Solution of probabilistic load flow in power system based on non-intrusive arbitrary polynomial chaos theory

Non-intrusive arbitrary polynomial chaos theory (NIAPC) can overcome the defects of traditional methods which need abundant simulations and time. Meanwhile, NIAPC can deal with probabilistic load flow analysis with arbitrary distributed uncertainties precisely with a small quantity of simulations. The paper presents the probabilistic load flow based on non-intrusive arbitrary polynomial. Firstly, the probabilistic collocation points are chosen. Then, Hermite polynomial is solved, and the uncertain problems whose parameters obey to experienced probability distribution are solved. Finally, the paper simulated the process of probabilistic load flow (PLF) on the platform of Matlab. The results were compared between NIAPC and Monte Carlo (MC). Results indicate that the PLF calculation based on NIAPC is not only able to achieve a high accuracy compared to the MC, but also it does own high potential to relief the computation burden of traditional PLF calculation drastically.