Analysis Of Reservoir Optimal Operation Under Climate Change

Hydropower is an important part of China’s electric power industry.As a clean energy,it plays an important role in energy saving and emission reduction.Global climate change has become an objective fact that affects temperature and the distribution of precipitation.It directly affects the operation of hydropower system,and has an important impact on hydropower enrichment in southwestern China.Therefore,it is of great significance to study hydropower dispatching under climate change scenarios.Based on the background of the Lancang River Basin,this paper forecasts the runoff process under future climate change scenarios based on the NASA Earth Exchange Global Daily Downscaling Forecast(NEX-GDDP)dataset,and uses the forecasted runoff process to optimize the mid-and long-term hydropower stations.The specific work is as follows.(1)Six climate change scenario datasets consisting of NEX-GDDP’s CCSM4,GFDL-ESM2 M and MRI-CGCM3 global climate change models are selected to compose two emission scenarios: RCP 4.5 and RCP 8.5.The actual data of Lancang river basin from 1961 to 2012 and the change process of temperature and precipitation under the climate change scenario from 2013 to 2092 were compared and analyzed,and the change rules of climate characteristics such as maximum temperature,minimum temperature and precipitation were analyzed,as well as the differences under different climate change scenarios.Meanwhile,the differences of maximum temperature,minimum temperature and mean precipitation under different climate change scenarios were compared by time periods.It was found that the rate of temperature rise and precipitation increment in flood season under RCP 8.5 were both greater than that under RCP 4.5.(2)The BP neural network model is used to predict runoff.Rainfall and inbound runoff from 1961 to 2000(480 sets of data)were taken as network training samples.Meteorological data from 2001 to 2012(144 sets of data)and inbound runoff data were taken as network detection samples to establish a neural network.The results show that the future runoff predicted under different emission scenarios and models shows an increasing trend,and the monthly and annual average runoff in 2053-2092 are larger than the historical value.From different emission scenarios,the impact of RCP8.5 on runoff increase is greater than RCP4.5,indicating that the greater the emission intensity,the more obvious the increase in runoff.From the perspective of emission patterns,runoff changes are most pronounced in the GFDL-ESM2 M mode.From the perspective of time,the effects of climate change on runoff are more pronounced over time.(3)In order to maximize the generation capacity,an optimal dispatching model of hydropower station dynamic programming is established.The reservoir optimization scheduling is carried out for the runoff prediction results in different periods.It can be found from optimal dispatching results that under the influence of different emission scenarios and global climate patterns,the power generation of Xiaowan and Manwan hydropower stations will increase with the passage of time.In most climate change scenarios,annual average power generation is less than historical average power generation in the initial stage,but with the passage of time,annual power generation in all climate change scenarios is greater than historical average power generation at the end of this century.The annual power generation of Xiaowan and Manwan is arranged in the order of GFDL-ESM2 M,CCSM4 and MRI-CGCM3,and the annual power generation under RCP 8.5 scenario is larger than that under RCP 4.5 scenario.The simulation results show that the impact of different climate change scenarios on hydropower dispatching varies greatly.The research on optimal dispatch of hydropower system under climate change is conducive to power generation enterprises and grid companies to predict the future situation of hydropower generation and formulate corresponding response measures,and to improve the economic benefits of power generation enterprises and the stability of power grid.