An integrated optimisation platform for sustainable resource and infrastructure planning. (March 2018) - Triantafyllidis, Charalampos P.; Koppelaar, Rembrandt H.E.M.; Wang, Xiaonan; van Dam, Koen H.; Shah, Nilay
Abstract: It is crucial for sustainable planning to consider broad environmental and social dimensions and systemic implications of new infrastructure to build more resilient societies, reduce poverty, improve human well-being, mitigate climate change and address other global change processes. This article presents resilience.io, 2 a platform to evaluate new infrastructure projects by assessing their design and effectiveness in meeting growing resource demands, simulated using Agent-Based Modelling due to socio-economic population changes. We then use Mixed-Integer Linear Programming to optimise a multi-objective function to find cost-optimal solutions, inclusive of environmental metrics such as greenhouse gas emissions. The solutions in space and time provide planning guidance for conventional and novel technology selection, changes in network topology, system costs, and can incorporate any material, waste, energy, labour or emissions flow. As an application, a use case is provided for the Water, Sanitation and Hygiene (WASH) sector for a four million people city-region in Ghana. Highlights: A platform for resilient infrastructure planning to meet energy/material demands. Integration of Agent-Based and Mathematical Programming using open-source software. Flexible technology and waste scenario evaluation by input data-file adjustment. Integrated economic and environmental assessment using a weighted objective. A use case is provided to meet SDGs for water and waste-water treatment in Ghana.