Multiobjective optimal operations for an interprovincial hydropower system considering peak-shaving demands

Jianjian Shen, Chuntian Cheng, Sen Wang, Xiaoye Yuan, Lifei Sun and Jun Zhang

Renewable and Sustainable Energy Reviews, 2020, vol. 120, issue C

Abstract: Large-scale power transmission in China poses a challenge for the operation of an interprovincial hydropower system (IHS) connected by ultrahigh-voltage direct current (UHVDC) lines. This study develops a multiobjective optimization model for the monthly operation of an IHS considering daily peak-shaving demands. This model is first transformed into a sequence of single-objective subproblems with different peak-to-valley ratio constraints. A multiphase multigroup coordination strategy is proposed in which the plant group for each month is determined based on the hydrological seasons of the different rivers. A multidimensional search method is then utilized to optimize the monthly generation schedules, where the energy target for a typical day is proportional to the daily load share in each month. Finally, a load-reconstruction-based strategy is used to determine feasible hourly generation schedules and obtain the peak-to-valley ratios to evaluate the monthly operation schemes. The above model and method are applied to a real-world IHS related to the Xiluodu-Zhejiang UHVDC power transmission project. The obtained Pareto solutions reveal the interaction between the energy production and peak-shaving objectives and show a significant improvement in peak shaving with a small decrease in energy production. Moreover, in typical inflow scenarios, all operation schemes enhance the total energy generation from local hydropower plants while leaving that from Xiluodu almost unchanged compared with the conventional operation results.

Keywords: Multiobjective; Optimal operation; Interprovincial hydropower system (IHS); Peak shaving; Security constraints (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (15)

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DOI: 10.1016/j.rser.2019.109617

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