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An agent-based model is developed for investigating the role of individual behaviour and network influence on energy innovation diffusion. Behaviour is based on how agents value specific attributes of a technology, and network effects are disaggregated into indirect influence through exposure to a larger population, and direct influence through personal contacts. We find that network influence can have a positive effect on accelerating the diffusion of new energy innovations, but can be counteracted by risk adverse behaviour. Combined direct and indirect network effects can have as strong an influence on adoption behaviour as personal preferences. Interestingly, we find that indirect influence from the larger population can have a greater effect than direct personal contacts on an individual. This implies a feedback between population and sub-population level signals on adoption behaviour which warrants further …