This paper proposes the application of a multivariate diffusion model, based on ordinary differential equations, to investigate the energy transition in Germany. Specifically, the model is able to analyze the dynamic interdependencies between coal, gas and renewables in the energy market. A system dynamics representation of the model is also performed, allowing a deeper understanding of the system and the set-up of suitable strategic interventions through a simulation exercise. Such simulation provides a useful indication of how renewable energy consumption may be stimulated as a result of well-specified policies.

Bioenergy is being increasingly used worldwide to generate energy from biogas, biomethane, and other biofuels, bringing significant environmental and economic benefits. In Italy, biogas can significantly contribute to the achievement of the renewable energy targets set at the national and European levels. The exploitation of this energy source in a particular area is determined by its environmental and anthropic properties, as well as by the incentive system and the political will of decision makers. This paper analyzes the socioeconomic drivers and natural conditions triggering bioelectricity production in Italian regions. The analysis proposed here was performed in two steps—first, by identifying groups of similar regions for some natural, social, and economic variables, and then by modeling the historical trajectory of bioelectricity production for each identified group with innovation diffusion models. As a general finding, regions pertaining to the same group in terms of natural and socioeconomic conditions revealed a similar production pattern for bioelectricity, as confirmed by the results of diffusion modeling. On the basis of the diffusion modeling procedure, some scenario simulations were performed, which suggested the set-up of suitable policy actions for each group of regions.