2016

Journal Publications

  • Z. Ben Bouallegue, T. Heppelmann, S. Theis, P. Pinson (2016). Generation of scenarios from calibrated ensemble forecasts with a dynamic ensemble copula coupling approach. Monthly Weather Review 31(5), pp. 4737-4750 (arxiv link)
  • M. Xu, P. Pinson, Z. Lu, Y. Qiao, Y. Min (2016). Adaptive robust polynomial regression for power curve modeling with application to wind power forecasting. Wind Energy 19(12), pp. 2321-2336
  • A. Papakonstantinou, P. Pinson (2016). Information uncertainty in electricity markets: Introducing probabilistic offers. IEEE Transactions on Power Systems 31(6), pp. 5202-5203 (pdf)
  • S. Delikaraoglou, J.M. Morales, P. Pinson (2016). Impact of inter- and intra-regional coordination in markets with a large renewable component. IEEE Transactions on Power Systems, 31(6), pp. 5061-5070 (pdf)
  • H. Ding, P. Pinson, Z. Hu, Y. Song (2016). Optimal offering strategies for wind-storage systems based on linear decision rules. IEEE Transactions on Power Systems 31(6), pp. 4755-4764 (pdf)
  • P. Wang. F. Wen, P. Pinson, J. Østergaard (2016). A ranking method for peak load shifting considering different types of data. Journal of Energy Engineering, article no. 04016016.
  • G. He, Q. Chen, C. Kang, P. Pinson, Q. Xia (2016). Optimal bidding strategy of battery storage in power markets considering performance based regulation and battery cycle life. IEEE Transactions on Smart Grid 7(5), pp. 2359-2367 (pdf)
  • F. Golestaneh, P. Pinson, H.B. Gooi (2016). Very short-term nonparametric probabilistic forecasts of renewable energy generation – with application to solar energy. IEEE Transactions on Power Systems 31(5), pp. 3850-3863 (pdf)
  • T. Soares, P. Pinson, T.V. Jensen, H. Morais (2016). Optimal offering strategy for wind power in energy and primary reserve markets. IEEE Transactions on Sustainable Energy 7(3), pp. 1036-1045 (pdf)
  • N. Davis, P. Pinson, A. Hahmann, N.-E. Clausen, M. Zagar (2016). Identifying and characterizing the impact of turbine icing on wind farm power generation. Wind Energy 19(8), pp. 1503-1518
  • P. Pinson (2016). Comment to: Werner Ehm et al., “Of quantiles and expectiles: consistent scoring functions, Choquet representations and forecast rankings”. Journal of the Royal Statistical Society, Series B 78(3), pp. 552-553
  • T. Hong, P. Pinson, S. Fan, H. Zareipour, A. Troccoli, R.J Hyndman (2016). Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond. International Journal of Forecasting 32(3), pp. 896-913 (pdf)
  • L. Exizidis, J. Kazempour, P. Pinson, Z. De Greve, F. Vallée (2016). Sharing wind power forecasts in electricity markets: A numerical analysis. Applied Energy 176, pp. 65-73 (pdf)
  • F. Golestaneh, H.B. Gooi, P. Pinson (2016). Generation and evaluation of space-time trajectories of photovoltaic power. Applied Energy 176, pp. 80-91 (pdf)
  • C. Zhang, Q. Wang, J. Wang, M. Korpås, P. Pinson, J. Østergaard, M.E. Khodayar (2016). Trading strategies for distribution company with stochastic distributed energy resources. Applied Energy 177, pp. 625-635
  • H. Ding, P. Pinson, Z. Hu, Y. Song (2016). Integrated bidding and operation strategies for wind-storage systems. IEEE Transactions on Sustainable Energy 7(1), pp. 163-172 (pdf)
  • J. Dowell, P. Pinson (2016). Very-short-term wind power probabilistic forecasts by sparse vector autoregression. IEEE Transactions on Smart Grid 7(2), pp. 763-770 (pdf)
  • N. O’Connell, P. Pinson, H. Madsen, M. O’Malley (2016). Economic dispatch of demand-side balancing through asymmetric block offers. IEEE Transactions on Power Systems 31(4), pp. 2999-3007 (pdf)
  • W. A. Bukhsh, C. Zhang, P. Pinson (2016). A integrated multiperiod OPF model with demand response and renewable generation uncertainty. IEEE Transactions on Smart Grid 7(3), pp. 1495-1503 (pdf)

Book Chapters

  • R. Bessa, J. Browell, P. Pinson (2016). Renewable Energy Forecasting. In: Smart Grid Handbook (C.-C. Liu, S. McArthur, S.-J. Lee, eds), Chichester, UK: John Wiley & Sons, Ltd, pp. 639-659

Conference Proceedings

  • C. Ordoudis, P. Pinson (2016). Impact of renewable energy forecast imperfections on market-clearing outcomes. IEEE EnergyCon 2016, Leuven, Belgium
  • W. Bukhsh, A. Papakonstantinou, P. Pinson (2016). A robust optimization approach using CVaR for unit commitment in a market with probabilistic offers. IEEE EnergyCon 2016, Leuven, Belgium (pdf)
  • N. Mazzi, P. Pinson (2016). Purely data-driven approaches to trading of renewable energy generation. European Electricity Market, EEM Conference 2016 , Porto, Portugal (pdf)
  • E. Mocanu, P.H. Nguyen, M. Gibescu, E.M. Larsen, P. Pinson (2016). Demand forecasting at low aggregation levels using Factored Conditional Restricted Boltzmann Machine. PSCC 2016, Genoa, Italy (pdf)
  • E.B. Iversen, P. Pinson, I. Arduin (2016). RESGen: Renewable Energy Scenario Generation Platform. IEEE PES General Meeting 2016, Denver, USA (invited) (pdf)
  • P. Pinson (2016). Introducing distributed learning approaches in wind power forecasting. IEEE PMAPS 2016 (Probabilistic Methods Applied to Power Systems), Beijing, China (pdf)
  • S.J. Kazempour, P. Pinson (2016). Effects of risk aversion on market outcomes: A stochastic two-stage equilibrium model. IEEE PMAPS 2016 (Probabilistic Methods Applied to Power Systems), Beijing, China
  • L. Mitridati, P. Pinson (2016). Optimal coupling of heat and electricity systems: A stochastic hierarchical approach. IEEE PMAPS 2016 (Probabilistic Methods Applied to Power Systems), Beijing, China (pdf)
  • A. Papakonstantinou, P. Pinson (2016). Population dynamics for renewables in electricity markets: a minority game view. IEEE PMAPS 2016 (Probabilistic Methods Applied to Power Systems), Beijing, China (pdf)
  • L. Exizidis, J. Kazempour, P. Pinson, Z. De Greve, F. Vallee (2016). Strategic wind power trading considering rival wind power production. ISGT-Asia 2016, Melbourne, Australia

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IEEE Transactions on Power Systems

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