IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v36y2008i7p2439-2448.html
   My bibliography  Save this article

Restriction techniques for the unit-commitment problem with total procurement costs

Author

Listed:
  • Kaleta, Mariusz
  • Toczylowski, Eugeniusz

Abstract

Many discrete optimization problems may be solved much easier, if the solution space can be restricted in a convenient way. For a given specific problem, the restriction techniques can be helpful if an available optimization solver, perceived as a black box, is capable of solving quickly only reduced subproblems of a limited size. For the family of hard unit-commitment problems we investigate a hierarchical search algorithm, which is based on decomposition of the problem into two subproblems. The upper-level subproblem is a relatively small decision "kernel" of the problem that can be solved approximately by a search algorithm. We define an appropriate restricted decision space for this subproblem. The lower-level subproblem is an appropriate restriction of the original problem that can be solved efficiently by a dedicated solver. Our approach was analyzed on a set of historical data from the Polish electrical balancing market and the best known solutions were improved by the average of about 2-5%.

Suggested Citation

  • Kaleta, Mariusz & Toczylowski, Eugeniusz, 2008. "Restriction techniques for the unit-commitment problem with total procurement costs," Energy Policy, Elsevier, vol. 36(7), pages 2439-2448, July.
  • Handle: RePEc:eee:enepol:v:36:y:2008:i:7:p:2439-2448
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301-4215(08)00057-8
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. John A. Muckstadt & Sherri A. Koenig, 1977. "An Application of Lagrangian Relaxation to Scheduling in Power-Generation Systems," Operations Research, INFORMS, vol. 25(3), pages 387-403, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jorge Antunes & Luis Alberiko Gil-Alana & Rossana Riccardi & Yong Tan & Peter Wanke, 2022. "Unveiling endogeneity and temporal dependence in energy prices and demand in Iberian countries: a stochastic hidden Markov model approach," Annals of Operations Research, Springer, vol. 313(1), pages 191-229, June.
    2. Emanuel Canelas & Tânia Pinto-Varela & Bartosz Sawik, 2020. "Electricity Portfolio Optimization for Large Consumers: Iberian Electricity Market Case Study," Energies, MDPI, vol. 13(9), pages 1-21, May.
    3. Maximilian Borning & Larissa Doré & Michael Wolff & Julian Walter & Tristan Becker & Grit Walther & Albert Moser, 2020. "Opportunities and Challenges of Flexible Electricity-Based Fuel Production for the European Power System," Sustainability, MDPI, vol. 12(23), pages 1-26, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Payal Mitra & Soumendu Sarkar & Tarun Mehta & Atul Kumar, 2022. "Unit Commitment in a Federalized Power Market: A Mixed Integer Programming Approach," Working papers 323, Centre for Development Economics, Delhi School of Economics.
    2. Dong, Jizhe & Li, Yuanhan & Zuo, Shi & Wu, Xiaomei & Zhang, Zuyao & Du, Jiang, 2023. "An intraperiod arbitrary ramping-rate changing model in unit commitment," Energy, Elsevier, vol. 284(C).
    3. Ramteen Sioshansi and Ashlin Tignor, 2012. "Do Centrally Committed Electricity Markets Provide Useful Price Signals?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    4. Johnson, Raymond B. & Oren, Shmuel S. & Svoboda, Alva J., 1997. "Equity and efficiency of unit commitment in competitive electricity markets," Utilities Policy, Elsevier, vol. 6(1), pages 9-19, March.
    5. L. A. C. Roque & D. B. M. M. Fontes & F. A. C. C. Fontes, 2014. "A hybrid biased random key genetic algorithm approach for the unit commitment problem," Journal of Combinatorial Optimization, Springer, vol. 28(1), pages 140-166, July.
    6. Heejung Park, 2022. "A Unit Commitment Model Considering Feasibility of Operating Reserves under Stochastic Optimization Framework," Energies, MDPI, vol. 15(17), pages 1-22, August.
    7. Maturana, Jorge & Riff, Maria-Cristina, 2007. "Solving the short-term electrical generation scheduling problem by an adaptive evolutionary approach," European Journal of Operational Research, Elsevier, vol. 179(3), pages 677-691, June.
    8. Richter, Lucas & Lehna, Malte & Marchand, Sophie & Scholz, Christoph & Dreher, Alexander & Klaiber, Stefan & Lenk, Steve, 2022. "Artificial Intelligence for Electricity Supply Chain automation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    9. Steeger, Gregory & Rebennack, Steffen, 2017. "Dynamic convexification within nested Benders decomposition using Lagrangian relaxation: An application to the strategic bidding problem," European Journal of Operational Research, Elsevier, vol. 257(2), pages 669-686.
    10. Feng, Chenjia & Shao, Chengcheng & Wang, Xifan, 2021. "CSP clustering in unit commitment for power system production cost modeling," Renewable Energy, Elsevier, vol. 168(C), pages 1217-1228.
    11. C. L. Tseng & C. A. Li & S. S. Oren, 2000. "Solving the Unit Commitment Problem by a Unit Decommitment Method," Journal of Optimization Theory and Applications, Springer, vol. 105(3), pages 707-730, June.
    12. Samer Takriti & Benedikt Krasenbrink & Lilian S.-Y. Wu, 2000. "Incorporating Fuel Constraints and Electricity Spot Prices into the Stochastic Unit Commitment Problem," Operations Research, INFORMS, vol. 48(2), pages 268-280, April.
    13. Dotzauer, Erik, 2003. "Experiences in mid-term planning of district heating systems," Energy, Elsevier, vol. 28(15), pages 1545-1555.
    14. Claude Lemaréchal, 2007. "The omnipresence of Lagrange," Annals of Operations Research, Springer, vol. 153(1), pages 9-27, September.
    15. Yau, Sheena & Kwon, Roy H. & Scott Rogers, J. & Wu, Desheng, 2011. "Financial and operational decisions in the electricity sector: Contract portfolio optimization with the conditional value-at-risk criterion," International Journal of Production Economics, Elsevier, vol. 134(1), pages 67-77, November.
    16. Briest, Gordon & Lauven, Lars-Peter & Kupfer, Stefan & Lukas, Elmar, 2022. "Leaving well-worn paths: Reversal of the investment-uncertainty relationship and flexible biogas plant operation," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1162-1176.
    17. Samer Takriti & John R. Birge, 2000. "Lagrangian Solution Techniques and Bounds for Loosely Coupled Mixed-Integer Stochastic Programs," Operations Research, INFORMS, vol. 48(1), pages 91-98, February.
    18. Fattahi, Salar & Ashraphijuo, Morteza & Lavaei, Javad & Atamtürk, Alper, 2017. "Conic relaxations of the unit commitment problem," Energy, Elsevier, vol. 134(C), pages 1079-1095.
    19. Marshall L. Fisher, 2004. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 50(12_supple), pages 1861-1871, December.
    20. Raymond B. Johnson & Alva J. Svoboda & Claudia Greif & Ali Vojdani & Fulin Zhuang, 1998. "Positioning for a Competitive Electric Industry with PG&E's Hydro-Thermal Optimization Model," Interfaces, INFORMS, vol. 28(1), pages 53-74, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:36:y:2008:i:7:p:2439-2448. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.