This paper presents an algorithm to solve a unit
commitment problem that takes into account the uncertainty in
the demand. This uncertainty is included in the optimization
problem as a joint chance constraint that bounds the minimum
value of the probability to jointly meet the deterministic power
balance constraints. The demand is modeled as a multivariate,
normally distributed, random variable and the correlation
among different time periods is also considered. A deterministic
mixed-integer linear programming problem is sequentially
solved until it converges to the solution of the chanceconstrained
optimization problem. Different approaches are
presented to update the z-value used to transform the joint
chance constraint into a set of deterministic constraints. Results
from a realistic size case study are presented and the values
obtained for the multivariate normal distribution probability
are compared with the ones obtained by using a Monte Carlo
simulation procedure
