With constant improvement of intermittent energy source, its agglomeration effect and stochastic volatility will greatly influence the power system operation. It’s an inexorable trend that probabilistic power flow calculation shifts from offline analysis to real-time operation online. Among all probabilistic trend algorithms, probability flow calculation based on cumulant method is the fastest one; it has better prospect of online application. However, it requires random variables independent to each other, so the single slack bus always undertakes all unbalance power in conventional cumulant methods. When the fluctuation of system power injection becomes larger and larger, this calculation model will hardly adapted to the actual demand of the grid in the future. To improve the practicability, a improvement of probabilistic load flow based on cumulant method is proposed in this paper. By modify the calculation of the sensitivity matrix, the distribution of system unbalance power can be considered. The accuracy of this method is verified by the simulated analysis of the standard examples and actual power system model.
Probabilistic load flow calculation based on sparse polynomial chaos expansion
