Abstract
In the short-term operation of the power generation of cascade reservoirs, uncertainty factors such as inflow forecast errors could cause various types of risks. The inflow to a downstream reservoir is not only affected by inflow forecast errors from upstream reservoirs but also the forecast errors associated with inflow to the stream segment between the reservoirs, such as from a tributary. The inflow forecast errors of different forecast periods may also be correlated. To address this multivariate problem, the inflow forecast error variables were jointly fitted in this study using the Gaussian mixture model (GMM) and a t-Copula function based on the analysis of the error distribution characteristics in different forecast periods. Therefore, a stochastic model that coupled with the GMM and t-Copula to calculate inflow forecast errors in multiple forecast periods was established. Furthermore, according to the simulation results of the stochastic model and the predicted runoff series, a set of simulated runoff processes were obtained. Then they were combined with the existing power generation plan to carry out the risk analysis for short-term operation of the power generation in a cascade reservoir. The approach was evaluated using the Jinguan cascade hydropower system within the Yalong River basin as a case study. For this case study, the risk analysis for short-term operation of the power generation was analyzed based on stochastic simulation of the inflow forecast errors; the results show the feasibility and effectiveness of the proposed methods.
Highlights
The accuracy of inflow forecasts is crucial to the formulation of plans for short-term operation of the power generation from cascade reservoirs [1,2]
These indicate that the methodology proposed in this study can effectively describe the statistical characteristics of the inflow forecast error series and provides a reference value for short-term operation of the power generation in large cascade reservoirs
From the aspect of risk rate, the hydropower generation plan usually takes the forecast runoff as the input data directly, without considering the inflow forecast errors, which leads to the risk and failure of the generation plan
Summary
The accuracy of inflow forecasts is crucial to the formulation of plans for short-term operation of the power generation from cascade reservoirs [1,2]. Forecast inflow is often directly used to formulate operation schemes for short-term operation of the power generation in cascade reservoirs. Forecasted inflow does not currently consider the influence of various uncertainty factors which may cause risks of insufficient output, wasted water and beyond-or-below-reservoir limit water levels, because of deviations between the actual and predicted inflow. The optimal operation schemes cannot be currently applied directly to actual power generation processes [6]. The risk analysis for short-term operation of the power generation in complex reservoirs is needed to reduce power and economic losses
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