S. Haben

发表

Conditioning of incremental variational data assimilation, with application to the Met Office system

Nancy Nichols, Amos S. Lawless, Stephen Haben, 2011 .

Conditioning and preconditioning of the variational data assimilation problem

Nancy Nichols, Amos S. Lawless, Stephen Haben, 2011 .

Conditioning and preconditioning of the optimalstate estimation problem

N. Nichols, A. Lawless, S. Haben, 2014 .

A new error measure for forecasts of household-level, high resolution electrical energy consumption

Peter Grindrod, Danica Vukadinovic Greetham, Stephen Haben, 2014 .

Analysis and Clustering of Residential Customers Energy Behavioral Demand Using Smart Meter Data

Peter Grindrod, Stephen Haben, Colin Singleton, 2016, IEEE Transactions on Smart Grid.

Review of low voltage load forecasting: Methods, applications, and recommendations

Georgios Giasemidis, Stephen Haben, Siddharth Arora, 2021, Applied Energy.

A Peak Reduction Scheduling Algorithm for Storage Devices on the Low Voltage Network

Matthew Rowe, William Holderbaum, Timur Yunusov, 2014, IEEE Transactions on Smart Grid.

The Real-Time Optimisation of DNO Owned Storage Devices on the LV Network for Peak Reduction

Matthew Rowe, William Holderbaum, Timur Yunusov, 2014 .

Long term individual load forecast under different electrical vehicles uptake scenarios

Danica Vukadinovic Greetham, Stephen Haben, Tamsin E. Lee, 2015 .

Probabilistic Day-Ahead Wholesale Price Forecast: A Case Study in Great Britain

Stephen Haben, Julien Caudron, Jake Verma, 2021, Forecasting.

Short term load forecasting and the effect of temperature at the low voltage level

Georgios Giasemidis, Florian Ziel, Stephen Haben, 2019, International Journal of Forecasting.

Short Term Load Forecasts of Low Voltage Demand and the Effects of Weather

Georgios Giasemidis, Florian Ziel, Stephen Haben, 2018, 1804.02955.

A hybrid model of kernel density estimation and quantile regression for GEFCom2014 probabilistic load forecasting

Georgios Giasemidis, Stephen Haben, S. Haben, 2016, 1610.05183.

Day-ahead industrial load forecasting for electric RTG cranes

V. Becerra, W. Holderbaum, William HOLDERBAUM, 2018 .

Electric vehicles and low-voltage grid: impact of uncontrolled demand side response

Danica Vukadinovic Greetham, Laura Hattam, Stephen Haben, 2017 .

A genetic algorithm approach for modelling low voltage network demands

Peter Grindrod, Georgios Giasemidis, Stephen Haben, 2016, 1612.06833.

Conditioning of the 3DVAR Data Assimilation Problem

N. Nichols, A. Lawless, S. Haben, 2009 .

Impacts of building load dispersion level on its load forecasting accuracy: Data or algorithms? Importance of reliability and interpretability in machine learning

D. Wallom, B. Stephen, S. Haben, 2023, Energy and Buildings.

Dirichlet Sampled Capacity and Loss Estimation for LV Distribution Networks With Partial Observability

Bruce Stephen, Rory Telford, Stephen Haben, 2020, IEEE Transactions on Power Delivery.

Modelling the Electricity Consumption of Small to Medium Enterprises

P. Grindrod, T. E. Lee, S. A. Haben, 2014 .

Mathematical solutions for electricity networks in a low carbon future

Matthew Rowe, Peter Grindrod, William Holderbaum, 2013 .

The conditioning of least‐squares problems in variational data assimilation

Sarah L. Dance, Amos S. Lawless, Joanne A. Waller, 2018, Numer. Linear Algebra Appl..

Day-ahead industrial load forecasting for electric RTG cranes

V. Becerra, W. Holderbaum, S. Haben, 2018 .

Modelling the demand and uncertainty of low voltage networks and the effect of non-domestic consumers

Georgios Giasemidis, Stephen Haben, S. Haben, 2018, Sustainable Energy, Grids and Networks.

Stochastic optimal energy management system for RTG cranes network using genetic algorithm and ensemble forecasts

William Holderbaum, Feras Alasali, Stephen Haben, 2019, Journal of Energy Storage.