Optimization Assisted Load Tracing via Hybrid Ant Colony Algorithm for Deregulated Power System

The development of electricity tracing theory is to solve the problem concerning fair and nondiscriminatory transmission service pricing of a deregulated power system. As the traditional methods such as postage stamp allocation and megawatts-mile methodology neglect the consideration of physical power system constraints, the allocation of service charge is said to be unreliable and rather biasing. At the same time, proportional sharing principle (PSP) based power tracing techniques necessitate for matrix inversion process; in which sometimes cannot be performed due to singularity property of the matrix. As a result, the tracing results are unable to be obtained due to error in mathematical operation. To try a new approach, this paper demonstrates the technique to implement Artificial Intelligence (AI) based optimization for performing load tracing, that is, by means of a new hybrid algorithm; Blended Crossover Continuous Ant Colony Optimization (BX-CACO) with simple and easy formulation steps. Experiment on IEEE 30-bus system together with comparative studies justifies the capability of the proposed technique for real system application. Key-Words: BIM, BX-CACO, Load Tracing, Matrix Singularity Property, PSP, TLDF