A Carryover Storage Valuation Framework for Medium-Term Cascaded Hydropower Planning: A Portland General Electric System Study

TL;DR

This paper introduces a new framework for quantifying the future value of carryover storage in medium-term cascaded hydropower planning, enhancing the optimization of reservoir management for better power generation outcomes.

Contribution

The paper develops a novel framework that accurately quantifies the future value of carryover storage and integrates it into planning models using analytical rules and linear constraints.

Findings

Framework effectively determines proper carryover storage values.

Numerical results demonstrate improved planning accuracy.

Framework offers valuable insights for hydropower operators.

Abstract

Medium-term planning of cascaded hydropower (CHP) determines appropriate carryover storage levels in reservoirs to optimize the usage of available water resources. This optimization seeks to maximize the hydropower generated in the current period (i.e., immediate benefit) plus the potential hydropower generation in the future period (i.e., future value). Thus, in the medium-term CHP planning, properly quantifying the future value deposited in carryover storage is essential to achieve a balanced trade-off between immediate benefit and future value. To this end, this paper presents a framework to quantify the future value of carryover storage, which consists of three major steps: i) constructing a model to calculate the maximum possible hydropower generation that a given level of carryover storage can deliver in the future period; ii) extracting the implicit locational marginal water value (LMWV) of carryover storage for each reservoir by applying a partition-then-extract algorithm to the constructed model; and iii) developing a set of analytical rules based on the extracted LMWV to effectively calculate the future value. These rules can be seamlessly integrated into medium-term CHP planning models as tractable mixed-integer linear constraints to quantify the future value properly, and can be easily visualized to offer valuable insights for CHP operators. Finally, numerical results on a CHP system of Portland General Electric demonstrate the effectiveness of the presented framework in determining proper carryover storage values to facilitate medium-term CHP planning.