The viability of existing energy infrastructures is being challenged globally. Concerns about climate change, energy security, resource scarcity, growth in demand, and others, are at the forefront of national political debate and international civil action the world over. The complexity of this environment sits in stark relief to existing energy planning tools, which remain locked in a deterministic, “least-cost” optimization paradigm. The inadequacy of such an approach is becoming patently obvious.

As a point of departure, this paper considers energy infrastructures as complex adaptive systems. Descriptive models for such systems must include the capacity for distributed decision making, recognize the emergence of behaviour(s) over the whole system which are not apparent from the behaviour of the component sub systems, be able to characterize dynamic responses which give rise to a range of pseudo-stable operating environments, all within a climate of uncertainty and (possible) conflicts of interest amongst various stakeholders.

Specific attention is given to the role of Agent-Based Modelling (ABM) tools to map distributed decision making , demonstrating how these can complement existing infrastructure planning tools, and how such an integrated approach can contribute to decision support frameworks based on Multi-Criteria Decision Making (MCDM). This approach is demonstrated for selected case studies from the electricity sector.