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An improved unit decommitment algorithm for combined heat and power systems

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  • Rong, Aiying
  • Lahdelma, Risto
  • Grunow, Martin

Abstract

This paper addresses the unit commitment in multi-period combined heat and power (CHP) production planning, considering the possibility to trade power on the spot market. In CHP plants (units), generation of heat and power follows joint characteristics, which means that production planning for both heat and power must be done in coordination. We present an improved unit decommitment (IUD) algorithm that starts with an improved initial solution with less heat surplus so that the relative cost-efficiency of the plants can be determined more accurately. Then the subsequent decommitment procedures can decommit (switch off) the least cost-efficient plants properly. The improved initial solution for the committed plants is generated by a heuristic procedure. The heuristic procedure utilizes both the Lagrangian relaxation principle that relaxes the system-wide (heat and power) demand constraints and a linear relaxation of the ON/OFF states of the plants. We compare the IUD algorithm with realistic test data against a generic unit decommitment (UD) algorithm. Numerical results show that IUD is an overall improvement of UD. The solution quality of IUD is better than that of UD for almost all of tested cases. The maximum improvement is 11.3% and the maximum degradation is only 0.04% (only two sub-cases out of 216 sub-cases) with an average improvement of 0.3-0.5% for different planning horizons. Moreover, IUD is more efficient (1.1-3 times faster on average) than UD.

Suggested Citation

  • Rong, Aiying & Lahdelma, Risto & Grunow, Martin, 2009. "An improved unit decommitment algorithm for combined heat and power systems," European Journal of Operational Research, Elsevier, vol. 195(2), pages 552-562, June.
    • Handle: RePEc:eee:ejores:v:195:y:2009:i:2:p:552-562
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    References listed on IDEAS

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    1. Rong, Aiying & Lahdelma, Risto, 2007. "Efficient algorithms for combined heat and power production planning under the deregulated electricity market," European Journal of Operational Research, Elsevier, vol. 176(2), pages 1219-1245, January.
    2. Rong, Aiying & Lahdelma, Risto, 2007. "An efficient envelope-based Branch and Bound algorithm for non-convex combined heat and power production planning," European Journal of Operational Research, Elsevier, vol. 183(1), pages 412-431, November.
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    5. Rong, Aiying & Lahdelma, Risto, 2005. "An efficient linear programming model and optimization algorithm for trigeneration," Applied Energy, Elsevier, vol. 82(1), pages 40-63, September.
    6. Rong, Aiying & Hakonen, Henri & Lahdelma, Risto, 2006. "An efficient linear model and optimisation algorithm for multi-site combined heat and power production," European Journal of Operational Research, Elsevier, vol. 168(2), pages 612-632, January.
    7. Thorin, Eva & Brand, Heike & Weber, Christoph, 2005. "Long-term optimization of cogeneration systems in a competitive market environment," Applied Energy, Elsevier, vol. 81(2), pages 152-169, June.
    8. Lahdelma, Risto & Hakonen, Henri, 2003. "An efficient linear programming algorithm for combined heat and power production," European Journal of Operational Research, Elsevier, vol. 148(1), pages 141-151, July.
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    Cited by:

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    2. Marshman, D.J. & Chmelyk, T. & Sidhu, M.S. & Gopaluni, R.B. & Dumont, G.A., 2010. "Energy optimization in a pulp and paper mill cogeneration facility," Applied Energy, Elsevier, vol. 87(11), pages 3514-3525, November.
    3. Alipour, Manijeh & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2016. "Optimal risk-constrained participation of industrial cogeneration systems in the day-ahead energy markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 421-432.
    4. Rong, Aiying & Lahdelma, Risto, 2017. "An efficient model and algorithm for the transmission-constrained multi-site combined heat and power system," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1106-1117.
    5. Fan, Lei & Pan, Kai & Guan, Yongpei, 2019. "A strengthened mixed-integer linear programming formulation for combined-cycle units," European Journal of Operational Research, Elsevier, vol. 275(3), pages 865-881.
    6. Abdollahi, Elnaz & Wang, Haichao & Lahdelma, Risto, 2019. "Parametric optimization of long-term multi-area heat and power production with power storage," Applied Energy, Elsevier, vol. 235(C), pages 802-812.
    7. Abdollahi, Elnaz & Lahdelma, Risto, 2020. "Decomposition method for optimizing long-term multi-area energy production with heat and power storages," Applied Energy, Elsevier, vol. 260(C).
    8. Helin, Kristo & Käki, Anssi & Zakeri, Behnam & Lahdelma, Risto & Syri, Sanna, 2017. "Economic potential of industrial demand side management in pulp and paper industry," Energy, Elsevier, vol. 141(C), pages 1681-1694.
    9. Kumbartzky, Nadine & Schacht, Matthias & Schulz, Katrin & Werners, Brigitte, 2017. "Optimal operation of a CHP plant participating in the German electricity balancing and day-ahead spot market," European Journal of Operational Research, Elsevier, vol. 261(1), pages 390-404.
    10. Hamdi Abdi, 2023. "A Survey of Combined Heat and Power-Based Unit Commitment Problem: Optimization Algorithms, Case Studies, Challenges, and Future Directions," Mathematics, MDPI, vol. 11(19), pages 1-36, October.
    11. Santos, Maria Izabel & Uturbey, Wadaed, 2018. "A practical model for energy dispatch in cogeneration plants," Energy, Elsevier, vol. 151(C), pages 144-159.
    12. Fang, Tingting & Lahdelma, Risto, 2016. "Optimization of combined heat and power production with heat storage based on sliding time window method," Applied Energy, Elsevier, vol. 162(C), pages 723-732.

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