Abstract
This thesis studies the long-term operation of price-taker peak hydropower plants associated
to reservoirs and subject to minimum flows and maximum ramping rates that sell energy in
day-ahead electricity markets. The thesis is organised in five chapters and two appendixes.
The first chapter is an introduction of the above-mentioned issue. It aims to provide both
an overview as well as a mathematical description of the addressed problem and define the
scope and objectives of the thesis.
The second chapter shows a review of the literature related to the main topics tackled in
the thesis, such as the principal approaches of reservoir decision support tools, the optimisation
techniques most used in hydro scheduling, the main procedures for the characterisation
of the involved random inputs and the methods most employed to estimate the generation
characteristic of a peak hydropower plant. Furthermore, the chapter also presents a brief description
of the hydro scheduling models that have considered minimum flows and maximum
ramping rates jointly.
The third and the fourth chapters are devoted to the achievement of the thesis objectives
and are divided in several studies. Among the main contributions cointaned in these studies
can be found different long-term optimisation models for hydropeaking subject to minimum
flows and maximum ramping rates, several sensitivity analyses of the long-term effects of
these constraints on certain economical and operational aspects of a peak hydropower plant,
a set of formulae for the approximate assessment of the long-term economic impact caused
by these constraints on this type of plants, and the introduction of a new concept in hydro
scheduling: flow value.
The fith chapter sets out the conclusions of the thesis which can be summarised as follows.
On the one hand, the presence of minimum flows in hydropeaking increases the spillage
volume and the water value, whereas decreases the generated energy, the number of start-ups
and shut-downs of the hydro units, the plant capability for price tracking and the revenue.
On the other hand, the presence of maximum ramping rates, in turn, increases the number of
plant operating hours, the spillage volume, and, in the driest weeks, the flow value, whereas
decreases the number of start-ups and shut-downs of the hydro units, the plant capability for
price tracking, the revenue, the water value, and, in the wettest weeks, the flow value.
The appendix A contains the equations involved in the developed optimisation models and
the appendix B provides a summary of the main data of the case studies considered in the
third and fourth chapters. Finally, both the cited references and the applied nomenclature
can be found at the end of the thesis.
