Sugar cane, grown widely in African countries, is known to be one of the most productive species in terms of its conversion of solar energy to chemical potential energy. However, the deployment and diffusion of this technology option on large scale basis is hindered by the complexity in bio-electricity generation. The conversion pathways across bio-electricity production involve water, energy, and land-use planning decision and policy making often occurs in separate and disconnected institutional entities. As such the analytical tools used in support of the decision making process are equally fragmented. In addition the supply of feedstock for electricity generation is limited to the crop harvest season. Let alone the supply is threatened by a wide range of factors among which includes declining sugar prices, competing priorities for land and water which hinder growth of this sector. The complexity warrants the need for decision support tools that can be used not only to broaden the understanding of electricity generation but provide ways of enhancing the energy value of sugarcane production systems in an integrated manner. Using Mauritius as an example this study applied Spatial Systems Dynamics Model (SSDM) that provides a platform for multi-disciplinary simulation. The model integrates the spatial complexity in biomass production, socio-technical complexities in electricity production, and environmental implications in terms of emission avoidance. The model provides multiple scenarios of bio-electricity generation projected from 2012 to 2035. The model highlights the significance of good policy interventions required to optimize electricity production, the potential environmental benefits, and technological improvements that are critical for decision-making especially to a small developing island like Mauritius, which depends heavily on imported fossil fuels to meet its energy demand
