| A statistical model for hourly large-scale wind and photovoltaic generation in new locations J Ekström, M Koivisto, I Mellin, RJ Millar, M Lehtonen IEEE Transactions on Sustainable Energy 8 (4), 1383-1393, 2017 | 60 | 2017 |
| ePROs in the follow-up of cancer patients treated with immune checkpoint inhibitors: a retrospective study S Iivanainen, T Alanko, K Peltola, T Konkola, J Ekström, H Virtanen, ... Journal of Cancer Research and Clinical Oncology 145, 765-774, 2019 | 43 | 2019 |
| A control framework for the utilization of heating load flexibility in a day-ahead market A Alahäivälä, J Corbishley, J Ekström, J Jokisalo, M Lehtonen Electric Power Systems Research 145, 44-54, 2017 | 43 | 2017 |
| A statistical approach for hourly photovoltaic power generation modeling with generation locations without measured data J Ekström, M Koivisto, J Millar, I Mellin, M Lehtonen Solar Energy 132, 173-187, 2016 | 38 | 2016 |
| Utilising demand response in the future Finnish energy system with increased shares of baseload nuclear power and variable renewable energy V Olkkonen, J Ekström, A Hast, S Syri Energy 164, 204-217, 2018 | 34 | 2018 |
| Assessment of large scale wind power generation with new generation locations without measurement data J Ekström, M Koivisto, I Mellin, J Millar, E Saarijärvi, L Haarla Renewable Energy 83, 362-374, 2015 | 33 | 2015 |
| Wind speed modeling using a vector autoregressive process with a time-dependent intercept term M Koivisto, J Seppänen, I Mellin, J Ekström, J Millar, I Mammarella, ... International Journal of Electrical Power & Energy Systems 77, 91-99, 2016 | 31 | 2016 |
| Sizing hydrogen energy storage in consideration of demand response in highly renewable generation power systems M Ali, J Ekström, M Lehtonen Energies 11 (5), 1113, 2018 | 29 | 2018 |
| A statistical model for comparing future wind power scenarios with varying geographical distribution of installed generation capacity M Koivisto, J Ekström, J Seppänen, I Mellin, J Millar, L Haarla Wind Energy 19 (4), 665-679, 2016 | 26 | 2016 |
| A framework for the assessment of electric heating load flexibility contribution to mitigate severe wind power ramp effects A Alahäivälä, J Ekström, J Jokisalo, M Lehtonen Electric Power Systems Research 142, 268-278, 2017 | 25 | 2017 |
| Follow-up of cancer patients receiving anti-PD-(L) 1 therapy using an electronic patient-reported outcomes tool (KISS): Prospective feasibility cohort study S Iivanainen, T Alanko, P Vihinen, T Konkola, J Ekstrom, H Virtanen, ... JMIR Formative Research 4 (10), e17898, 2020 | 22 | 2020 |
| Electronic patient-reported outcomes and machine learning in predicting immune-related adverse events of immune checkpoint inhibitor therapies S Iivanainen, J Ekstrom, H Virtanen, VV Kataja, JP Koivunen BMC Medical Informatics and Decision Making 21, 1-8, 2021 | 20 | 2021 |
| Minimizing variance in variable renewable energy generation in Northern Europe M Koivisto, N Cutululis, J Ekström 2018 IEEE International Conference on Probabilistic Methods Applied to Power …, 2018 | 17 | 2018 |
| Statistical modeling of aggregated electricity consumption and distributed wind generation in distribution systems using AMR data M Koivisto, M Degefa, M Ali, J Ekström, J Millar, M Lehtonen Electric Power Systems Research 129, 217-226, 2015 | 15 | 2015 |
| Calorimetric system for measurement of synchronous machine losses P Rasilo, J Ekström, A Haavisto, A Belahcen, A Arkkio IET electric power applications 6 (5), 286-294, 2012 | 15 | 2012 |
| A statistical modeling methodology for long-term wind generation and power ramp simulations in new generation locations J Ekström, M Koivisto, I Mellin, RJ Millar, M Lehtonen Energies 11 (9), 2442, 2018 | 13 | 2018 |
| Statistical analysis of large scale wind power generation using Monte Carlo simulations M Koivisto, J Ekström, E Saarijärvi, L Haarla, J Seppänen, I Mellin 2014 Power Systems Computation Conference, 1-7, 2014 | 11 | 2014 |
| A machine learning approach to modelling escalator demand response S Uimonen, T Tukia, J Ekström, ML Siikonen, M Lehtonen Engineering Applications of Artificial Intelligence 90, 103521, 2020 | 10 | 2020 |
| Multi-agent based distributed voltage regulation scheme with grid-tied inverters in active distribution networks A Arshad, J Ekström, M Lehtonen Electric Power Systems Research 160, 180-190, 2018 | 10 | 2018 |
| Assessing the upward demand response potential for mitigating the wind generation curtailment: A case study M Ali, J Ekström, A Alahäivälä, M Lehtonen 2017 14th International Conference on the European Energy Market (EEM), 1-6, 2017 | 10 | 2017 |
