Characterizing the Hydraulic Connection of Cascade Reservoirs for Short-Term Generation Dispatching via Gaussian Process Regression

• Main Authors: Xiao Chen, Jianzhong Zhou, Benjun Jia, Xin Yang, Chao Zhou
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Cascade reservoirs; short-term generation dispatching; hour-scale hydraulic connection; Gaussian process regression
• Online Access: https://ieeexplore.ieee.org/document/9130681/

The characterization of the mapping relationship (MR) between outflow of the upstream reservoir (OUR) and inflow of the downstream reservoir (IDR) in the short-term generation dispatching of cascade reservoirs (SGDCR) greatly impacts the safe and economic operation of hydropower plants. If this MR is not characterized properly, the operation process of hydropower stations will deviate from the planning dispatching schemes. Especially when the upstream reservoir (UR) undertakes peak load regulation tasks frequently and the downstream reservoir (DR) owns weak re-regulation capacity, the safety of cascade reservoirs will be seriously threatened. In this extreme system, the commonest characterizing models in SGDCR, such as the lag time (LT) model and the Muskingum model, may cause a huge deviation when simulating or forecasting the IDR. Given this dilemma, the Gaussian process regression (GPR) model, which is a representative for Bayesian regression methods, is firstly introduced to handle this MR and compared with the LT and the Muskingum model in this paper. The Three Gorges-Gezhouba cascade reservoirs (TGGCR) in China are selected as a typical case study. The performance indicators of four categories are adopted to evaluate the simulated IDR in a single period and a set of pivotal indicators are proposed to estimate the simulation dispatching in multiple periods. The results show that (1) The GPR model reduces the mean absolute deviation (MAD) about inflow of Gezhouba by 197m³/s and 263m³/s than the LT and the Muskingum model respectively; (2) The distribution characteristics of inflow deviation produced by the GPR model are most competitive. Meanwhile, the GPR model has the strongest ability when conducting the multi-period simulation dispatching and owns best applicability on the whole range of streamflow. (3) The Muskingum model is not recommended to characterize the hour-scale hydraulic connection in the extreme system of SGDCR.