Research On Forecast Method Of Power System Cascading Outages And It's Application

Large-scale blackouts of electrical power systems have been concerned around the world in recent years. Most of the blackouts are caused by cascading outage, the study of which has been a popular issue nowadays. Due to increasing complexity of modern electric network, the work appears to be more challenging. This is reflected by the facts that the outages are usually linked to a complex combination of events, constructing analytical equations of the process and is often difficult. This paper mainly study on the model building, the evaluation, the forecasting for practical application and the vulnerability assessment based on the cascading outages forecasting. Further, the author studies on the statistical learning theory applied in the cascading outages assessment.The paper discusses some important issues about the self-organized criticality of the large-scale blackouts in power system in detail, including the characteristics of power laws distribution, the fractal and 1/f noise. And then the author makes the probability analysis model considering the needs and features of the predictive analysis. As from the perspective of the forecast, the factors, such as the location of the initial failure, the reclosing etc., are not certainty. To analysis in the probability way, firstly, we can quantify the probability of the above factors to quantify the probability of the chain fault path searched in the forecasting; secondly the result of the quantification is used to compare the probability of different chain fault paths.In this paper, the evaluation index of the probability, the possibility and the speed of the cascading outage is presented and the method based on fuzzy clustering and integration evaluation on the cascading outage is proposed. The evaluation index will be used in the forecast to find the cascading outage path which is most likely and the most quickly overspread, and then we can find the vulnerability of the network earlier.This paper proposes a search strategy of cascading outage path, based on probability prioritization and by combining network monitor. As the number of random factors in network is tremendous , it is hard to search the entire cascading outage path. Using probability prioritization strategy and starting from reality and possibility, the search can ensure that the pathes are some chains that may happen, and then the searched pathes may be useful for the actual operation .On this basis, this paper brings forward a way to analyze the vulnerability lines in network and warning strategy.Finally, the paper presents a power system cascading outage assessment methods based on statistical learning theory, the starting point of this method is the actual use ofdata resources and combine statistical learning theory with the Support Vector Machine (SVM) technology which can be easier to promote, it also provides a useful additional tool for rapid assessment and simulation and can be used in practical.