Juan Miguel Morales

Juan Miguel Morales

Full professor

Publications

You can also find my articles on my Google Scholar profile.

Journal Papers:

  1. S. Pineda, J. Pérez-Ruiz, J. M. Morales (2025). Beyond the Neural Fog: Interpretable Learning for AC Optimal Power Flow. IEEE Transactions on Power Systems (preprint)
  2. J.G. De la Varga, S. Pineda, J.M. Morales, Á. Porras (2025). Learning-based Improvement in State Estimation for Unobservable Systems. Electric Power System Research 241:111268 (preprint, published)
  3. A. Stratigakos, S. Pineda, J.M. Morales (2025). Decision-focused linear pooling for probabilistic forecast combination. International Journal of Forecasting (preprint, published)
  4. A. Porras, L. Roald, J. M. Morales, S. Pineda (2025). Unifying Chance-Constrained and Robust Optimal Power Flow for Resilient Network Operations. IEEE Transactions on Control of Network Systems (preprint, published)
  5. R. Mieth, J. M. Morales, H. V. Poor (2025). Data Valuation from Data-driven Optimization. IEEE Transactions on Control of Network Systems (preprint, published)
  6. C. Domínguez, R. Gázquez, J. M. Morales, S. Pineda (2024). The Cooperative Maximal Covering Location Problem with ordered partial attractions. Computers & Operations Research 170: 106782 (preprint, published open access)
  7. S. Pineda, J. M. Morales, A. Porras, C. Domínguez (2024). Tight Big-Ms for Optimal Transmission Switching. Electric Power Systems Research, 234:110620  (preprint, published open access)
  8. S. Pineda, J. M. Morales and A. Jiménez-Cordero (2024). Learning‑assisted optimization for transmission switching. TOP 32:489-516 (preprint, published open access)
  9. Z. Li, A. M. Alonso, A. Elías and J. M. Morales (2024). Clustering and forecasting of day-ahead electricity supply curve using a market-based distance. International Journal of Electric Power & Energy Systems, 158: 109977  (preprint, published)
  10. A. Stratigakos, S. Pineda, J. M. Morales and G. Kariniotakis (2023). Interpretable Machine Learning for DC Optimal Power Flow with Feasibility Guarantees. IEEE Transactions on Power Systems 39(3):5126-5137 (preprint, published)
  11. Á. Porras, C. Domínguez, J.M. Morales and S. Pineda (2023). Tight and compact sample average approximation for joint chance constrained optimal power flow. INFORMS Journal on Computing 35(6):1454-1469   (published open access)
  12. J. M. Morales, M. A. Muñoz, S. Pineda (2023). Prescribing net demand for electricity market clearing. Operations Research Perspectives, 10: 100268 (published open access)
  13. A. Esteban-Pérez and J. M. Morales (2023).  Distributionally Robust Optimal Power Flow with Contextual Information. European Journal of Operational Research 306(3):1047-1058  (preprint, published open access)
  14. A. Elías, J. M. Morales and S. Pineda (2023). A high dimensional functional time series approach to evolution outlier detection for grouped smart meters. Quality Engineering 35(3):371-387 (published open access)
  15. A. Porras, S. Pineda, J. M. Morales, A. Jiménez-Cordero (2023). Cost-driven screening of network constraints for the unit commitment problem. IEEE Transactions on Power Systems 38(1):42-51 (preprint, published)
  16. A. Jiménez-Cordero, J. M. Morales and S. Pineda (2022). Warm-starting constraint generation for mixed-integer optimization: A Machine Learning approach. Knowledge-Based Systems, 253:109570 (published open access)
