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Hydropower systems can provide two dierent electricity services: base load and peak load generation
or peak load generation only (Egré and Milewski, 2002). The former is often found in regions where
hydropower is abundant, while the latter is found where hydropower complements other energy sources.
In a region where hydropower oers base load and peak load generation, the increase in generation
capacity can be readily seen as bene cial in terms of energy reliability. On the other hand, hydropower
plants are always associated with reservoirs, one of the main causes of social and environmental impacts.
In the last years, hydropower projects have been facing many challenges around the world, frequently
related to public expectations regarding social and environmental performances (Klimpt et al., 2002).
Decision-makers often choose the best set of hydropower plants to be built in a given river or watershed
based on optimization models. These models can be an important tool not only to decide what might
be the best policy, but also to communicate the main stakeholders why a given policy was chosen and
what were the main variables that lead to that decision. In addition, by using a multi-objective model
that considers social-environmental aspects as a goal, and not as a constraint, it might be possible to
better assess the trade-os that hydropower expansion presents.
The main goal of this research is to develop a multi-objective decision-support model that may be used
by policy makers to decide where to build new hydopower plants, considering social-environmental
aspects explicitly as an objective function.
Another desired goal is to identify the main aspects that might represent a barrier in this process,
in order to try to overcome them or indicate that increase in energy/storage might not be possible,
showing the main reasons and consequences of this outcome. |