Improvement of Local Search for the Problem of Economic Dispatch using the Golden Section Ratio in the Bee Colony Optimization Method

Abstract

This article provides a way to improve local search using the golden section ratio in the bee colony optimization method for the problem of economic dispatch. This modification adjusts the movement process to find new sources of bee feed. From the original, the multiplication factor has to be multiplied, which results in a fairly wide distribution. This process of refinement uses the gold ratio as a multiplicative component in the equation of motion of the bee population instead of the random step. Operations will consider power system requirements, transmission line losses, and regulatory conditions. The MATLAB program was used for simulation and testing with 2 standard case studies consisting of 3 generators and 6 units. Testing to evaluate the effectiveness of the methods presented used traditional BCO, HLBCO and MSA methods. Comparisons were made in terms of response efficiency and convergence speed. From the results of the tests it can be concluded that the proposed method provides a valid and effective solution to solve the problem of the quality of the answer- the convergence feature. In case 1, the proposed method calculated the average number of rounds was 256.8- 59 per cent faster than usual- with the lowest cost at 1957.48. In case 2, the proposed method calculated the average number of rounds was 145.9 rounds- 33.27 per cent faster than usual- with the lowest cost at 15439.51.