A New Algorithm And Its Application For The Probabilistic Load Flow Of The Power System

The computation of probabilistic load flow is an important content in the electricalpower system analysis, and it is helpful to get a comprehensive appraisal for theperformance of the entire electrical network under all kinds of operation conditions, andmakes a quantitative assessment to the weak segment which exists in the electricalnetwork. The information extremely has the reference value with the dispatchdepartment's decision-making and planning. Also it has its special value in the researchand its application under the electric power market environment. This innovative methodthat the combines the concept of semi-invariant and Gram-Charlier expansion theory inthe paper can fast and precisely obtain probability distribution function (PDF) and thecumulative distribution function (CDF) of transmission line flows. It adopts a linearizedAC model on the mathematical model. When getting some low order semi-invariant withbasic theory of Probability Theory & Mathematical Statistics, we can enough preciselyestimate the PDF and CDF of the load flow by the Gram-Charlier expanding. Thus itsignificantly reduces computation effort and the computation storage space. In the end,with a computation to an typical large-scale system, compared with the result of MonteCarlo simulation method, it had proven that the method of combined semi-invariant andGram-Charlier expanding has a high degree of accuracy and efficiency.