Micro Hydro Power Plants (MHPP) constitute an effective, environmentally-friendly
solution to deal with energy poverty in rural isolated areas, being the most extended renewable
technology in this field. Nevertheless, the context of poverty and lack of qualified manpower usually
lead to a poor usage of the resources, due to the use of thumb rules and user experience to design
the layout of the plants, which conditions the performance. For this reason, the development of
robust and efficient optimization strategies are particularly relevant in this field. This paper proposes
a Genetic Algorithm (GA) to address the problem of finding the optimal layout for an MHPP based on
real scenario data, obtained by means of a set of experimental topographic measurements. With this
end in view, a model of the plant is first developed, in terms of which the optimization problem is
formulated with the constraints of minimal generated power and maximum use of flow, together
with the practical feasibility of the layout to the measured terrain. The problem is formulated in
both single-objective (minimization of the cost) and multi-objective (minimization of the cost and
maximization of the generated power) modes, the Pareto dominance being studied in this last case.
The algorithm is first applied to an example scenario to illustrate its performance and compared with
a reference Branch and Bound Algorithm (BBA) linear approach, reaching reductions of more than
70% in the cost of the MHPP. Finally, it is also applied to a real set of geographical data to validate its
robustness against irregular, poorly sampled domains.Agencia Española de Cooperación Internacional para el Desarrollo 2014 / ACDE / 00601