The transformation of our energy system is a dynamic process that must be shaped amid uncertainty and often without perfect foresight. Political, technological, and societal conditions are constantly changing, while various stakeholders pursue objectives that are sometimes contradictory. Conventional modeling approaches in energy system analysis often reach their limits in this context: They typically calculate only a single, purely cost-optimal solution for a given objective. As a result, alternative courses of action as well as the specific path to achieving them, including potential dead ends and dependencies, remain largely unexplored.
To solve this problem, the OPTIMA research project combines two advanced modeling approaches for the first time: dynamic-recursive path modeling, which maps the transformation process step by step across several consecutive time periods, and the MGA (Modeling to Generate Alternatives) method. Instead of merely calculating a cost-optimized solution, MGA systematically generates a multitude of nearly equivalent but structurally distinct courses of action. This makes decisions more robust in the face of unforeseeable developments and reveals the actual scope for maneuver when conflicting objectives arise. To make the resulting volume of information manageable, we work with relevant stakeholders to develop participatory methods (such as data-driven clustering) that transparently condense these solution spaces and provide practical decision-making tools.
Project Objectives
- Application and further development of MGA (Modeling to Generate Alternatives): Utilizing the MGA methodology to systematically calculate a variety of near-optimal alternative solutions to identify realistic options for action when conflicting objectives arise
- Participatory Complexity Reduction: Development of methods (such as clustering) to work with stakeholders from the field to make the large sets of MGA solutions transparent and manageable.
- Field Testing and Open-Source Transfer: Testing the MGA approach in four cross-thematic case studies (a large centralized energy system, a small decentralized energy system, municipal heat planning, and transportation infrastructure), as well as the free publication of the models and guidelines for the scientific community and the energy sector.
Key Questions
- What options for action exist beyond the single cost-optimal path?
- How do decisions made under uncertainty play out over different time horizons?
- How can complex solution spaces be structured in a way that is practical for real-world applications?
- How can the dynamic-recursive MGA modeling approach be applied to different levels of the energy transition?
The EWI’s Role in OPTIMA
The EWI is contributing to “Work Package 3: Implementation of the Dynamic-Recursive MGA Workflow” and “Work Package 8: Synthesis & Open-Source Publication,” and is leading and carrying out the substantive work for “Work Package 6: Case Study 3: Municipal Heat Planning & Alignment with National Transformation Pathways.”
- Further development of EWI’s proprietary energy system model DIMENSION for dynamic-recursive MGA, including complexity reduction
- Based on the KOMPare data, use dynamic-recursive MGA to generate a reproducible set of near-optimal, bottom-up-informed heat transformation pathways and consolidate them into representative pathway archetypes.
- Evaluate the archetypes based on key KPIs (affordability/system costs, climate impact, feasibility—including grid and land requirements) and transparently highlight their alignment with the dena reference study path as well as the relevant trade-offs.