# Multilevel Emulation for Stochastic Computer Models with Application to Large Offshore Wind farms

arXiv: https://arxiv.org/abs/2003.08921 · HTML: https://mlsanity.com/paper/2003.08921/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Mar 2020.

## Built on by (most cited first, 1 of 1)

- [Sensitivity Analysis in the Presence of Intrinsic Stochasticity for Discrete Fracture Network Simulations](https://mlsanity.com/paper/2312.04722/) (2023)

## Abstract (arXiv)

Renewable energy projects, such as large offshore wind farms, are critical to achieving low-emission targets set by governments. Stochastic computer models allow us to explore future scenarios to aid decision making whilst considering the most relevant uncertainties. Complex stochastic computer models can be prohibitively slow and thus an emulator may be constructed and deployed to allow for efficient computation. We present a novel heteroscedastic Gaussian Process emulator which exploits cheap approximations to a stochastic offshore wind farm simulator. We also conduct a probabilistic sensitivity analysis to understand the influence of key parameters in the wind farm model which will help us to plan a probability elicitation in the future.