Executive Summary:
Within the context of project tracking in Lens Hydrogen, the term Likelihood refers to the probability of a hydrogen project reaching an operational state. It is presented as a percentage between 0% and 100%. Wood Mackenzie’s hydrogen research team has developed a methodology for calculating likelihood based on key predictive indicators. This is intended to serve as a quantitative framework for estimating project likelihood, and to improve overall consistency in estimating likelihood across our project tracking efforts.
The term Likelihood Category is an attribute of a hydrogen project phase and corresponds to a numeric value of Likelihood. Figure 1 provides a representation of the Likelihood scale.
Likelihood is calculated at a project phase level and is based on a scoring rubric which currently covers four categories:
Geographic advantage
Developer credibility
Phase planning completeness
Phase status
Each category covers one or more sub-dimensions which are scored individually. The scores for each are then weighted to provide an overall score which equates to Likelihood.
1.This is applicable only to cancelled, retired or inactive projects.
2.This is only applicable to projects which are under construction or operational.
3.In Lens Hydrogen a project-level likelihood score will also be shown based on the underlying phase-level scores.
For single- phase projects this project- level score will match the phase-level score, However, the project-level score for multi-phase projects is derived from the likelihood score from the phase with the most recent status change.
Category and Dimensions Weight:
Category and dimension weights depend on the colour of the project. To understand the rationale for selecting each of the sub-dimensions considered, see the Appendix.
The weightings applied to green and other low-carbon projects are almost identical, except for there being a different weighting for the project phase sizing and offtake firmness dimensions.
Project phase sizing contributes 2.5% for green hydrogen projects and 1.5% for other low-carbon projects. Green projects receive a higher weighting due to greater variability in project sizes, making phase sizing a more important consideration than in other project types with less variable implementation scales. To balance this, offtake firmness carries a lower weight for green projects (4%) compared with others (5%). Green hydrogen projects typically face a wider range of challenges due to the sector’s nascency of the sector and associated technology. Consequently, offtake firmness is considered a marginally smaller factor in determining overall project likelihood for green hydrogen initiatives.
4. Whether a project has offtake in place will impact its status, as this is indicative of a more advanced project. As such, this is an implicit component of the Status dimension. The Offtake firmness dimension considers the firmness of an offtake deal and assigns greater value to deals which are firmer. Hence, Offtake firmness is included within the Phase Planning Completeness category as it considered separately to offtake as a component of Status.
Scoring Rubric:
Geographic Advantage - 20% contribution to Likelihood
Each country receives a Geographic Advantage score that aggregates the risk from four dimensions: policy readiness, maturity of country project pipeline, geographic location and levelised cost of hydrogen production (LCOH).
Developer Credibility - 20% contribution to Likelihood:
Each phase receives a Developer Credibility score based on a developer’s experience in developing hydrogen projects, the company’s experience in an adjacent sector, and the company employee count which is considered indicative of its capacity to deliver the project.
5. The country's average LCOH is evaluated against a global range of LCOH values for a project reaching FID in the year 2027, and a lower LCOH would correspond to higher likelihood score for this dimension. Each project receives relevant LCOH score, and this would be dependent on the color of the hydrogen produced by the project.
Phase Planning Completeness - 10% contribution to Likelihood:
Each phase receives a Phase Planning Completeness score based on announced phase characteristics, including offtake agreement firmness, availability of timeline, partners, project phase sizing, and phase capacity data availability.
Phase Status- 50% contribution to Likelihood:
Each phase receives a Status score. The status of a Project phase is by far the most important indicator of likelihood as it is a reflection of how far the project has progressed down the development pipeline, and takes account of which development milestones have been reached. Hence, the weighting applied to this category is considerably higher than all others. For details on how status is assigned see the appendix. Projects that are Under Construction or Operational receive a default likelihood score of 100% and projects that are Cancelled, Retired, or Inactive receive a default likelihood score of 0%, hence these statuses not being included in the below table.
6. The table details the methodology applied to electrolytic projects. A modified version is applied to other project types wherein operator data is used in place of electrolyser vendor data.
7. The table details the methodology applied to electrolytic projects. A modified version is applied to other project types wherein a net project capacity is used instead of electrolyser capacity.
8. The table details the methodology applied to electrolytic projects. A modified version is applied to other project types based on relevant factors like whether a CCUS capacity has been announced.
Likelihood calculation:
The below provides an example of how the final likelihood percentage is calculated based on the scoring rubric and dimension weights. In this example, the developer score is zero, meaning this category does not appear on the scoring chart as it does not contribute to the overall score.
Appendix:
Dimension selection rationale
Data availability and a qualitative assessment of useful likelihood indicators guided the selection of dimensions for this analysis. The WoodMac analyst team determined dimension weights through an iterative process. They tested different weighting breakdowns and assessed results for specific projects. The team chose the final dimension weight distribution which the WoodMac analyst team judged to produce the most accurate likelihood scores.
