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MILP model for short-term peak shaving of multi-grids using cascade hydropower considering discrete HVDC constraints

Author

Listed:
  • Liao, Shengli
  • Xiong, Jiang
  • Liu, Benxi
  • Cheng, Chuntian
  • Zhou, Binbin
  • Wu, Yuqiang

Abstract

The thriving of high-voltage direct current transmission for hydropower tackles supply-demand imbalances but complicates grids safety, especially concerning the related challenges of varying numbers of hydroelectric units operating, including the effects of discrete rectifier station altering current and vibration zones with minimum numbers of hydroelectric units operating. Here, a mixed integer linear programming model considering high-voltage direct current safety constraints for daily peak-shaving of cascade hydropower plants serving multi-grids is proposed to address these challenges. First, the model integrates the altering current constraint across multiple intervals to ensure stable operation following the passive transition of the direct current terminal into islanded system state. Second, a power distribution strategy considering load differences is adopted to compensate for shortcomings of traditional peak shaving treatments for multiple grids to achieve effective results. Finally, a method for linearizing the segmented vibration zones of hydropower station with minimum numbers of units operating is adopted during model solving to ensure that the model meets safe specifications. The case study indicates that besides guaranteeing the proposed security constraints, the model reduces the average distance by 30.4 % and 30.3 % during the dry and flood seasons, respectively, with better calculation time and variance of the residual load.

Suggested Citation

  • Liao, Shengli & Xiong, Jiang & Liu, Benxi & Cheng, Chuntian & Zhou, Binbin & Wu, Yuqiang, 2024. "MILP model for short-term peak shaving of multi-grids using cascade hydropower considering discrete HVDC constraints," Renewable Energy, Elsevier, vol. 235(C).
  • Handle: RePEc:eee:renene:v:235:y:2024:i:c:s0960148124014095
    DOI: 10.1016/j.renene.2024.121341
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