Rembrandt H.E.M. Koppelaar

An integrated optimisation platform for sustainable resource and infrastructure planning

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.

Waste-Energy-Water systems in sustainable city development using the resilience.io platform

Abstract The move towards more sustainable cities involves rethinking various infrastructure systems and supply chains, including those for energy and waste. To provide decision support to local stakeholders, the resilience.io platform provides a series of modules to allow forecasting of socio-demographic changes, simulating spatio-temporal activities and planning investment and operational strategies to meet the sustainable development goals for multiple domains including water, energy, food and cities. In this paper we apply these tools to waste-to-energy pathways, aiming to develop treatment capacity and energy recovery with the lowest cost. Two categories of waste including wastewater (WW) and municipal solid waste (MSW) are analysed as the source of biogas through either direct combustion for combined heat and power generation in incinerators, or anaerobic digestion (AD) for electricity and heating along with digestate produced. Results show that for a case study in Ghana a combination of waste incineration, large-scale AD for WW and MSW and farm-scale AD for plantations, depending on local characteristics for supply and demand, provides waste treatment and energy at lowest cost. This application demonstrates how simulation and optimisation models can provide new insights in the design of value chains, with particular emphasis on whole-system analysis and integration.