Probabilistic Power Flow Analytic Algorithm Based on Scenario Partition

With increasing penetration of renewable energy in power system, fluctuation of random factors ranges more widely, posing a great challenge to accuracy of conventional cumulant method. In this paper, a new probabilistic power flow method based on scenario partition is proposed. Scenario reduction algorithm is used to obtain typical working scenario of power system, and, on this basis, several scenario sets are generated. In each scenario set, the cumulant method is used to calculate probabilistic power flow. Overall distribution of power flow is obtained using total probability formula. The new probabilistic power flow algorithm based on scenario partition proposed in this paper completes partitioning operation of initial scenario database, and fluctuation range of the random factors is limited to the scenario set where they lie. Thus, the fluctuation of random factors is reduced equivalently, so the drawback is eliminated that the probabilistic power flow of power system with high proportion renewable energy cannot be accurately obtained with conventional cumulant method. Effectiveness and accuracy of the proposed method are verified on the modified IEEE-118 system.