Uncertainty analysis for optimal design and assessment of active electricity distribution networks
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2021-09-01
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Other Conference Item
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Abstract
Transitioning to sustainable, reliable and affordable energy is a worldwide challenge subject to many uncertainties. This project characterizes and quantifies the uncertainty associated with the design of active electricity distribution networks (ADNs) and microgrids with islanding ability. Here, distributed energy resources (DERs) are optimally placed to minimize total annual costs while achieving reliability and greenhouse gas emission targets. To understand which geographical, techno-economic and regulatory circumstances are amenable to DER and microgrid installation, the model response to the variation of 48 input parameters is tested. First, the uncertainty of the renewable en ergy sources and load profiles is characterized through the definition of "energy regions" based on climate Köppen Geiger classes, as well as wind and solar potential. Then, the optimal number of regions to capture most of the global variability is defined via the analysis of various clustering algorithms. For each region, a sensitivity analysis is performed through the elementary effect method, which enables to rank the parameters by relevance, and shows the variability of optimal ADN design throughout the regions. The elementary effects of all inputs, outputs and regions are aggregated with a new sensitivity
measure and used to determine a subset of highly influencing parameters.
Furthermore, the most influencing parameters are tested through an uncertainty analysis with distributions based on extensive literature research. Monte Carlo Filtering is finally used to capture the combinations of parameters that lead to a cost-competitive installation of DERs and microgrids.
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International Conference of Operations Research (OR 2021)
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09452 - Sansavini, Giovanni / Sansavini, Giovanni
Notes
Conference lecture held on September 1, 2021