Method and device for modeling a long-time-scale photovoltaic output time sequence

Abstract

A method and device for modeling a long-time-scale photovoltaic output time sequence are provided. The method includes that: historical data of a photovoltaic power station is acquired, and a photovoltaic output with a time length of one year and a time resolution of 15 mins is selected (101); weather types of days corresponding to the photovoltaic output are acquired from a weather station (102), and probabilities of transfer between each type of weather are calculated respectively (103); and a simulated time sequence of the photovoltaic output within a preset time scale is generated (104), and its validity is verified (105). By the method, annual and monthly photovoltaic output simulated time sequences consistent with a random fluctuation rule of a photovoltaic time sequence may be acquired according to different requirements to provide a favorable condition and a data support for analogue simulation of time sequence production including massive new energy.

1 . A method for modeling a long-time-scale photovoltaic output time sequence, comprising:
 acquiring historical data of a photovoltaic power station, and selecting a photovoltaic output with a time length of one year and a time resolution of 15 mins;   acquiring weather types of days corresponding to the photovoltaic output, the weather types comprising at least one of clear weather, cloudy weather, overcast weather or changing weather;   calculating probabilities of transfer between each type of weather respectively;   generating a simulated time sequence of the photovoltaic output within a preset time scale; and   verifying validity of the simulated time sequence.   
     
     
         2 . The method according to  claim 1 , wherein calculating the probabilities of transfer between each type of weather respectively comprises: adopting a Markov chain to simulate transfer processes of each type of weather and acquire the probabilities of transfer between each weather type, an expression being: 
       
         
           
             
               
                 
                   
                     
                       
                         P 
                         k 
                       
                       = 
                       
                         
                           N 
                           k 
                         
                         
                           N 
                           1 
                         
                       
                     
                     , 
                   
                 
                 
                   
                     ( 
                     1 
                     ) 
                   
                 
               
             
           
         
         in formula (1), P k  being the probability of transfer of the clear weather to another weather type, k representing a weather type, N k  being a number of times of transfer and N 1  being a number of times of occurrence of the clear weather. 
       
     
     
         3 . The method according to  claim 2 , further comprising: sequentially obtaining the probabilities of transfer between the other weather types by virtue of a method for calculating the probabilities of transfer of the clear weather to the other weather types. 
     
     
         4 . The method according to  claim 1 , wherein generating the simulated time sequence of the photovoltaic output within the preset time scale comprises: sequentially and randomly extracting the weather types and corresponding relative outputs within the preset time scale according to the probabilities of transfer between each weather type, and calculating products of the relative outputs and a predetermined threshold value to generate the simulated time sequence of the photovoltaic output, wherein the simulated time sequence is a curve chart for reflecting changes of a Probability Density Function (PDF), an Autocorrelation Function (ACF) and short-duration fluctuation characteristic of photovoltaic output of multiple time scales;
 wherein the short-duration fluctuation characteristic is a maximum PDF of the photovoltaic output within a time scale t, 15 min≤t≤60 min;   the maximum PDF being a difference value between a maximum output and a minimum output within the time scale t; and the difference value is positive if the maximum output appears after the minimum output, and the difference value is negative if the maximum output appears before the minimum output.   
     
     
         5 . The method according to  claim 1 , wherein verifying the validity of the simulated time sequence comprises:
 defining the PDF C f , short-duration fluctuation characteristic C d  and ACF C r  of the simulated time sequence respectively; and   adopting a Root-Mean-Square Error (RMSE) of each characteristic to quantitatively evaluate the validity of the time sequence, an expression being:   
       
         
           
             
               
                 RMSE 
                 = 
                 
                   
                     
                       1 
                       n 
                     
                     · 
                     
                       
                         ∑ 
                         
                           i 
                           = 
                           1 
                         
                         n 
                       
                        
                       
                           
                       
                        
                       
                         ( 
                         
                           
                             
                               y 
                               ^ 
                             
                             i 
                           
                           - 
                           
                             y 
                             i 
                           
                         
                         ) 
                       
                     
                   
                 
               
               , 
             
           
         
         where ŷ i  ∈[C f , C d , C r ], ŷ i  is a unit vector and represents a function value of each characteristic of the simulated time sequence, y i  represents a function value of each characteristic, corresponding to each characteristic of the simulated time sequence, of a historical time sequence, n is a length of a function value set of each characteristic of the time sequence, RMSE is smaller than ε with a value range of 0.1˜0.2. 
       
