WP:2 – Methods and toolkit (TU Delft)

This work package focuses on developing, improving, and making use of methods for social process design, making models linkable, analyzing uncertainty propagation, scaling, and working principle effects in multi-model interactions, and translating these into practical toolkits for integrated decision-making.


This work package delivers the following generically applicable results with a project-specific implementation:

wp:2:r:3 Multi-model methods

This result has a strong scientific and model methodological character.
By methods, we mean mathematical and algorithmic methods for:

      1. Quantifying uncertainty propagation between models interacting via the multi-model infrastructure
      2. Linking models operating on different spatial and temporal scales and
      3. Linking models with different operating principles

wp:2:r:4 Conceptual framework for multi-models

The conceptual framework is understood to mean creating a “model of the multi-model”, i.e., a formal ontological and algorithmic description of:

      1. ”Boilerplate” metadata about individual models and their properties
      2. Language for information exchange between energy models
      3. Language for dynamic control and orchestration of models

wp:2:r:5 Concepts and methods for a generic scenario space

Language and method for spanning a generic scenario space that enables Deep Uncertainty analysis using Exploratory model analysis. This includes matters such as the ontology of scenario dimensions, relevant sets of possibilities per aspect, timing of events, and ontology of policy instruments and institutional setup.

wp:2:r:6 Tooling for multi-models

This result has a strong design character. The methods and concepts are made operational for practice. This concerns practical manuals and any software toolkits for:

      1. Model selection that takes into account capabilities and limitations of individual models
      2. Alignment representation within a multi-model framework such as system boundaries, resolution, scale, and so on.
      3. Architecture, definitions, specifications, and standards for linking models that take into account functional and performance requirements, the technical format of the data exchange between models, and the use of external data and information in models.
      4. Creating a collaborative scenario space that enables Deep Uncertainty analysis through Exploratory model analysis
      5. Methodology for using multi-models

This concerns an integrating result, which consists of a scenario/manual for performing participatory multi-modeling processes using the tooling.

wp:2:r:7 Participatory process for integrated decision-making (IO)

This result has a strong social process character. This result focuses on the “front and back” of the multi-modeling process, which is based on the “Good Modeling Practice” guide on The results and experiences from the project are translated in the form of a step-by-step plan/manual and the following aspects are discussed:

      1. Definition and understanding of integrated decision making
      2. Identifying the need for information and insights in integrated decision-making
      3. Identifying and communicating the (im)possibilities that multi-modelling offers for integrated decision-making
      4. Identify, supplement, and use the generic scenario space
      5. Communicating outcomes of multi-models, with specific attention to uncertainties

Success Indicators

All results of the wp:2 are in the form of reports describing the methods and are measurable as such.


The bulk of the activities within wp:2 concerns scientific research into methods and their further development. These methods are tested and improved in an iterative process, mainly through interaction with tooling activities and the cases in wp:4.
This activity starts by identifying and bringing together pre-existing knowledge so that it lays off a foundation that can be applied in the first iteration.