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Accounting for uncertainty when using computer models as decision-support tools in energy system planning

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MESW02 - Electricity systems of the future: incentives, regulation and analysis for efficient investment

Computer models are widely used as decision-support tools for planning energy systems in both industry and government. These computer models are often computationally intensive and have high-dimensional input spaces, making it difficult to quantify the impact that different sources of uncertainty have on model output. Without a complete picture of the effect of these uncertainties it is difficult to take planning decisions that are robust in the real-world. This presentation will discuss methodology for accounting for uncertainties in computationally intensive energy planning models. Both input uncertainty and uncertainty in the structure of the model itself will be considered. An emulator, or statistical model of the underlying computer model, will be used to quantify uncertainty in areas of the input space where it has not been possible to make model runs. This emulator will be combined with a description of the uncertainty over the input space and a description of the structural error to quantify uncertainty in model outputs. Several real-world examples in energy planning will be discussed, including the modelling of wholesale electricity prices and making decisions about renewable support schemes.

This talk is part of the Isaac Newton Institute Seminar Series series.

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