An Agent-based Model for Sustainable Power Generation using Optimal Biomass Utilisation

Exponential growth in the global population induces larger dependencies on natural resources to meet the demands for products causing resource depletion and environmental degradation. As such, there is an impetus to transform current industrial systems into systems that operate based on inherent sustainable values. While most of the current energy systems are based on polluting fossil fuels, alternative sources have exhibited high performances both economically and environmentally. Biomass for instance, represents a potential source for energy utilisation. Understanding the functioning of biomass gasification strategies as part of the biorefinery system's operations is fundamental, yet, not sufficient to grant sustainable energy provision. The deployment of biomass technologies should also be assessed whilst considering the interaction with other energy sources. The purpose of this work is to design a dynamic and sustainable decision-making scheme that predicts the performance of the power generation system. The framework is developed as an agent-based model illustrating the several entities contributing to the shift towards a biomass-fuelled energy system. The power generation system and biomass feedstock producers are the main categories of agents interacting with one another following a set of rules restricting their behaviors with an ultimate aim to determine the optimal energy portfolio to meet energy demands whilst considering the contribution of existing natural-gas power plants and biomass blending. Rules of interactions impacting strategies adopted are imposed through two different scenarios representing the environmental and economic performances. Findings of this research demonstrate that under environmental restrictions, a diversified energy mix supporting the contribution of biomass is environmentally viable, as it contributes to a 34% reduction in emissions. However, it entails an economic expenditure amounting to 64% increase owing to the deployment of biomass technologies. The optimal biomass blending indicates the domination of manure feedstock over date pits, sludge and food waste in both scenarios, being the lowest in both economic and environmental costs.