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Decomposition method for optimizing long-term multi-area energy production with heat and power storages

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  • Abdollahi, Elnaz
  • Lahdelma, Risto

Abstract

To achieve efficient transition towards climate and energy framework targets, improvement in energy efficiency is important. This paper presents a model for long-term multi-area combined heat and power production with heat and power storages, and power transmission between areas. Assuming fixed unit commitment, the model minimizes total production and transmission cost. The model can in principle be solved as a linear programming model. However, energy storages impose dynamic constraints to the model, making the long-term model very large and slow to solve. To speed up solution and to allow larger models to be solved, we develop a novel decomposition method that solves three kinds of smaller sub-models iteratively. The method is validated by comparing it with the integrated linear programming model using realistic demand data generated by a forecasting model. The method produces near-optimal solutions within three iterations. The decomposition method can also solve larger models much faster than the integrated model.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:appene:v:260:y:2020:i:c:s0306261919320197
    DOI: 10.1016/j.apenergy.2019.114332
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    2. Wakui, Tetsuya & Akai, Kazuki & Yokoyama, Ryohei, 2022. "Shrinking and receding horizon approaches for long-term operational planning of energy storage and supply systems," Energy, Elsevier, vol. 239(PD).
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    6. Du, Sipeng & Wu, Di & Dai, Zhong & Li, Guiqiang & Lahaxibai, Shala, 2023. "Regional collaborative planning equipped with shared energy storage under multi-time scale rolling optimisation method," Energy, Elsevier, vol. 277(C).

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