  17. S. Pineda, J. M. Morales (2022). Is learning for the unit commitment problem a low-hanging fruit? Electric Power System Research 207: 107851 (preprint, published open access)
  18. M. A. Muñoz, S. Pineda, J.M. Morales (2022). A bilevel framework for decision-making under uncertainty with contextual information. OMEGA,108: 102575 (published open access, preprint).
  19. A. Esteban-Pérez and J. M. Morales (2022). Distributionally robust stochastic programs with side information based on trimmings. Mathematical Programming 195: 1069-1105, https://doi.org/10.1007/s10107-021-01724-0. (published open access).
  20. J. M. Morales, S. Pineda, Y. Dvorkin (2021). Learning the price response of active distribution networks for TSO-DSO coordination. IEEE Transactions on Power Systems, DOI:10.1109/TPWRS.2021.3127343. (published open access, arXiv).
  21. V. Bucarey, M. Labbé, J. M. Morales, S. Pineda (2021). An exact dynamic programming approach to segmented isotonic regression.  OMEGA, 105:102516 (published, preprint).
  22. A. Esteban-Pérez and J. M. Morales (2021). Partition-based Distributionally Robust Optimization via optimal transport with order cone constraints. 4OR, https://doi.org/10.1007/s10288-021-00484-z.
  23. R. Fernández-Blanco, J. M. Morales, S.Pineda and Á. Porras (2021). Inverse optimization with kernel regression: Application to the power forecasting and bidding of a fleet of electric vehicles. Computers & Operations Research, 134, https://doi.org/10.1016/j.cor.2021.105405.
  24. R. Fernández-Blanco, J. M. Morales, S.Pineda (2021).  Forecasting the price-response of a pool of buildings via homothetic inverse optimization. Applied Energy, 290: 116791, https://doi.org/10.1016/j.apenergy.2021.116791 (published, arXiv).
  25. M. Gržanić, J. M. Morales, S. Pineda, T. Capuder (2021).  Electricity cost sharing in energy communities under dynamic pricing and uncertainty. IEEE Access (published).
  26. A. Jiménez-Cordero, J. M. Morales and S. Pineda (2021). A novel embedded min-max approach for feature selection in nonlinear support vector machine classification, European Journal of Operational Research, 293(1):24-35 (published, arXiv).
  27. Á. Porras, R. Fernández-Blanco, J. M. Morales and S. Pineda (2020). An Efficient Robust Approach to the Day-ahead Operation of an Aggregator of Electric Vehicles , IEEE Transactions on Smart Grid, 11(6): 4960-4970 , DOI:10.1109/TSG.2020.3004268 (published, arXiv).
  28. D. Guericke, I. Blanco, J. M. Morales and H. Madsen (2020). A two-phase stochastic programming approach to biomass supply planning for combined heat and power plants,  OR Spectrum, 42:863–900, https://doi.org/10.1007/s00291-020-00593-x  (published).
  29. S. Pineda, J. M. Morales and A. Jiménez-Cordero (2020). Data-Driven Screening of Network Constraints for Unit Commitment, IEEE Transactions on Power Systems, 35(5): 3695-3705 ,DOI: 10.1109/TPWRS.2020.2980212  (published) .
  30. M. Á. Muñoz, J. M. Morales and S. Pineda (2020). Feature-driven Improvement of Renewable Energy Forecasting and Trading. IEEE Transactions on Power Systems, 35(5): 3753-3763, DOI: 10.1109/TPWRS.2020.2975246
  31. G. De Zotti, S. A. Pourmousavi, J. M. Morales, H. Madsen and N. K. Poulsen (2020). A Control-based Method to Meet TSO and DSO Ancillary Services Needs by Flexible End-users. IEEE Transactions on Power Systems, 35(3):1868-1880,  DOI: 10.1109/TPWRS.2019.2951623
