Enhancement of thermal unit commitment using immune algorithms based optimization approaches

A new approach using immune algorithms to solve thermal generation scheduling problems is proposed in this article. In the proposed scheme, the objective functions and constraints were categorized as antigens. The antibodies for the immune system were determined through the calculation of affinity. For an antibody that is perfectly combined with the antigen, this antibody is deemed the solutions to the problem. With the embodiment of affinity computation, the possibility of stagnation in the iteration process was decreased. The computational performance can be also enhanced. The proposed method was tested on a practical Taiwan Power System (Taipower) through the utility data. The test results demonstrated the feasibility of this method for unit-scheduling applications.