In Preparation/SubmittedT. Shen, J. Browell, D. Castro-Camilo, "Adaptive Bayesian Very Short-Term Wind Power Forecasting Based on the Generalised Logit Transformation", (arXiv, submitted)
G. Dantas, J. Browell, "Large-scale, seamless probabilistic wind power forecasting", (arXiv, submitted) J. Browell, S. Haglund, H. Kälvegren, R.J. Bessa, D.W. Van der Meer, "The Hybrid Energy Forecasting and Trading Competition 2024: Results and learnings", (submitted) K. Stylpnopoulos, J. Browell, J. Illian, C. Gilbert, W. Jones, "Intra-day imbalance price forecasting leveraging continuous trade data", (submitted) M. Maia, D. Castro-Camilo, J. Browell, "Probabilistic forecasting of weather-driven faults on electricity distribution networks", (working paper) JournalM. J. Schneider, J. Browell, R. Rankin, "Limiting Extreme Behavior in Forecasting Competitions", Foresight, issue 75, 2024 (PDF, online (subscription required))
V. Gioia, M. Fasiolo, J. Browell, R. Bellio, "Additive covariance models: modelling regional electricity net-demand in Great Britain", Journal of the American Statistical Association, 2024, (accepted) (arXiv, Data and Code, WESC23 slides) J. de Vilmarest, J. Browell, M. Fasiolo, Y. Goude and O. Wintenberger, "Adaptive Probabilistic Forecasting of Electricity (Net-)Load", IEEE Transactions on Power Systems, vol. 39, no. 2, pp. 4154-4163, 2024, (DOI, arXiv) D.L. Donaldson, J. Browell, C. Gilbert, "Predicting the magnitude and timing of peak electricity demand: A competition case study", IET Smart Grid, 7(4), 473-484, 2024, (DOI) B. Rostami-Tabar, J. Browell and I. Svetunkov, "Probabilistic forecasting of hourly Emergency Department arrivals", Health Systems, 13(2), 133-149, 2023, (DOI) M. Hu, B. Stephen, J. Browell, S. Haben, D. Wallom, "Impacts of building load dispersion level on its load forecasting accuracy: Data or algorithms? Importance of reliability and interpretability in machine learning", Energy and Buildings, vol. 285, 2023, (DOI) C. Gilbert, J. Browell and B. Stephen, "Probabilistic load forecasting for the low voltage network: forecast combination and daily peaks", Sustainable Energy Grids and Networks, vol. 34, 2023 (DOI, arXiv, Data and Code) D. Huppmann, J. Browell, B.Nastasi, Z. Vale, D. Süsser, "Editorial: A research agenda for open energy science: Opportunities and perspectives of the F1000Research Energy Gateway", F1000Research, 11:896, 2022 (DOI) M. T. Craig, J. Wohland, L. P. Stoop, A. Kies, B. Pickering H. C. Bloomfield, J. Browell and co-authors, "Overcoming the disconnect between energy system and climate modeling", Joule, 6(7), pp. 1405-1417, 2022, (DOI) C. Kang, J. Browell and co authors, "Editorial: Special Section on COVID-19 Impact on Electrical Grid Operation: Analysis and Mitigation", IEEE Open Access Journal of Power and Energy, vol. 9, pp. 183-184, 2022, (DOI) J. Browell and C. Gilbert, "Predicting electricity imbalance prices and volumes: capability and opportunity", Energies, 15(10), 3645, 2022, (DOI) R. Tawn, J. Browell, and D McMillan, "Sub-seasonal-to-Seasonal forecasting for wind turbine maintenance scheduling", Wind, 2(2), 260-287, 2022, (DOI) J. Browell, C. Gilbert and M. Fasiolo, "Covariance Structures for High-dimensional Energy Forecasting", Electric Power Systems Research (Special Issue for PSCC 2022), (DOI, PSCC slides, WESC slides) M. Farrokhabadi, J. Browell, Y. Wang, S. Makonin, W. Su, and