Probabilistic harmonic load flow using an improved kernel density estimator

• A method for probabilistic harmonic load flow has been presented.
• It can handle the correlation between input variables.
• It has been applied to the IEEE 14-bus harmonic test system.

Harmonic distortion in power systems is a growing phenomenon that could lead to serious problems. Harmonic load flow (HLF) methods have been developed in order to predict and solve many of the problems caused by harmonics from a deterministic point of view. Probabilistic approaches for HLF calculation are necessary due to the existence of uncertainties in electrical power systems and random nature of harmonics. In this paper, a new method using an improved kernel density estimator for probabilistic harmonic load flow (PHLF) calculation is presented. Unlike many other methods, this one is immune to errors caused by simplified probabilistic techniques based on linearized models or any simplifying assumptions. Its implementation for any problem is easy and it can handle the correlated variables. The proposed method has been tested on the well-known IEEE 14-bus harmonic test system. The simulation results clearly show that it guarantees a reasonable execution time as well as an acceptable accuracy in obtaining the harmonic probability density functions (PDFs) of output random variables.