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An effective heuristic for combined heat-and-power production planning with power ramp constraints

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  • Rong, Aiying
  • Lahdelma, Risto

Abstract

Combined heat-and-power (CHP) production is an increasingly important technology for its efficient utilization of primary-energy resources and for reducing CO2 emissions. In the CHP plant, the generation of heat-and-power follows a joint characteristic, which makes the determination of both the marginal power production cost (MPPC) and the feasible operating region for the plant more complicated than for the power-only generation plant. Due to the interdependence between heat and power production, the power-ramp constraints, which limit how much the power production of a CHP plant may increase or decrease between two successive periods, may also imply constraints on the heat production. In this paper, we investigate the impact of power-ramp constraints on CHP production planning and develop a robust heuristic for dealing with the power-ramp constraints based on the solution to the problem with relaxed ramp-constraints (RRC). Numerical results based on realistic production models show that the heuristic can generate high-quality solutions efficiently.

Suggested Citation

  • Rong, Aiying & Lahdelma, Risto, 2007. "An effective heuristic for combined heat-and-power production planning with power ramp constraints," Applied Energy, Elsevier, vol. 84(3), pages 307-325, March.
    • Handle: RePEc:eee:appene:v:84:y:2007:i:3:p:307-325
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    References listed on IDEAS

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    1. Makkonen, Simo & Lahdelma, Risto, 2006. "Non-convex power plant modelling in energy optimisation," European Journal of Operational Research, Elsevier, vol. 171(3), pages 1113-1126, June.
    2. 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.
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    9. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
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    13. Sadeghian, H.R. & Ardehali, M.M., 2016. "A novel approach for optimal economic dispatch scheduling of integrated combined heat and power systems for maximum economic profit and minimum environmental emissions based on Benders decomposition," Energy, Elsevier, vol. 102(C), pages 10-23.
    14. Rong, Aiying & Lahdelma, Risto & Luh, Peter B., 2008. "Lagrangian relaxation based algorithm for trigeneration planning with storages," European Journal of Operational Research, Elsevier, vol. 188(1), pages 240-257, July.
    15. Jin, Jingliang & Zhou, Peng & Li, Chenyu & Bai, Yang & Wen, Qinglan, 2020. "Optimization of power dispatching strategies integrating management attitudes with low carbon factors," Renewable Energy, Elsevier, vol. 155(C), pages 555-568.
    16. Bazmi, Aqeel Ahmed & Zahedi, Gholamreza, 2011. "Sustainable energy systems: Role of optimization modeling techniques in power generation and supply—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(8), pages 3480-3500.
    17. 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.
    18. 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).
    19. Jin, Jingliang & Zhou, Dequn & Zhou, Peng & Qian, Shuqu & Zhang, Mingming, 2016. "Dispatching strategies for coordinating environmental awareness and risk perception in wind power integrated system," Energy, Elsevier, vol. 106(C), pages 453-463.
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