Innovation diffusion for renewable energy technologies

Abstract

We present an analysis of innovation diffusion models for solar energy technologies based on the spread of information in real-world social networks. Three dynamic innovation diffusion networks are simulated through diverse configurations of the Barabási Albert model with a linear threshold approach to information spread, using a dataset of Twitter messages about solar and renewable energy as reference information diffusion network. The characteristics of the simulated dynamic innovation diffusion networks (e.g. number of informed nodes) are then compared with those of the reference information diffusion network to establish which innovation diffusion model yields the best fit. The results of this analysis provide a solution for the development of the innovation diffusion component for renewable energy adoption models. We demonstrate the feasibility of including the innovation diffusion factor into an agent-based model of the solar PV market, which is applied to Qatar market.