Medium-term optimization of pumped hydro storage with stochastic intrastage subproblems

TL;DR

This paper develops a medium-term optimization framework for pumped hydro storage that incorporates detailed short-term flexibility through stochastic intrastage subproblems, comparing three different modeling approaches.

Contribution

It introduces a novel decomposition method with multi-stage stochastic intrastage subproblems for detailed flexibility modeling in hydro storage optimization.

Findings

The stochastic intrastage approach outperforms deterministic methods in revenue generation.

Different flexibility modeling approaches significantly impact operational strategies.

The method effectively captures short-term variability in a realistic hydro power plant setting.

Abstract

This paper presents a medium-term self-scheduling optimization of pumped hydro storage power plants with detailed consideration of short-term flexibility. A decomposition of the problem into inter- and intrastage subproblems, where the intrastage problems themselves are formulated as multi-stage stochastic programs, allows the detailed consideration of short- term flexibility. The method is presented together with three alter- native approaches, where the short-term flexibility is considered differently: (1) with aggregated peak and off-peak prices, (2) with price duration curves and (3) with deterministic intrastage subproblems. The methods are compared and evaluated in a Monte Carlo operation simulation study. The study is performed on a realistic hydro power plant with consideration of revenue from ancillary services.