Genetic algorithms in power system planning and operation

Effective optimal power system planning and operation is limited by: (i) the high dimensionality of power systems; and (ii) the incomplete domain dependent knowledge of power system engineers. The first limitation is addressed by numerical optimisation procedures using gradient approximations to calculate the search directions in various nonlinear programming formulations or by linear programming solutions to imprecise models. The advantages of such methods are in their mathematical underpinnings, but disadvantages exist also in the sensitivity to problem formulation, algorithm selection and undue focus on local minima. Here, the author examines the use of genetic algorithms in addressing the above problems.