  32. S. Pineda, R. Fernández-Blanco and J. M. Morales (2019). Time-adaptive Unit Commitment. IEEE Transactions on Power Systems, 34(5): 3869-3878.
  33. S. Pineda and J. M. Morales (2019). Solving linear bilevel problems using Big-Ms: Not all that glitters is gold. IEEE Transactions on Power Systems, 34(3): 2469-2471.
  34. C. Ordoudis, P. Pinson, and J. M. Morales (2019). An Integrated Market for Electricity and Natural Gas Systems with Stochastic Power Producers. European Journal of Operational Research, 272(2):642- 654.
  35. N. Mazzi, A. Trivella and J. M. Morales (2019). Enabling active/passive electricity trading in dual-price balancing markets. IEEE Transactions on Power Systems, 34(3): 1980-1990.
  36. G. De Zotti, S. A. Pourmousavi, J. M. Morales, H. Madsen and N. K. Poulsen (2019). Consumers’ flexibility estimation at the TSO level for balancing services. IEEE Transactions on Power Systems, 34(3): 1918-1930.
  37. K. Dächert, S. Siddiqui, J. Saez-Gallego, S. Gabriel and J. M. Morales (2019). A bicriteria perspective on L-Penalty Approaches - A corrigendum to Siddiqui and Gabriel’s L-Penalty Approach for Solving MPECs. Networks and Spatial Economics, 19(4): 1199-1214.
  38. V. Dvorkin, S. Delikaraoglou and J. M. Morales (2019). Setting reserve requirements to approximate the efficiency of the stochastic dispatch. IEEE Transactions on Power Systems, 34(2): 1524-1536.
  39. C. Lima, S. Relvas, A. Barbosa-P ovoa, J. M. Morales (2019). Adjustable robust optimization for planning logistics operations in downstream oil networks. Processes 7(8):507-537
  40. S. Pineda and J. M. Morales (2018). Chronological time-period clustering for optimal capacity expansion planning with storage. IEEE Transactions on Power Systems, 33(6):7162-7170.
  41. S. Pineda, H. Bylling and J. M. Morales (2018). Efficiently solving linear bilevel programming problems using off -the-shelf optimization software. Optimization and Engineering, 19(1):187-211.
  42. J. Saez-Gallego and J. M. Morales (2018). Short-term forecasting of price-responsive loads using inverse optimization. IEEE Transactions on Smart Grid, 9(5):4805-4814.
  43. J. Saez-Gallego, M Kohansal, A Sadeghi-Mobarakeh and J.M. Morales (2018). Optimal price-energy demand bids for aggregate price-responsive loads. IEEE Transactions on Smart Grid, 9(5):5005-5013.
  44. C. Zhang, Q. Wang, J. Wang, J. M. Morales, P. Pinson, and Jacob Østergaard (2018). Real-time procurement strategies of a proactive distribution company with aggregator-based demand response. IEEE Transactions on Smart Grid, 9(2):766-776.
  45. I. Blanco and J.M. Morales (2017). An efficient robust solution to the two-stage stochastic unit commitment problem. IEEE Transactions on Power Systems, 32(5):4477-4488.
  46. J.M. Morales and S. Pineda (2017). On the inefficiency of the merit order in forward electricity markets with uncertain supply. European Journal of Operational Research, 261(2):789–799 (published).
  47. E. B. Iversen, J.M. Morales,  J. K. Møller, P.-J. Trombe, H. Madsen (2017). Leveraging stochastic differential equations for probabilistic forecasting of wind power using a dynamic power curve, Wind Energy, 20(1):33-44.
  48. E. B. Iversen,  J. K. Møller, J.M. Morales, H. Madsen (2017). Inhomogeneous Markov models for describing driving patterns, IEEE Transactions on Smart Grid, 8(2):581-588
