The uncertainties in system and model parameters arising from the volatility of market, weather and operating conditions pose a major challenge to the optimal short-term operation of cascaded hydropower systems. The dynamic operating environment resulting from the fluctuating parameters greatly impacts the scheduling of power generation and generating unit commitment in such systems. This article focuses on the development and implementation a novel rolling horizon robust online scheduling framework that utilizes stochastic optimization within a model-based feedback scheme to tackle the uncertainties in electricity prices, electric power demands, water inflows and plant model parameters. The efficacy of this approach is demonstrated through application to a variety of case studies for different types of uncertainty. Case studies demonstrate significant improvements in system performance with the proposed strategy, in terms of system economics and constraint satisfaction, over schedules generated without feedback or use of a nominal online scheduling scheme.

市场，天气和运行条件的波动性导致系统和模型参数的不确定性，对梯级水电系统的最佳短期运行提出了重大挑战。由波动的参数产生的动态操作环境极大地影响了这种系统中发电的调度和发电单元的投入。本文着重于开发和实现一种新颖的滚动式稳健在线调度框架，该框架利用基于模型的反馈方案中的随机优化来解决电价，电力需求，水流入和工厂模型参数的不确定性。通过针对各种类型的不确定性应用到各种案例研究中，证明了这种方法的有效性。