H. Zareipour, "Day-Ahead Electricity Demand Forecasting Competition: Post-COVID Paradigm", IEEE Open Access Journal of Power and Energy, vol. 9, pp. 185-191, 2022 (DOI) R.M. Graham, J. Browell, D. Bertram and C.J. White, "The application of sub-seasonal to seasonal (S2S) predictions for hydropower forecasting", Meteorological Applications, 29(1), e2047, 2022, (DOI) E. Heylen, J. Browell and F. Teng, "Probabilistic day-ahead inertia forecasting", IEEE Transactions on Power Systems, vol. 37, no. 5, 3738-3746, 2022, (DOI, pre-print) C.J. White, R.M. Graham, J. Browell et al., "Advances in the application and utility of subseasonal-to-seasonal predictions", Bulletin of the American Meteorological Society, 103, E1448–E1472, 2022, (DOI) F. Petropoulos, J. Browell, et al., "Forecasting: theory and practice", International Journal of Forecasting, vol. 38, no. 3, pp. 705-871, 2022, (DOI) R. Tawn and J. Browell, "A review of very short-term wind and solar power forecasting", Renewable and Sustainable Energy Reviews, vol. 153, 111758, 2022 (pre-print, DOI) J. Browell and M. Fasiolo, "Probabilistic Forecasting of regional net-load with conditional extremes and gridded NWP", IEEE Transactions on Smart Grid, vol. 12, no. 6, pp. 5011-5019, 2021, (DOI, arXiv), [data and code] [Recorded presentation from EVA2021] E. Medina-Lopez, D. McMillan, J. Lazic, E. Hart, S. Zen, A. Angeloudis, E. Bannon, J. Browell, S. Dorling, R.M. Dorrell, R. Foster, C. Old, G.S. Payne, G. Porter, A.S. Rabaenda, B. Sellar, E. Tapoglou, N. Trifonova, I.H. Woodhouse, and A. Zampollo, "Satellite data for the offshore renewable Energy sector: synergies and innovation opportunities", Remote Sensing of Environment, vol. 264, 2021 112588, (DOI, arXiv) H.C. Bloomfield, P.L.M. Gonzalez, J.K. Lundquist, L.P. Laurens, J. Browell, R. Dargaville, M. De Felice, K. Gruber, A. Hilbers, A. Kies, M. Panteli, H.E. Thornton, J. Wohland, M. Zeyringer and D.J. Brayshaw, "The importance of weather and climate to energy systems: A workshop on Next Generation Challenges in Energy-Climate Modelling", Bulletin of the American Meteorological Society, 102(1), E159-E167, (open access) R. Telford, B. Stephen, J Browell and S. Haben, "Dirichlet Sampled Capacity and Loss Estimation for LV Distribution Networks with Partial Observability", IEEE Transaction on Power Delivery, vol. 36, no. 5, pp. 2676-2686, Oct. 2021, (pre-print, DOI) C. Gilbert, J. Browell and D. McMillan, "Probabilistic Access Forecasting for Improved Offshore Operations", International Journal of Forecasting, vol. 37, no. 1, pp. 134-150, 2021, (open access) In BookContributions to Parts 2 and 3 by J. Browell, Eds. C. Möhrlen , J. W. Zack, G. Giebel, IEA Wind Recommended Practice for the Implementation of Renewable Energy Forecasting Solutions, Academic Press, 270 pages, ISBN: 0443186812, 2022
ConferenceG. Giebel, C. Draxl2, H. Frank, J. Zack, C. Möhrlen, G. Kariniotakis, J. Browell, R. Bessa, and D. Lenaghan, "Forecasting for the Weather Driven Energy System – A new Task under IEA Wind", Wind & Solar Integration Workshop, 2022, (pre-print)
SlidesPast, present, and future of renewable energy forecasting, MetDesk Winter 23/24 Forecast Symposium, London, 10 October 2023
Dynamic covariance models for wind and net-demand forecasting, Wind Energy Science Conference, Glasgow, 2023 Important copyright note:
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