The SIIA framework combines principles from technology assessment ("Technikfolgenabschätzung") with process and systems engineering across all life cycle stages. Its core focus is on the integration of processes, systems, and sectors; the role of storages, batteries, and securities in temporal integration; and the interaction of networks, grids, infrastructure and trade routes for spatial integration.

The SIIA framework seeks to provide a balanced perspective on positive impacts, such as improved efficiency and reliability, and negative impacts, including cascading risks and the inertia of integrated solutions compared to standalone alternatives. The framework supports convergence between operational, tactical, and strategic planning across scales and governance levels, aiming to amplify synergies while mitigating trade-offs and systemic risks arising from increasing complexity.

SIIA is implemented as a qualitative methodological extension of IIASA’s models, particularly the BeWhere model, as well as macroeconomic and energy system models. Model-Based Systems Engineering (MBSE) using UML or SysML enables visualization of systems-of-systems through standardized, interoperable diagrams. Furthermore, SIIA can be formalized within a mathematical modeling framework using Hetero-Functional Graph Theory, which translates SysML diagrams into executable code.

 

About the SIIA framework

Value chain networks often exhibit complex architectures. Consider timber-based construction: wood is sourced from forests, cut into panels at sawmills, and further processed in downstream industries before reaching the construction site. Meanwhile, wood-processing residues, such as sawdust, are transported to pellet plants, where they are pressed into a storable energy commodity for residential heating. In such systems, residues from one sector become feedstocks for another, creating synergies rather than competition among sectors.

SIIA distills conceptual parallels across approaches such as process integration, industrial symbiosis, heating network synthesis, electricity sector coupling, multi-sector coupling, and nexus thinking. The framework calls for an explanation, qualitative or quantitative, of how and why the whole becomes greater than the sum of its parts.

Definitions of integration and flexibility:

We define system integration as the combination of two or more systems that were previously, or in reference cases, operated or planned separately. Impact assessment seeks a balanced evaluation of the value proposition of integrated planning by explicitly representing the interactions, synergies, trade-offs, and risks that emerge through integration.

Temporal, spatial, process, system, sectoral, and market integration enable, or at least increase, the flexibility of resource flows. Resources may be tangible commodities such as water, land, food, materials, energy, labor, and data, or intangible assets such as ideas, political voice, social capital, trust, and cultural knowledge.

We define flexibility as the ability to shift resources across time, space, processes, systems, and sectors. Flexibility emerges through integration and allows for balancing resource availability. However, flexibility can also be mismanaged, leading to imbalances or even propagating cascading risks.

Opportunities and threats of integration:

The key opportunity of integration lies in transforming abundance into reliability. This involves efficiently valorizing surpluses by redirecting them to times, spaces, or sectors where they are needed. We refer to this as efficient reliability, which helps absorb uncertain variabilities, trends, and extreme events, whether originating in the Earth system or the human system. For instance, batteries allow abundant and low-cost electricity to be stored and later used to cover shortages or prevent outages. Similarly, bioeconomy infrastructure facilitates proactive forest management against threats such as wildfires or pests, while channeling harvested wood into diverse markets.

A key threat of integration lies in the interconnection of vulnerabilities. This risk manifests as the cascading propagation of shocks, errors, or attacks across interconnected entities. For example, a power outage can disrupt digital communication systems, making the analog radio capacities of first responders indispensable. Similarly, tightly coupled smart grids, smart homes, and digitally linked electric vehicle charging infrastructure create opportunities for cyberattacks and can overload electricity networks through excessive capacity or demand.

The SIIA framework seeks to enable a balanced assessment of integration impacts, supporting strategies that amplify beneficial effects while mitigating detrimental ones.

 

SIIA as a Complementary Qualitative Methodology

A first step toward a more balanced account of integration impacts—based on qualitative methodologies—is to raise awareness of boundary regions in existing modeling setups and results. Boundary regions can be understood as inter-spatial, inter-temporal, or inter-sectoral artifacts. This perspective prompts questions such as:

  • How feasible are the projected trade flows between two countries, and what do these flows imply for the import and export regions?
  • How does the size of a biogas plant affect its local environment, social acceptance, and participation opportunities?
  • How can we automate the flexible operation of a battery or a combined heat and power plant, and how does this shortto medium-term flexibility influence long-term strategy and planning, both on-site and for subsequent projects?

In general, we ask: Which processes, systems, sectors, and markets are involved and affected in the study area, and what potential synergies, trade-offs, and interconnected vulnerabilities emerge between them?

The next qualitative step is to raise awareness of biases and neglected uncertainties. Achieving a balanced account of integration impacts requires moderating both technology optimism and distrust, reconciling synergy-oriented and trade-off thinking, and understanding risk as a potential for both gain and loss. It also involves addressing resource efficiency alongside efficient error propagation and acknowledging that reliable and resilient entities can sometimes act as barriers to positive change.

Relevant uncertainties are often difficult to articulate and even more challenging to quantify or model. A simplified framework distinguishes uncertainties originating from dynamics in the Earth System, including:

  • the atmosphere (e.g., weather patterns and radiation),
  • the biosphere (e.g., biodiversity and pathogens),
  • the hydro- and cryosphere (e.g., precipitation and ice coverage), and
  • the geosphere (e.g., plate tectonics and erosion).

