Typical Scenarios Selection Of Wind Power Output Based On Measured Data

With constantly highlighting environmental problems resulted from fossil energy crisis and energy exploitation, new energy, as the clean, renewable energy, occupies an increasing proportion in the energy structure. China owns a vast territory with abundant wind and solar power reserves. At present, China is speeding up the process of building large wind farms and solar power plants.Because of the electric randomness, volatility and uncontrollability, large-scale wind power grid connection will bring a series of problems related to power quality, system security, redefining and distributing the system reserve capacity as well as the increasing operating costs of all parts. It is necessary to select a typical wind power scene for the full consumption or affordable consumption of wind power, and the stability of the power grid. According to the wind power scene, a typical output characteristic of wind power in the region could be achieved for the planning and operation of regional grid with wind power.Summing up the results of relevant research at home and abroad, the paper firstly analyzes the characteristics of wind speed, sets up wind speed model and steady-state model of the wind turbine, and discusses the multi-scene technical and classical statistical methods and Cluster Theory related to the paper. Then based on the average value, the paper introduces the selecting method for the typical scene of the regional wind power, which reflects the average output characteristic of regional wind power. It also proposes, according to the typical regional load characteristics, the selecting method for the typical scene of the regional wind power based on the Pearson product-moment correlation coefficient method, to select the wind power scene in the Calculation of regional peaking power grid. With this method, we could extract the wind power scene with the most notably characteristics of forward regulation and inverse regulation of wind power in the region.Regarding to the massive output of the wind power, this paper puts forward the selecting method for the typical scene of the regional wind power based on Data Mining and Fuzzy C-means clustering algorithm. As requested by the Fuzzy C-means clustering algorithm, the number of classes must be given out before cluster computing. Therefore, it proposes the selecting method for the typical scene of the regional wind power based on hierarchical clustering algorithm by directly classifying the designated data. With these methods, it could extract the typical scene of the regional wind power with the largest probability of occurrence and the typical scene of the regional wind power with the most volatility.The paper uses the actual operation data of wind power in a region to carry out the simulation of four selecting method for the typical scene of the regional wind power mentioned above, which verifies the feasibility of the method. The achievement of this paper could serve the theoretical basis for the selection of typical scene of the regional wind power.