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Digital Generator Capability Curve for Improving Optimal Power Flow based on IPSO
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Abstract
The generator capability curve (GCC) based on neural network (NN) is used as a constraint in optimal power flow based on improved particle swarm optimization (OPF-IPSO) to replace rectangular (Pmin-Pmax and Qmin-Qmax) constraint in achieving lower cost at the same security level. The security check algorithm is developed to eliminate the complicated mathematical equations in employing GCC as a constraint in OPF-IPSO. The algorithm is very simple and flexible especially for representing non-linear generation operation limits and under excitation operation areas. In effort to avoid local optimal solution and to get global optimal solution faster, chaotic parameter is used in updating weights of PSO. The data used to verify the performance of the proposed method is the Java-Bali 500 kV power systems that containt 8 generators and 23 buses
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