  49. M. Zugno, J.M. Morales, H. Madsen (2016). Commitment and dispatch of heat and power units via affinely adjustable robust optimization. Computers & Operations Research, 75:191–201
  50. B. Bach, J. Werling, T. Ommen, M. Münster,  J.M. Morales, B. Elmegaard (2016). Integration of large-scale heat pumps in the district heating systems of Greater Copenhagen, Energy, 107:321–334.
  51. J. Saez-Gallego, J.M. Morales, M. Zugno, H. Madsen (2016). A data-driven bidding model for a cluster of price-responsive consumers of electricity. IEEE Transactions on Power Systems, 31(6):5001-5011.
  52. 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):5061-5070.
  53. S. Pineda, J.M. Morales (2016). Capacity expansion of stochastic power generation under two-stage electricity markets, Computers & Operations Research, 70:101-114 (published)
  54. E. B. Iversen, J.M. Morales, J. K. Møller, H. Madsen (2016). Short-term probabilistic forecasting of wind speed using stochastic differential equations. International Journal of Forecasting (Special Issue on Probabilistic Energy Forecasting), 32(3):981-990  (published)
  55. S. Pineda, J.M. Morales, T. K. Boomsma (2016). Impact of forecast errors on expansion planning of power systems with a renewables target. European Journal of Operational Research, 248(3):1113-1122  (published)
  56. M. G. Nielsen, J.M. Morales, M. Zugno, T. E. Pedersen, H. Madsen (2016). Economic valuation of heat pumps and electric boilers in the Danish energy system. Applied Energy, 167:189-200  (published)
  57. A. Hellmers, M. Zugno, A. Skajaa, J.M. Morales (2016). Operational strategies for a portfolio of wind farms and CHP plants in a two-price balancing market. IEEE Transactions on Power Systems, 31(3):2182-2191. (published)
  58. M. Zugno, J. M. Morales, H. Madsen (2015). Decision support tools for electricity retailers, wind power and CHP plants using probabilistic forecasts. Special Issue of International Journal of Sustainable Energy Planning and Management, 7:19-36
  59. Y. Hu, J.M. Morales, S. Pineda, M. J. Sanchez, P. Solana (2015). Dynamic multi-stage dispatch of isolated wind-diesel power systems. Energy Conversion and Management, 103: 605-615  (published)
  60. A. Skajaa, K. Edlund, J.M. Morales (2015). Intraday trading of wind energy. IEEE Transactions on Power Systems, 30(6):3181-3189  (published).
  61. J. Saez-Gallego, J.M. Morales, H. Madsen, T. Jonsson (2014). Determining reserve requirements in DK1 area of Nord Pool using a probabilistic approach. Energy, 74:682-693 (published)
  62. S. Pineda, J. M. Morales, Y. Ding, J. Østergaard (2014). Impact of equipment failures and wind correlation on generation expansion planning. Electric Power Systems Research, 116:451-458 (published)
  63. E. B. Iversen, J.M. Morales, H. Madsen (2014). Optimal charging of an electric vehicle using a Markov decision process. Applied Energy, 123:1-12 (published)
  64. E. B. Iversen, J.M. Morales, J. K. Møller, H. Madsen (2014). Probabilistic forecasts of solar irradiance by stochastic differential equations. Environmetrics, 25(3):152-164 (published)
  65. J. M. Morales, M. Zugno, S. Pineda, P. Pinson (2014). Electricity Market Clearing With Improved Scheduling of Stochastic Production. European Journal of Operational Research, 235(3):765-774 (published)
  66. J. M. Morales, M. Zugno, S. Pineda, P. Pinson (2014). Redefining the Merit Order of Stochastic Generation in Forward Markets. IEEE Transactions on Power Systems, 29(2):992-993 (published)
