Available transfer capability assessment using evolutionary programming based capacity benefit margin

The determination of ATC must accommodate a reasonable range of capacity benefit margin (CBM) so that the operation of power system is secure from the generation deficiency that may occur during a power transfer. There are two ways of incorporating CBM into ATC, which are by considering the CBM as firm and non-firm transfers. The CBM for each area is specified based on the installed generation capacity that gives the loss-of-load expectation index below 2.4 h/year. The determination of CBM based on heuristic search for a large size power system with many areas is complicated and computationally time consuming. Therefore, a new technique is proposed which uses evolutionary programming (EP) to maximize the total amount of generation capacity so as to determine the CBM for each area. The EP performance is improved by using the modified Gaussian formulation in which it has the capability of providing a new population in a fast global maximum domain search. The proposed EP with modified Gaussian formulation in estimating the CBM is verified on the modified 24 bus IEEE reliable test system. Comparison in terms of accuracy and computation time in estimating the CBM is made by considering the four methods which are the EP using modified Gaussian formulation, EP using standard Gaussian formulation, genetic algorithm (GA) and the conventional method.