追蹤
Stephen Haben
Stephen Haben
在 maths.ox.ac.uk 的電子郵件地址已通過驗證 - 首頁
標題
引用次數
引用次數
年份
Analysis and clustering of residential customers energy behavioral demand using smart meter data
S Haben, C Singleton, P Grindrod
IEEE Transactions on Smart Grid 7 (1), 136-144, 2016
4342016
A new error measure for forecasts of household-level, high resolution electrical energy consumption
S Haben, J Ward, D Vukadinovic Greetham, C Singleton, P Grindrod
International Journal of Forecasting 30 (2), 246-256, 2014
1782014
Review of Low-Voltage Load Forecasting: Methods, Applications, and Recommendations
S Haben, S Arora, G Giasemidis, M Voss, DV Greetham
Applied Energy 304, 2021
1172021
Short term load forecasting and the effect of temperature at the low voltage level
S Haben, G Giasemidis, F Ziel, S Arora
International Journal of Forecasting, 2019
1012019
A hybrid model of kernel density estimation and quantile regression for GEFCom2014 probabilistic load forecasting
S Haben, G Giasemidis
International Journal of Forecasting 32 (3), 1017-1022, 2016
812016
A peak reduction scheduling algorithm for storage devices on the low voltage network
M Rowe, T Yunusov, S Haben, C Singleton, W Holderbaum, B Potter
IEEE Transactions on Smart Grid 5 (4), 2115-2124, 2014
742014
The Real-Time Optimisation of DNO Owned Storage Devices on the LV Network for Peak Reduction
M Rowe, T Yunusov, S Haben, W Holderbaum, B Potter
Energies 7 (6), 3537-3560, 2014
702014
Conditioning of incremental variational data assimilation, with application to the Met Office system
SA Haben, AS Lawless, NK Nichols
Tellus A: Dynamic Meteorology and Oceanography 63 (4), 782-792, 2011
682011
Conditioning and preconditioning of the variational data assimilation problem
SA Haben, AS Lawless, NK Nichols
Computers & Fluids 46 (1), 252-256, 2011
542011
Energy management systems for a network of electrified cranes with energy storage
F Alasali, S Haben, W Holderbaum
International Journal of Electrical Power & Energy Systems 106, 210-222, 2019
452019
Day-ahead industrial load forecasting for electric RTG cranes
F Alasali, S Haben, V Becerra, W Holderbaum
Journal of Modern Power Systems and Clean Energy 6 (2), 223-234, 2018
402018
Long term individual load forecast under different electrical vehicles uptake scenarios
A Poghosyan, DV Greetham, S Haben, T Lee
Applied Energy 157, 699-709, 2015
342015
Conditioning and preconditioning of the minimisation problem in variational data assimilation
SA Haben
PhD thesis, Department of Mathematics and Statistics, University of Reading, 2011
322011
The conditioning of least‐squares problems in variational data assimilation
JM Tabeart, SL Dance, SA Haben, AS Lawless, NK Nichols, JA Waller
Numerical Linear Algebra with Applications 25 (5), e2165, 2018
312018
Optimal Energy Management and MPC Strategies for Electrified RTG Cranes with Energy Storage Systems
F Alasali, S Haben, V Becerra, W Holderbaum
Energies 10 (10), 1598, 2017
312017
A genetic algorithm approach for modelling low voltage network demands
G Giasemidis, S Haben, T Lee, C Singleton, P Grindrod
Applied Energy 203, 463-473, 2017
232017
Stochastic optimal energy management system for RTG cranes network using genetic algorithm and ensemble forecasts
F Alasali, S Haben, W Holderbaum
Journal of Energy Storage 24, 100759, 2019
212019
Analysis of RTG crane load demand and short-term load forecasting
F Alasali, S Haben, V Becerra, W Holderbaum
Int J Comput Commun Instrumen Eng 3 (2), 448-454, 2016
192016
Conditioning of the 3DVAR data assimilation problem
SA Haben, AS Lawless, NK Nichols
University of Reading, Dept. of Mathematics, Math Report Series 3, 2009, 2009
172009
Core Concepts and Methods in Load Forecasting: With Applications in Distribution Networks
S Haben, M Voss, W Holderbaum
Springer Nature, 2023
162023
系統目前無法執行作業,請稍後再試。
文章 1–20