Resumo:
Renewable sources of energy will take a greater share of the electricity
generation mix in order to minimize the dependence on fossil fuels and the
emission of CO2. The insertion of those sources in the power systems have
called the attention of regulator organs, as well as planners and operators – not
only because it represent an important structural change, but also because of
the introduction of a high number of random variables and complexities in the
generation and transmission systems, due to flotation capacity of renewable
sources.
Bearing in mind the fragility of deterministic criteria to work with randomness
involved in power systems, the adoption of probabilistic approaches become
crucial for a correct definition of reserve requirements in systems with high
penetration of renewable energy. However, the probabilistic models are not still
easily accepted. In order to reduce the rejection in relation to probabilistic
techniques, a new methodology called Well-Being Analysis was developed,
which combines the robustness of probabilistic approaches with the
deterministic planners’ perception. This technique, by further classifying the
success states in healthy and marginal, allows the identification of how distant
from the failure region the system operates.
This dissertation presents a new methodology, based on the sequential Monte
Carlo simulation model, to evaluate the reserve requirements of generating
systems with high penetration of renewable energy. The main objective is to
analyze the behavior of the traditional and Well-Being indices, when the
penetration level assumes significant values, no matter if it is from hydraulic or
wind sources. The application of the proposed methodology is illustrated
through case studies carried out using configurations of the Portuguese
generating system.
