Optimasi Penjadwalan Ekonomis Pembangkit pada Sistem IEEE 30 Bus dengan Algoritma Metaheuristik

Power Plants Economic Dispatch Optimization on IEEE 30 Bus System using Metaheuristic Algorithms. Economical scheduling or also known as economic dispatch (ED) of power plants is an important approach in electric power system to reduce fuel costs while still considering the system technical constraints. ED problems are nonlinear and complex because they involve quadratic functions, generation limits and power losses in the system. In this study, metaheuristic algorithm are used, namely Particle Swarm Optimization (PSO) and Novel Bat Algorithm (NBA) which are applied to an IEEE 30-bus sytem with 6 generator units. The data used are generator cost function data, minimum and maximum generator limit data, load data for each bust and transmission line parameters. Both metaheuristic algorithms are simulated in MATLAB software, with the objective function of minimizing the total generation cost and considering power losses as an additional evaluation parameter. Based on the simulation results, NBA shows a total generation cost of $488.07/hour while PSO is $501.54/hor. By using the NBA method, the total fuel cost is cheaper than PSO. Power allocation using NBA is more economically efficient, although it results in slightly higher power losses of 4.76 MW compared to PSO 4.16 MW. However, this difference is still with acceptable limits. Therefore, this algorithm can be an effective alternative for optimizing generator scheduling in electric power system.