activity
20192022
most citedImportance subsampling: improving power system planning under climate-based uncertainty

58 citations · 63 across the 4 of their papers we have counts for

collaborators

5 papers

stat.AP20225 cited

Reducing climate risk in energy system planning: a posteriori time series aggregation for models with storage

Adriaan P Hilbers, David J Brayshaw, Axel Gandy

The growth in variable renewables such as solar and wind is increasing the impact of climate uncertainty in energy system planning. Addressing this ideally requires high-resolution…

eess.SY2022

Comparing Generator Unavailability Models with Empirical Distributions from Open Energy Datasets

Matthew Deakin, David Greenwood, David J. Brayshaw +1

The modelling of power station outages is an integral part of power system planning. In this work, models of the unavailability of the fleets of eight countries in Northwest Europe…

stat.AP2020

Importance subsampling for power system planning under multi-year demand and weather uncertainty

Adriaan P Hilbers, David J Brayshaw, Axel Gandy

This paper introduces a generalised version of importance subsampling for time series reduction/aggregation in optimisation-based power system planning models. Recent studies indic…

stat.AP2019

Efficient quantification of the impact of demand and weather uncertainty in power system models

Adriaan P Hilbers, David J Brayshaw, Axel Gandy

This paper introduces a new approach to quantify the impact of forward propagated demand and weather uncertainty on power system planning and operation models. Recent studies indic…

stat.AP201958 cited

Importance subsampling: improving power system planning under climate-based uncertainty

Adriaan P Hilbers, David J Brayshaw, Axel Gandy

Recent studies indicate that the effects of inter-annual climate-based variability in power system planning are significant and that long samples of demand & weather data (spanning…