Deploying sustainable energy technologies to enhance global development and human well being

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Addressing the climate emergency requires energy systems models to ensure efficient use of resources. The complexity of the challenges that these models are being asked to address has increased significantly. Models are being asked to represent variable renewable energy and storage, to incorporate trade-offs between land, energy, and water, and to address uncertainties. Not addressing these challenges, synergies and trade-offs can lead to inefficient use of resources. This research program addresses major modelling challenges for sustainable development. The long-term objectives support sustainable development at the local, regional, and international scale through creating effective modelling tools, and apply these tools to policy making around the globe. Short term objectives address uncertainty in systems models, develop algorithms for incorporating the UN Sustainable Development Goals (SDGs), and address challenges posed by demand side management (DSM) and storage. Work addressing uncertainty in energy system models focusses on financial risks and not risks related to climate impacts, nor future demand/population projections. Expanding the risks that models address will result in better policy decisions. For example, addressing the risk of shifts in solar resources can reduce the likelihood of installing solar panels in locations where the future resource is not suitable. Given the resource limitations being faced in addressing the climate crisis, incorporating uncertainty into system models will reduce the inefficient use of resources. Incorporating more aspects of the SDGs into models will address trade-offs and synergies. Recent work incorporates aspects of the nexus of land, energy and water into models, but this needs to be expanded. Expanding the nexus to include health and biodiversity will better address trade-offs. For example, indoor air quality from burning biomass is not currently considered in most electrification plans, but in developing countries these impacts could significantly shift the benefits of electrification. Finally, addressing DSM and storage will be critical in future planning of the energy system. These emerging technologies allow more variable renewable energy sources to contribute to reducing climate emissions, but the modelling tools to represent them are not well studied. Combined, these modelling enhancements will build a strong research program that will enhance decision making. Building models that consider the trade-offs in sustainable development is critical to efficient resource use. HQP working on the program will have the opportunity to apply their modelling knowledge to sustainable development projects around the globe, expanding the impact of the research program.