  This paper tackles the short-term hydro-power unit commitment problem in a
multi-reservoir system - a cascade-based operation scenario. For this, we
propose a new mathematical modelling in which the goal is to maximize the total
energy production of the hydro-power plant in a sub-daily operation, and,
simultaneously, to maximize the total water content (volume) of reservoirs. For
solving the problem, we discuss the Multi-objective Evolutionary Swarm
Hybridization (MESH) algorithm, a recently proposed multi-objective swarm
intelligence-based optimization method which has obtained very competitive
results when compared to existing evolutionary algorithms in specific
applications. The MESH approach has been applied to find the optimal water
discharge and the power produced at the maximum reservoir volume for all
possible combinations of turbines in a hydro-power plant. The performance of
MESH has been compared with that of well-known evolutionary approaches such as
NSGA-II, NSGA-III, SPEA2, and MOEA/D in a realistic problem considering data
from a hydro-power energy system with two cascaded hydro-power plants in
Brazil. Results indicate that MESH showed a superior performance than
alternative multi-objective approaches in terms of efficiency and accuracy,
providing a profit of \$412,500 per month in a projection analysis carried out.
