Perbandingan Metode Gaussian Particle Swarm Optimization (GPSO) dan Lagrange Multiplier pada Masalah Economic Dispatch
DOI:
https://doi.org/10.21512/comtech.v3i1.2407Keywords:
power system, load demand, economic dispatch, Gaussian Particle Swarm Optimization (GPSO), Lagrange MultiplierAbstract
On electric power system operation, economic planning problem is one variable to take into account due to operational cost efficiency. Economic Dispatch problem of electric power generation is discussed in this study to manage the output division on several units based on the the required load demand, with minimum operating cost yet is able to satisfy equality and inequality constraint of all units and system. In this study the Economic Dispatch problem which has non linear cost function is solved using swarm intelligent method is Gaussian Particle Swarm Optimization (GPSO) and Lagrange Multiplier. GPSO is a population-based stochastic algorithms which their moving is inspired by swarm intelligent and probabilities theories. To analize its accuracy, the Economic Dispatch solution by GPSO method is compared with Lagrange Multiplier method. From the test result it is proved that GPSO method gives economic planning calculation better than Lagrange Multiplier does.
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