Stochastic Unit Commitment Problem with Security and Emissions Constraints

  • Rui Laia
  • Hugo M. I. Pousinho
  • Rui Melício
  • Victor M. F. Mendes
  • Manuel Collares-Pereira
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 423)


This paper presents a stochastic optimization-based approach for the unit commitment (UC) problem under uncertainty on a deregulated electricity market that includes day-ahead bidding and bilateral contracts. The market uncertainty is modeled via price scenarios so as to find the optimal schedule. An efficient mixed-integer linear program is proposed for the UC problem, considering not only operational constraints including security ones on units, but also emission allowance constraints. Emission allowances are used to mitigate carbon footprint during the operation of units. While security constraints settle on spinning reserve are used to provide reliable bidding strategies. Numerical results from a case study are presented to show the effectiveness of the approach.


Emission allowances stochastic optimization security constraints unit commitment 


  1. 1.
    Li, Y.P., Huang, G.H.: Electric-Power Systems Planning and Greenhouse-Gas Emission Management Under Uncertainty. Energy Conv. Manag. 57, 173–182 (2012)CrossRefGoogle Scholar
  2. 2.
    Wu, L., Shahidehpour, M., Li, T.: Stochastic Security-Constrained Unit Commitment. IEEE Trans. Power Syst. 22(2), 800–811 (2007)CrossRefGoogle Scholar
  3. 3.
    Amjady, N., Nasiri-Rad, H.: Economic Dispatch Using an Efficient Real Coded Genetic Algorithm. IET Gener. Transm. Distrib. 3(3), 266–278 (2009)CrossRefGoogle Scholar
  4. 4.
    Morales-España, G., Latorre, J.M., Ramos, A.: Tight and Compact MILP Formulation of Start-Up and Shut-Down Ramping in Unit Commitment. IEEE Trans. Power Syst. 28(2), 1288–1296 (2013)CrossRefGoogle Scholar
  5. 5.
    Yamin, H., Shahidehpour, M.: Self-Scheduling and Energy Competitive Electricity Markets. Electr. Power Syst. Res. 71(3), 203–209 (2004)CrossRefGoogle Scholar
  6. 6.
    UCTE. Operation handbook: G3 Recommended Secondary Control Reserve (2004)Google Scholar
  7. 7.
    Collective Awareness Platforms for Sustainability and Social Innovation, (accessed October 2013)
  8. 8.
    Senjyu, T., Shimabukuro, K., Uezato, K., Funabashi, T.: A Fast Technique for Unit Commitment Problem by Extended Priority List. IEEE Trans. Power Syst. 18, 882–888 (2003)CrossRefGoogle Scholar
  9. 9.
    Dhillon, J.S., Kothari, D.P.: Economic-Emission Load Dispatch Using Binary Successive Approximation-Based Evolutionary Search. IET Gener. Trans. Distrib. 3(1), 1–16 (2009)CrossRefGoogle Scholar
  10. 10.
    Chandrasekaran, K., Hemamalini, S., Simon, S.P., Padhy, N.: Thermal UC Using Binary/Real Coded Artificial Bee Colony Algorithm. Electr. Power Syst. Res. 84(1), 109–119 (2012)CrossRefGoogle Scholar
  11. 11.
    Dieua, V.N., Ongsakul, W.: Augmented Lagrange Hopfield Network Based Lagrangian Relaxation for Unit Commitment. Int. J. Electr. Power Energy Syst. 33(3), 522–530 (2011)CrossRefGoogle Scholar
  12. 12.
    Ouyang, Z., Shahidehpour, M.: A Hybrid Artificial Neural Network-Dynamic Programming Approach to Unit Commitment. IEEE Trans. Power Syst. 7(1), 236–242 (1992)CrossRefGoogle Scholar
  13. 13.
    Kumar, V.S., Mohan, M.R.: Solution to Security Constrained Unit Commitment Problem Using Genetic Algorithm. Electr. Power Energy Syst. 32(2), 117–125 (2010)CrossRefGoogle Scholar
  14. 14.
    Carrion, M., Arroyo, J.M.: A Computationally Efficient Mixed-Integer Linear Formulation for the Thermal Unit Commitment Problem. IEEE Trans. Power Syst. 21, 1371–1378 (2006)CrossRefGoogle Scholar
  15. 15.
    Ostrowski, J., Anjos, M.F., Vannelli, A.: Tight Mixed-Integer Linear Programming Formulations for the Unit Commitment Problem. IEEE Trans. Power Syst. 27, 39–46 (2012)CrossRefGoogle Scholar
  16. 16.
    Catalão, J.P.S., Pousinho, H.M.I., Mendes, V.M.F.: Short-Term Electricity Prices Forecasting in a Competitive Market by a Hybrid Intelligent Approach. Energy Conv. Manag. 52(2), 1061–1065 (2011)CrossRefGoogle Scholar
  17. 17.
    Thermal Units Data, (accessed October 2013)

Copyright information

© IFIP International Federation for Information Processing 2014

Authors and Affiliations

  • Rui Laia
    • 1
    • 2
  • Hugo M. I. Pousinho
    • 1
    • 2
  • Rui Melício
    • 1
    • 2
  • Victor M. F. Mendes
    • 1
    • 3
  • Manuel Collares-Pereira
    • 1
  1. 1.University of ÉvoraÉvoraPortugal
  2. 2.IDMEC/LAETA, Instituto Superior TécnicoUniversidade de LisboaLisbonPortugal
  3. 3.Instituto Superior of Engenharia de LisboaLisbonPortugal

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