Additional uncertainties arise from the Human System, encompassing:

  • the sociosphere (e.g., geopolitics and social networks),
  • the technosphere (e.g., technology diffusion and supply chains),
  • the econosphere (e.g., prices and financial cycles), and
  • the cybersphere (e.g., digital connectivity and cybersecurity).

Uncertain variabilities, trends, and extreme events may originate within any of these spheres, or from their interactions.

Quantitative methodologies and models remain limited in addressing these uncertainties and the potential gains or losses associated with neglecting or managing them. Historically, energy system models (ESMs) and climate models introduced scenarios to explore uncertain trends. As variable renewable energy sources become more prominent, ESMs increasingly focus on uncertain variabilities, while climate models emphasize extreme events. From the SIIA perspective, we advocate for Integrated Assessment Models to incorporate a more balanced representation of uncertain trends, variabilities, and extreme events, originating from both the Earth system and the human system.

 

SIIA as a Formalized Mathematical Modelling Framework

Model-Based Systems Engineering (MBSE) using UML/SysML enables multi-resolution visualization of systems-of-systems, allowing us to zoom in and out and to delineate boundary regions between processes, systems, and markets, as well as between operational control and strategic planning. While spatial resolution and regional heterogeneity remain limited in pure SysML, future hard coupling with BeWhere can supply spatial explicitness and geoeconomic context. Crucially, this visual layer supports qualitative discourse and preserves ontological coherence, the consistent meaning of resources, processes, and operands across visual, mathematical, and computational representations.

Standardized SysML architectures can be translated into Hetero-Functional Graph Theory (HFGT), an ontology-driven formalism that extends classical graph theory to multi-layer networks with diverse operand flows (e.g., energy, materials, information). In HFGT, buffers (states, storages) and elements (transformations, transports) are linked by resource flows to unify system architecture and behavior. This makes the framework extensible, problem-independent, and capable of both analysis (robustness, resilience, reliability) and synthesis (architectural redesign, feedback reconfiguration, policy experimentation), including multi-timescale reasoning that bridges hour-to-decade decisions.

SIIA within HFGT supports comparative studies of integrated versus separate configurations of processes, systems, and markets. It quantifies how integration generates efficient reliability (valorizing surpluses through flexible reallocation across time, space, and sectors) while also exposing cascading risks (interdependent failure paths, cyber-physical coupling, congestion). Primary use cases are value-chain networks with process-engineering character, bioeconomy, circular economy, and the hydrogen economy, where metabolic flows of heterogeneous feedstocks yield products, residues, and emissions. In such systems, the value proposition is often non-obvious; SIIA clarifies why, where, and by how much the whole becomes more than the sum of its parts, while avoiding convergence pitfalls such as fragmented ontologies, reductionist bottom-up modeling, and co-simulation limits that miss multilateral feedbacks.

 

Key highlights and teaching materials

  • NEW: Schipfer, F., Harasek, M., Tiwari, S., Kraxner, F., Schmidt, J., Wehrle, S., Asasian Kolur, N., Thrän, D., Esmaeili Aliabadi, D., & Breunig, H. (2025).  “Are We Ready to Plan for Synergies? System Integration Impact Assessment in the Austrian Energy System Modelling Community.” Energy Research & Social Science 131 (January 2026): 104505. https://doi.org/10.1016/j.erss.2025.104505.
  • Harris M., Naderi M.M., Ghorbanichemazkati E., Jangjoo S., Laban E., Hosseini S.A., Schipfer F., Craig S., Moallemi E., Khayal I., Arpan L.M., Tang T., Little J.C., Farid A.M. “A System-of-Systems Convergence Paradigm for Societal Challenges of the Anthropocene.” arXiv:2603.01972. Preprint, arXiv, March 4, 2026. https://doi.org/10.48550/arXiv.2603.01972.
  • Schipfer F., Pralhad B., Uwe F., Christiane H., Stricker F., Wirth M., Proskurina S., Serna-Loaiza S. (2024). “The Circular Bioeconomy: A Driver for System Integration.” Energy, Sustainability and Society 14, no. 1 : 34. https://doi.org/10.1186/s13705-024-00461-4.
  • Schipfer F. (2025) Lecture on Technology Assessment and Systems Engineering. In Basics of Process Development and Life Cycle Assessment at Technische Universität Wien. 
  • Discussion document for the AFE Coordination Meeting, 2026 February 12th:

 

Ongoing projects

  • International Energy Agency (IEA) Bioenergy Technology Collaboration Programme (TCP) Task44: Flexible Bioenergy and System Integration https://task44.ieabioenergy.com/about-us/task-44-members/
  • Bioeconomy synergies across energy, materials, and food, socio-economic and regulating services. BioSyn project.
  • Strategy discussions for the next phase of the BeWhere modelling framework.

Past projects

  • Integrative energy infrastructure planning tool for inter-sectoral resilience and flexibilization concepts. FFG Project BioFlex. https://projekte.ffg.at/projekt/4875820