  67. M. Zugno, J. M. Morales, P. Pinson, H. Madsen (2013). Pool strategy of a price-maker wind power producer. IEEE Transactions on Power Systems 28(3):3440-3450 (published)
  68. H. Pandžić, J. M. Morales, A. J. Conejo, I. Kuzle (2013). Offering model for a virtual power plant based on stochastic programming. Applied Energy 105: 282-292 (published)
  69. M. Zugno, J. M. Morales, P. Pinson, H. Madsen (2013). A bilevel model for energy retailers participation in a demand response market environment. Energy Economics 36:182-197 (published)
  70. J. M. Morales, A. J. Conejo, K. Liu, J. Zhong (2012). Pricing electricity in pools with wind producers. IEEE Transactions on Power Systems 27(3):1366-1376 (published)
  71. J. M. Morales, P. Pinson, H. Madsen (2012). A transmission-cost based model to estimate the amount of market-integrable wind resources. IEEE Transactions on Power Systems 27(2):1060-1069 (published)
  72. M. Rahimiyan, J. M. Morales, A. J. Conejo (2011). Evaluating alternative offering strategies for wind producers in a pool. Applied Energy 88(12):4918-4926 (published)
  73. A. J. Conejo, J. M. Morales, J. A. Martínez (2011). Tools for the analysis and design of distributed resources-Part III: Market Studies. IEEE Transactions on Power Delivery 26(3):1663-1670 (published)
  74. J. M. Morales, A. J. Conejo, J. Pérez-Ruiz (2011). Simulating the impact of wind production on locational marginal prices. IEEE Transactions on Power Systems 26(2):820-828 (published)
  75. A. J. Conejo, J. M. Morales, L. Baringo (2010). Real-time demand response model. IEEE Transactions on Smart Grid 1(3):236-242 (published)
  76. E. Caro, J. M. Morales, A. J. Conejo, R. Mínguez (2010). Calculation of measurement correlations using point estimate. IEEE Transactions on Power Delivery 25(4):2095-2013 (published)
  77. J. M. Morales, L. Baringo, A. J. Conejo, R. Mínguez (2010). Probabilistic power flow with correlated wind sources. IET Generation, Transmission & Distribution 4(5):641-651 (published)
  78. J. M. Morales, R. Mínguez, A. J. Conejo (2010). A methodology to generate statistically dependent wind speed scenarios. Applied Energy 87(3):843-855 (published)
  79. A. J. Conejo, J. Nogales, M. Carrión, J. M. Morales (2010). Electricity pool prices: long-term uncertainty characterization for futures-market trading and risk management. Journal of the Operational Research Society 61(2):235-245 (published)
  80. J. M. Morales, A. J. Conejo, J. Pérez-Ruiz (2010). Short-term trading for a wind power producer. IEEE Transactions on Power Systems 25(1):554-564 (published)
  81. J. M. Morales, A. J. Conejo, J. Pérez-Ruiz (2009). Economic valuation of reserves in power systems with high penetration of wind power. IEEE Transactions on Power Systems 24(2):900-910 (published)
  82. J. M. Morales, S. Pineda, A. J. Conejo, M. Carrión (2009). Scenario reduction for futures market trading in electricity markets. IEEE Transactions on Power Systems 24(2):878-888 (published)
  83. J. Misraji, A. J. Conejo, J.M. Morales (2008). Reserve-constrained economic dispatch: Cost and Payment allocations. Electric Power Systems Research 78(5):919-925 (published)
  84. J. M. Morales, J. Pérez-Ruiz (2007). Point-estimate schemes to solve the probabilistic power flow. IEEE Transactions on Power Systems 22(4):1594-1601 (published)

