Probabilistic load flow analysis using Halton sequences in power systems with renewable resources

Rising penetration of renewable resources in power systems through integration of distributed generation (DG) confronts traditional deterministic load flow (DLF) analysis with serious uncertainties and challenges. This claim is a direct consequence of variable energy production capability of the DGs whose operation strongly depends on weather conditions. The DLF approach gives only a snapshot of the state of the system at certain moment neglecting the all uncertainties arising from variable generation capabilities of DGs and volatility of consumption. Therefore, for the sake of such analyses another approach, namely, probabilistic load flow (PLF) should be adopted. The main issue regarding the application of PLF is the balance between method accuracy and efficiency. This paper is aimed to confirm the applicability of PLF method combining Monte Carlo simulations with Halton sequences for the modern power systems with integrated renewable generation. To that end, modified IEEE 30 bus test system was taken as a base for analysis and simulations, as well as deriving of key findings. Results have shown significant reduction of calculation time in comparison to basic Monte Carlo method, while keeping the precision of similar quasi-random techniques