TUE 2:00 PM Special Summary of Energy Dynamics Thread

Full Report:
Boundary Diversity Concerning Scales and Levels
The inherent challenge of energy planning and implementation are multi-scale and multi-level interactions between actors, networks, institutions (e.g. rules guiding the interactions), and the ecological environment as a source and sink of a dynamic, complex system. The strength of system dynamics models are their flexibility as an analytical construct for any system in focus defined by scale- and level-specific boundaries for a specific policy or management purpose. The most obvious scales and levels that come to my mind are presented in the schematic below.

Fig. 1: Schematic illustration of differences in scales and levels of dynamic energy models for planning, management and policy analysis

This strength has the downside that the field of system dynamics energy modeling and research is characterized by heterogeneous models and results that are neither easily comparable nor add straightforwardly to a harmonized body of knowledge bounded by generalized research frontiers. In order to illustrate this observation, I will briefly sketch some selected conference presentations.

Illustrations of Typical Cases
Sorting out energy-related system dynamics contributions within the last few system dynamics conferences poses problems since they can be found in disparate threads. A first attempt shows that system dynamics conferences include about twenty energy-related contributions with one-three plenary presentations, perhaps nine parallel presentations, and ten posters. Most promising signaling words of related contributions are energy, electricity, fuel, power, renewable, climate, and technology.


For the short illustration of the heterogeneity in the present system dynamics energy research, we refer to the Renewable Energies and Energy Efficiency parallel session of the system dynamics conference held in Albuquerque, 2009, which included three typical contributions:

In the following table, these three cases are characterized along the different scales as indicated in Fig. 1.

Scales and Level

Solar Power & Grid Parity

Renewable Energy Industry in Massachusetts

South African Energy Model

Policy / Management focus

Policy assessment and implementation

investment strategies

Policy and strategy analysis

Energy policy planning

Technology boundary

Focused on photovoltaic technology

Focused on photovoltaic technology

Aggregated electricity energy system

Knowledge boundary

Co-evolution of generation capacity, infrastructure and localized marginal prizing, referring to Renewable Portfolio Standard

Context specific

Diffusion patterns depending on the strengths of feedback loops

Specific and contextual lessons about policies that are robust to change

Policy analysis regarding energy demand – supply balance within a simple T21 framework for South African
Specific and contextual lessons

Jurisdictional boundary

US state level

Organizations of the renewable industry at US state level

Nation (South African)

Spatial boundary

US region

US region

African region


Graphs over time
Price development and diffusion patterns
Sensitivity studies

Graphs over time
Policy elasticities (Marketing, Incentive, Installer, Distributor, and Vision)

Graphs over time
Scenario analysis concerning demand and supply matches


Policy Implications

Method of phase plane analysis

A preliminary behavioral theory of the photovoltaic markets in MA

Method of policy specific feedback loop analysis

Energy module for a T21 framework for South Africa

Policy recommendations

Data source


Mental models of experts

Not clear

References to SD work

Considerable to energy dynamics

Few to method, none to energy dynamics

Few to method and energy dynamics

Table 1: Illustrative case comparison concerning scales and levels

This short case illustration highlights how different scales and foci as well as research techniques hamper the accumulation of a general and universal body of knowledge explaining energy dynamics. Although the first two cases seem to have much in common, more research in both cases is needed in order identify common research grounds in terms of similar concepts and comparable result presentations and interpretations. The third case seems to add to an active research stream. However, it is neither clearly indicated how this research builds on research of the existing T21 framework nor do the findings relate to other general and universal insights identified in the T21 modeling approach.

Cornerstones and concepts
The downside of heterogeneity and flexibility in energy dynamics modeling can be overcome, proven by the successful history of the USA National Energy Policy Model. The history shows that outstanding energy dynamics modeling work was chosen as a cornerstone in order to advance and adjust it to new national energy challenges as indicated in Fig. 2. One of the hidden success factors may be the personnel and institutional ownership of the analysis frameworks, allowing refining and adapting previous work to new challenges. Also, the researcher’s mentor and research network may have facilitated the succession of coherent energy dynamics modeling work.

Fig. 2: Illustration of the intellectual lineage of system dynamics energy modeling

However, this specific intellectual lineage of system dynamics energy modeling addressing national energy planning issues may not satisfy all the specific needs in the transition challenge that lies ahead of us. The multitude of the presented case studies indicate the need for an accumulation of further coherent research streams addressing task-specific scales and levels for policy and decision makers involved in the transition task.

Hence, we look forward to the ramifications of the intellectual lineage of energy dynamics modeling characterized by committed researchers following up on promising cornerstones and enriching the energy dynamics community with a succession of refined dynamic concepts and frameworks that make a real change in the world. Only by providing trustworthy and convincing simulation models for the different transition tasks may we be able to inform the mental models of policy makers, managers and citizens in such a way that they effectively jump out of the boiling water as soon as possible.

Silvia Ulli-Beer, Paul Scherrer Institut, Switzerland