Current research projects

  1. MSOpt - Mathematical Methods for the Optimization of Decision-making Processes based on Multi-source Data (01/09/2024 - 31/08/2028): Principal Investigator. Funding entity: Spanish Ministry of Innovation and Science (PID2023-148291NB-I00)
  2. DYCON - Data-driven Optimization Under a Dynamic Context (01/09/2021 - 01/02/2025): Principal Investigator. Funding entity: Spanish Ministry of Innovation and Science (PID2020-115460GB-I00)

Past research projects

  1. FlexAnalytics - Advanced Analytics to Empower the Small Flexible Consumers of Electricity (2018-2024): Principal Investigator. Funding entity: The European Research Council (ERC-STG-2017)
  2. Mathematical Optimization Methods for Decision Making Using Contextual Information (23/06/2021 - 31/12/2022): Principal Investigator. Funding entity: Andalusia Regional Government (Council for Economic Transformation, Industry,  Knowledge and Universities) (P20_00153)
  3. PowerMath - Mathematical Methods for Data-driven Power Systems. Principal Investigator. Funding entity: Spanish Research Agency (ENE2017-83775-P)
  4. SAND: Smart Distribution Grid Simulator (2018-2019). Principal Investigator. Funding Entity: Fundación Iberdrola España.
  5. OD^2ES - Decision-Making with Big Data: Applications to Renewable Energy Systems (2017-2019): Principal Investigator. Funding Entity: Universidad de Málaga (Research Funding Program for Young Talented Researchers) (PPIT-UMA-B1-2017/18).
  6. SmartNet -Smart TSO-DSO interaction schemes, market architectures and ICT Solutions for the integration of ancillary services from demand-side management and distributed generation (2016-2018): Leader of work package “Market architectures to integrate ancillary services from distributed energy resources.’’ (website) Funding entity: H2020-EU.
  7. CITIES - Centre for IT-Intelligent Energy Systems in Cities (2014-2019): Leader of work package 7 “Decision Making and Support Systems” (development of decision-making models for the optimal market participation of energy companies in smart cities, given the flexibility and controllability of the loads and production, transmission, storage and conversion resources that form energy companies’ portfolios (website). Funding entity: Danish Strategic Research Council (DSF).
  8. 5s - Future Electricity Markets (2013-2017): Within this project, my research focuses on potential designs for the electricity markets of the future, including new market-clearing mechanisms, demand-side management, economic incentives for capacity investments and adequacy, etc. (website). Funding entity: Danish Strategic Research Council (DSF).

Books

  1. A. J. Conejo, M. Carrión, J.M. Morales (2010). Decision Making Under Uncertainty in Electricity Markets. International Series in Operations Research and Management Science, Springer, New York, US. ISBN: 978-1-4419-7421-1 (info)
  2. J.M. Morales, A. J. Conejo, H. Madsen, P. Pinson, M. Zugno (2014). Integrating Renewables in Electricity Markets - Operational Problems. International Series in Operations Research and Management Science, Springer, New York, US. ISBN: 978-1-4614-9411-9 (info) (You can download the file “scenarios.csv” that is needed to run the GAMS codes of the stochastic and robust energy-reserve dispatch models in Sections 3.2.3 and 3.4 from here)

Chapters in books

  1. C. Domínguez, Á. Porras, S. Pineda, and J. M. Morales (2023). Optimal power flow under uncertainty. Encyclopedia of Electrical and Electronic Power Engineering: 765-776. J. García (ed). Elsevier, Ámsterdam, Países Bajos. ISBN 978-0-128-23211-8.
  2. S. Pineda, J. M. Morales, and S. Wogrin (2023). Mathematical programming for power systems. Encyclopedia of Electrical and Electronic Power Engineering: 722-733. J. García (ed). Elsevier, Ámsterdam, Países Bajos. ISBN 978-0-128-23211-8.
  3. J. M. Morales, S. Pineda, M. Zugno (2015). Market design for future clean electricity systems: Advances based on optimization under uncertainty. Handbook of Clean Energy Systems, Vol. 4: Intelligent Energy Systems, John Wiley & Sons, Chichester, UK.
  4. H. Madsen, J.M. Morales, P.-J. Trombe, G. Giebel, H.E. Jørgensen, P. Pinson (2014). Wind resource assessment and wind power forecasting. In DTU International Energy Report 2014: Wind Energy - Drivers and Barriers for Higher Shares of Wind in the Global Power Generation Mix, H.H. Larsen and L.S. Petersen (eds.), Chapter 10, pp. 72-78 (pdf)
  5. P.E. Morthorst, J.M. Morales, S. Schröder (2014). Wind economics. In DTU International Energy Report 2014: Wind Energy - Drivers and Barriers for Higher Shares of Wind in the Global Power Generation Mix, H.H. Larsen and L.S. Petersen (eds.), Chapter 11, pp. 79-85 (pdf)

Ph.D. Dissertation: Impact on System Economics and Security of a High Penetration of Wind Power, E.T.S. I. Industriales, Universidad de Castilla - La Mancha, December 2010 (pdf)

MSc. Project: Application of Point Estimate Methods to the Probabilistic Power Flow Problem (in Spanish), E.T.S. I. Industriales, Universidad de Málaga, June 2006 (pdf)