| 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 | 356 | 2016 |
| 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 | 138 | 2014 |
| 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 | 70 | 2014 |
| 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 | 67 | 2016 |
| 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 | 63 | 2019 |
| 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 | 63 | 2014 |
| 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 | 60 | 2011 |
| Conditioning and preconditioning of the variational data assimilation problem SA Haben, AS Lawless, NK Nichols Computers & Fluids 46 (1), 252-256, 2011 | 50 | 2011 |
| 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 | 36 | 2019 |
| Review of Low-Voltage Load Forecasting: Methods, Applications, and Recommendations S Haben, S Arora, G Giasemidis, M Voss, DV Greetham Applied Energy 304, 2021 | 33 | 2021 |
| 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 | 31 | 2015 |
| 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 | 29 | 2018 |
| 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 | 28 | 2017 |
| Conditioning and preconditioning of the minimisation problem in variational data assimilation SA Haben PhD thesis, Department of Mathematics and Statistics, University of Reading, 2011 | 28 | 2011 |
| 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 | 24 | 2018 |
| 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 | 19 | 2017 |
| 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 | 18 | 2019 |
| 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 | 17 | 2009 |
| 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 | 14 | 2016 |
| Modelling the electricity consumption of small to medium enterprises TE Lee, SA Haben, P Grindrod Progress in Industrial Mathematics at ECMI 2014 18, 341-349, 2016 | 12 | 2016 |
Colin SingletonCountingLabZweryfikowany adres z countinglab.co.uk
