JournalR. Tawn, J. Browell, and I.A. Dinwoodie, "Missing Data in Wind Farm Time Series: Properties and Effect on Forecasts," Electric Power Systems Research (PSCC 2020 Special Issue), vol. 189, December 2020, 106640, 2020, (DOI, pre-print)
J.W. Messner, P. Pinson, J. Browell, M.B. Bjerregard and I. Schicker, "Evaluation of Wind Power Forecasts – An up-to-date view," Wind Energy, 23:1461-1481, 2020, (available online, pre-print) C. Gilbert, J. Browell and D. McMillan, "Leveraging Turbine-level Data for Improved Probabilistic Wind Power Forecasting," IEEE Transactions on Sustainable Energy, vol. 11, no. 3, pp. 1152-1160, 2020, (open access) M. Nedd, J. Browell, K. Bell and C. Booth, "Containing Loss Risk in a Low Inertia GB Power System," IEEE Transactions on Industry Applications, vol. 6, no. 2, 1031-1039, 2020, (available online, pre-print) C. Sweeney, R.J. Bessa, J. Browell and P. Pinson, "The Future of Forecasting for Renewable Energy," WIREs Energy and Environment, vol. 9, no. 2, 2020, (pre-print, available online) C. Edmunds, S.M. Martinez, J. Browell, E. Gómez-Lázaro and S. Galloway, "The evolution of wind power participation in reserve and response markets in Great Britain and Spain," Renewable and Sustainable Energy Reviews, vol. 115, November 2019, 109360, (available online, pre-print) J. Browell, "Risk Constrained Trading Strategies for Stochastic Generation with a Single-Price Balancing Market," Energies, 11(6):1345, 2018, (open access) J. Browell, D. R. Drew and K. Philippopoulos, "Improved Very Short-term Spatio-temporal Wind Forecasting using Atmospheric Regimes," Wind Energy, vol. 21, no. 11, pp. 968-979, 2018, (open access) R. J. Bessa, C. Möhrlen, V. Fundel, M. Siefert, J. Browell, S. H. El Gaidi, B-M. S. Hodge, U. Cali, (2017), "Towards Improved Understanding of the Applicability of Uncertainty Forecasts in Wind Energy," Energies, 10(9):1402, 2017, (open access) A. Malvaldi, S. Weiss, D. Infield, J. Browell, P. Leahy and A. Foley, "A spatial and temporal correlation analysis of aggregate wind power in an ideally interconnected Europe," Wind Energy, vol. 20, no. 8, pp. 1315–1329, 2017, (open access) L. Cavalcante, R. J. Bessa, M. Reis and J. Browell, "Sparse Structures for Very Short-term Wind Power Forecasting," Wind Energy, vol. 20, no. 4, pp. 657-675, 2017, (pre-print, DOI) J. Dowell and P. Pinson, "Very-short-term Probabilistic Wind Power Forecasts by Sparse Vector Autoregression," IEEE Transactions on Smart Grid, vol. 7, no. 2, pp. 763-770, 2016, (pre-print, DOI) V. M. Catterson, D. McMillan, I. Dinwoodie, M. Revie, J. Dowell, J. Quigley and K. Wilson, "An economic impact metric for evaluating wave height forecasters for offshore wind maintenance access," Wind Energy, vol. 29, issue 2, pp. 199-212, February 2016 In Book and ReportsM. Nedd, J. Browell, A. Egea-Alvarez, K. Bell, R. Hamilton, S. Wang, and S. Brush, “Operating a zero-carbon GB power system: implications for Scotland,” University of Strathclyde, report commissioned by ClimateXChange, 2020 (DOI)
IEA Wind Task 36, "Recommended Practices for the Implementation of Wind Power Forecasting Solutions," Edited by, and Contributions from, C. Möhrlen, J Browel, et al., 2019 R. Bessa, J. Dowell, P. Pinson, Chapter: Renewable Energy Forecasting in "Smart Grid Handbook," Chen-Ching Liu, Stephen McArthur, Seung-Jae Lee (eds), Wiley, June 2016 ConferenceJ. Browell, C. Gilbert, R. Tawn, L. May, "Quantile combination for the EEM Wind Power Forecasting Competition", invited paper, European Energy Market Conference, 2020, (pre-print, DOI)
J. Browell and C. Gilbert, "ProbCast: Open-source Production, Evaluation and Visualisation of Probabilistic Forecasts," Probabilistic Methods Applied to Power Systems Conference, 2020, (pre-print, DOI) C. Gilbert, J. Browell and D. McMillan, "A data-driven vessel motion model for offshore access forecasting", IEEE OCEANS, Marseille, DOI, 2019 C. Möhrlen, J. Lerner, J.W. Messner, J. Browell, A. Tuohy, J. Zack, C. Collier, G. Giebel, (2018), "IEA Wind Recommended Practices for the Implementation of Wind Power Forecasting Solutions Part 2 and 3: Designing and executing forecasting benchmarks and evaluation of forecast solutions," Wind Integration Workshop, Stockholm, Sweden, 2018 C. Gilbert, J. Browell and D. McMillan, "A Hierarchical Approach to Probabilistic Wind Power Forecasting," Probabilistic Methods Applied to Power Systems (PMAPS), Boise, Idaho, 2018 J. Browell and C. Gilbert, "Cluster-based Regime-switching AR for the EEM Wind Power Forecasting Competiton," 14th International Conference on the European Energy Market (EEM), Dresden, Germany, 2017. Invited Paper. Code and Data J. Browell, C. Gilbert and D. McMillan, "Use of Turbine Level Data for Improved Wind Power Forecasting," IEEE PowerTech Conference, Manchester, UK, 2017 J. Dowell, I. Dinwoodie and D. McMillan, "Forecasting for Offshore Maintenance Scheduling under Uncertainty," European Safety and Reliability Conference, Glasgow, UK, 2016 J. Dowell, G. Hawker, K. Bell and S. Gill, "Review of Probabilistic Methods of Defining Reserve Requirements," IEEE Power and Energy Society General Meeting, Boston, MA, 2016 Important copyright note:
Please note that some of these materials have been copyrighted by the journals and conference proceedings in which these papers originally appeared. According to the copyright conditions, these documents are being made available in this site by the authors in response to requests of other researchers for personal use only, and cannot be distributed by the end-users. |
My Google Scholar Profile
University Profile
|
|
|