The Study Of Power Generation Capacity Forecast Methods And Coordinate Strategy Of Large Hydropower And Small Hydropower In Yunnan Power Grid

As a result of the regional development demand and the national policy, the small hydropower(SHP) has gained rapid growth in recent years, the SHPs with multi-characteristic have connected to Yunnan Power Grid in a large scale and over long distance, which become a threat to the power grid. Meanwhile, the SHPs compete with large hydropowers(LHP) on occupying limited transmission access in flood season, resulting in the abandon water. Therefore, obtaining the power generation capacity of SHPs and coordinating the LHPs&SHPs on the basis of the hydrology, power generation and parallel in of LHPs&SHPs is of great significance, which ensures the security and stability of power grid, the reduction of the waste of water and abandoned electrcity. The power generation forecast of SHP faces series problems of data shortage, the uncertainty of power generation, no regularity of a single station, the poor generality of forecasting model as a result of the characteristics of SHP. The coordination of LHPs&SHPs faces the problem of checking the water level of the power station in ultra-short term hydropower scheduling due to the lack of the delay time and the interval flow data of the certain cascade. Also, it's impossible to check the situation of partition power exceed accurately because of the lack of data for real-time power generation and the exceeding information of partition power. Therefore, this paper takes Yunnan Power Grid as the example to study the problems mentioned above. The results are as follows:1) For the long-term generation forecast of SHP, this paper puts forward a correlation analysis method of large and small hydropower for generation capacity forecast of SHP. We regard the SHPs of an area as a whole to analysis the multi-character of SHPs and the geography, hydrology, climate of the area rich in SHPs. After the screening of the correlation factor, we analysis and test the correlation of LHP and SHP. At last, a regression model of large and small hydropower is built for different districts, which provides the reference for the monthly generation scheduling.2) For the short-term generation forecast of SHP, this paper puts forward a divided seasonal stationary time series for generation capacity forecast of SHP by cluster analysis. We select the related data of SHP power generation capacity ervey 10 days and conduct the cluster analysis for the selected data, which divide the flood season and drought season into seperated periods. After that the sequence data for seasonal stationary time series can be obtained. At last the forecast model is built for different periods, which provides the forecast data for the day-ahead generation scheduling. 3) For the ultra-short term forecast of inflow and interval-flow for cascaded stations, this paper puts forward a ultra-short term delay time sequence forecast method for cascaded hydropower stations. First, the upstream history outflow and downstream flow of each hydropower plant are analyzed to solve the rational delay time and flow relationship. Second, the upsteam outflow will be out from the downstream flow to abtain effective interval-flow.Third, a sequence forecast method of forecasting downstream flow by day is built. At last, the inflow and interval-flow is calculated, which provides the data for the check of water level in ultra-short term regulation. 4) For the coordination of LHPs&SHPs, this paper puts forward an ultra-short term dispatching strategy for the coordination of LHPs&SHPs. Considering the load deviations in ultra-short term scheduling, we make full use of the real-time power generation, water regime and power partations information to guarantee load balance by allocating the power in cascaded hydroplants and check the partition power exceed in different levels. After that, the ultra-short term coordination of LHPs&SHPs is achieved, also the abandon water of SHPs is reduced as a result of the regulating capacity of LHP. This paper takes LHPs&SHPs of Yunnan Province as the example to study, the result indicates that the power generation forecast models of SHP, the coordination strategy of LHPs&SHPs models mentions in this paper can effectively solve some of the key problems caused by the SHPs connectd to the grid in a large scale. For the practical application, these models also have reference value.