic co-factors among groups of decision makers with similar preferred outcomes, however the sample size was not large enough to be representative and the link between demographics, scenario preference and criteria ranking is inconclusive.