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A novel data-driven tighten-constraint method for wind-hydro hybrid power system to improve day-ahead plan performance in real-time operation

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  • Lai, Chunyang
  • Kazemtabrizi, Behzad

Abstract

Complementary operation has been proven an effective way to handle the increasing levels of renewable energy sources (RESs) integration into the grid. However, due to the relative higher levels of forecast uncertainty associated with RESs outputs, when the hybrid power system operates according to the day-ahead plan in real-time operation, the performance of the system may deviate significantly from the initial expectation in the day-ahead plan. Few research works gauge the effectiveness of the day-ahead plan from the perspective of real-time operation, which inadvertently makes this problem under explored. To handle this problem, in this study, using the wind-hydro hybrid power system (WHHPS) as an example, a novel tighten-constraint method is proposed to guarantee the effectiveness of the day-ahead plan in real-time operation. First, the conventional day-ahead planning model and the real-time operation model are proposed to guide the operation of the WHHPS. Second, considering the lack of connection between day-ahead planning and real-time operation in current research, a novel metric, i.e. Reliability, denoted by R, is proposed to evaluate the performance of the day-ahead plan from the perspective of real-time operation given inherent prediction errors of wind power. Third, a data-driven tighten-constraint method is proposed by introducing an adjustment parameter, denoted by λ, to improve the reliability of the day-ahead plan and eventually guarantee the effectiveness of the day-ahead plan from the perspective of real-time operation. Finally, a bilevel Stackelberg model is proposed and reformulated to calculate the adjustment parameter and the whole procedure of using the proposed method is clarified. The effectiveness of the proposed method is tested and verified through a series of case studies at the end of this paper. The results show that (1) the proposed method can improve the reliability of the day-ahead plan under different reservoir status; (2) the proposed method can guarantee a high reliability level of the day-ahead plan without adding any additional computation burden; (3) improving the prediction precision of the adjustment parameter can enhance the efficiency of resource utilization for power generation; (4) over time, the increase in available historical data can enhance prediction accuracy of adjustment parameter and improve the effectiveness of the proposed method even further.

Suggested Citation

  • Lai, Chunyang & Kazemtabrizi, Behzad, 2024. "A novel data-driven tighten-constraint method for wind-hydro hybrid power system to improve day-ahead plan performance in real-time operation," Applied Energy, Elsevier, vol. 371(C).
    • Handle: RePEc:eee:appene:v:371:y:2024:i:c:s0306261924009991
    DOI: 10.1016/j.apenergy.2024.123616
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