Robust online scheduling for optimal short-term operation of cascaded hydropower systems under uncertainty. (February 2021)

• Record Type: Journal Article
• Authors: Mathur, Pulkit; Swartz, Christopher L.E.; Zyngier, Danielle; Welt, Francois
• Is Part Of: Journal of process control. Volume 98(2021)
• Page Start: 52
• Page End: 65
• Publication Date: 2021-02
• Subjects: Robust online scheduling -- Rolling horizon -- Hydropower systems -- Uncertainty; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2020.12.005
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract: 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. Highlights: Novel scheme for robust online scheduling of cascaded hydropower systems. Both continuous and discrete decisions modeled within robust scheduling framework. Uncertainty management through stochastic optimization and feedback. Uncertainty in electricity prices, demands, inflows and model parameters mitigated. Comparison of performance between nominal and robust online scheduling strategies.