(45e) Sustainable Planning of Urban Energy-Water-Food Nexus through Decision Making Tools

The United Nation’s Sustainable Development Goals (UN SDGs) condense the major challenges facing human society into 17 categories, many of which are interlinked and related to the energy-water-food (EWF) and climate change nexus. Integrated system analysis is more and more important for sustainable development by addressing challenges in natural resources, economic sectors, and human behaviors in a systematic manner. However, the main infrastructure and service of energy, water and food sectors are delivered in an isolated manner, causing investment and operational strategies limited to a single system and neglecting potential synergies across sectors.

To address the urgent challenges society is facing in urbanization and its associated energy demand and supply, we developed a holistic methodology and platform to support the resilient and sustainable planning at city-region level for multiple sectors, combining agent-based modelling to simulate and forecast resource demands on spatial and temporal scales, with resource network optimization incorporating capital expenditures, operational costs, and environmental impacts to find optimal allocations of resources and technologies given these demands [1]. In addition to a comprehensive study of water and sanitation sector study in a developing country context [2], we will also demonstrate how this framework can be applied to urban energy systems and the energy-water-food nexus.

The results suggest environmentally friendly and cost effective plans for sustainable city development by 2030. Both energy demand side simulation and supply side optimization are used to test innovative energy deployment policies especially to address the provision of clean energy for every citizen. A set of scenarios consisting of technological evolvement, effects of climate change and related policies are created to illustrate the application of the model especially in energy sector development. The cost of greenhouse gas emissions and the opportunity cost of land use based on the feasible food production are evaluated and optimized in various scenarios. Some typical scenarios are discussed in details including climate change impacts and policy interventions, such as how the capacity factor reduction for large-scale hydropower, feed-in electricity tariffs or agricultural intensification with yield increasing change the optimal power generation mix in future. Specific to the studied region (e.g., Ghana), it is found that the reduced power generation by large-scale hydropower is compensated for by the introduction of additional natural gas, solar thermal and photovoltaic capacity. Agricultural intensification is observed to promote the use of both solar thermal and solar photovoltaic power with a preference for solar photovoltaic power. Not only specific case and scenario analysis, the major contributions of this work also include the creation of a generalized algorithm within a uniform platform that can effectively handle and dispatch different types of technology in a variety of essential sectors.

[1] Xiaonan Wang, Koen H. van Dam, Charalampos Triantafyllidis, Rembrandt H.E.M. Koppelaar, and Nilay Shah. "Improving energy and water management in sustainable urban development by a systematic decision-making platform" (under review).

[2] Charalampos Triantafyllidis, Rembrandt H.E.M. Koppelaar, Xiaonan Wang, Koen H. van Dam, and Nilay Shah. "Resilience.io: An integrated optimisation platform for sustainable resource and infrastructure planning" (under review).