%0 Journal Article %A Mat Syai'in and Adi Soeprijanto %D 2010 %J International Journal of Electrical and Computer Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 48, 2010 %T Neural Network Optimal Power Flow(NN-OPF) based on IPSO with Developed Load Cluster Method %U https://publications.waset.org/pdf/4025 %V 48 %X An Optimal Power Flow based on Improved Particle Swarm Optimization (OPF-IPSO) with Generator Capability Curve Constraint is used by NN-OPF as a reference to get pattern of generator scheduling. There are three stages in Designing NN-OPF. The first stage is design of OPF-IPSO with generator capability curve constraint. The second stage is clustering load to specific range and calculating its index. The third stage is training NN-OPF using constructive back propagation method. In training process total load and load index used as input, and pattern of generator scheduling used as output. Data used in this paper is power system of Java-Bali. Software used in this simulation is MATLAB. %P 1701 - 1706