A Solution to The Unit Commitment Problem Using Hybrid Genetic and particle swarm optimization Algorithms

The solution of the unit commitment problem (UCP) is a complex optimization problem. The exact solution of the UCP can he obtained by a complete enumeration of all feasible combinations of generating units, which could be a huge number. The objective is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for the next hours. This paper presents a hybrid genetic and particle swarm optimization algorithms (HGAPSO) to solve optimal Unit Commitment Problem (UCP). The HGAPSO is applied to the widely used ten-unit test system and its multiples (10-100). Comparing our results with those of many UC solving methods demonstrate that not only the HGAPSO procedure consider is the constraints very well, but also has some advantages, such as good convergence, fast calculating speed and high precision.