     
     
         6 . A device for modeling a long-time-scale photovoltaic output time sequence, comprising:
 a memory storing computer-executable instructions; and   one or more processors executing the computer-executable instructions to implement a plurality of program units, wherein the plurality of program units comprise:   a data acquisition unit, configured to acquire historical data of a photovoltaic power station, and select a photovoltaic output with a time length of one year and a time resolution of 15 mins;   an acquisition unit, configured to acquire weather types of days corresponding to the photovoltaic output from a weather station, the weather types comprising at least one of clear weather, cloudy weather, overcast weather or changing weather;   a processing unit, configured to calculate probabilities of transfer between each type of weather respectively;   a generation unit, configured to generate a simulated time sequence of the photovoltaic output within a preset time scale; and   an evaluation unit, configured to verify validity of the simulated time sequence.   
     
     
         7 . The device according to  claim 6 , wherein the processing unit is further configured to: adopt a Markov chain to simulate transfer processes of each type of weather and acquire the probabilities of transfer between each weather type, an expression being: 
       
         
           
             
               
                 
                   
                     
                       
                         P 
                         k 
                       
                       = 
                       
                         
                           N 
                           k 
                         
                         
                           N 
                           1 
                         
                       
                     
                     , 
                   
                 
                 
                   
                     ( 
                     1 
                     ) 
                   
                 
               
             
           
         
         in formula (1), P k  being the probability of transfer of the clear weather to another weather type, k representing a weather type, N k  being a number of times of transfer and N 1  being a number of times of occurrence of the clear weather. 
       
     
     
         8 . The device according to  claim 7 , wherein the plurality of program units further comprise: a probability acquisition unit, configured to sequentially obtain the probabilities of transfer between the other weather types by virtue of a method for calculating the probabilities of transfer of the clear weather to the other weather types. 
     
     
         9 . The device according to  claim 6 , wherein the generation unit is further configured to: sequentially and randomly extract the weather types and corresponding relative outputs within the preset time scale according to the probabilities of transfer between each weather type, and calculate products of the relative outputs and a predetermined threshold value to generate the simulated time sequence of the photovoltaic output, wherein the simulated time sequence is a curve chart for reflecting changes of a Probability Density Function (PDF), Autocorrelation Function (ACF) and short-duration fluctuation characteristic of photovoltaic output of multiple time scales;
 wherein the short-duration fluctuation characteristic is a maximum PDF of the photovoltaic output within a time scale t; 15 min≤t≤60 min;   the maximum PDF being a difference value between a maximum output and a minimum output within the time scale t; and the difference value is positive if the maximum output appears after the minimum output, and the difference value is negative if the maximum output appears before the minimum output.   
     
     
         10 . The device according to  claim 6 , wherein the evaluation unit is further configured to:
 define the PDF C f , short-duration fluctuation characteristic C d  and ACF C r  of the simulated time sequence respectively; and   adopt a Root-Mean-Square Error (RMSE) of each characteristic to quantitatively evaluate the validity of the time sequence, an expression being:   
       
         
           
             
               
                 RMSE 
                 = 
                 
                   
                     
                       1 
                       n 
                     
                     · 
                     
                       
                         ∑ 
                         
                           i 
                           = 
                           1 
                         
                         n 
                       
                        
                       
                           
                       
                        
                       
                         ( 
                         
                           
                             
                               y 
                               ^ 
                             
                             i 
                           
                           - 
                           
                             y 
                             i 
                           
                         
                         ) 
                       
                     
                   
                 
               
               , 
             
           
         
         where ŷ i  ∈[C f , C d , C r ], ŷ i  is a unit vector and represents a function value of each characteristic of the simulated time sequence, y i  represents a function value of each characteristic, corresponding to each characteristic of the simulated time sequence, of a historical time sequence, n is a length of a function value set of each characteristic of the time sequence, RMSE is smaller than ε with a value range of 0.1˜0.2. 
       
     
     
         11 . The method according to  claim 3 , wherein generating the simulated time sequence of the photovoltaic output within the preset time scale comprises:
 sequentially and randomly extracting the weather types and corresponding relative outputs within the preset time scale according to the probabilities of transfer between each weather type, and calculating products of the relative outputs and a predetermined threshold value to generate the simulated time sequence of the photovoltaic output, wherein the simulated time sequence is a curve chart for reflecting changes of a Probability Density Function (PDF), an Autocorrelation Function (ACF) and short-duration fluctuation characteristic of photovoltaic output of multiple time scales;   wherein the short-duration fluctuation characteristic is a maximum PDF of the photovoltaic output within a time scale t, 15 min≤t≤60 min;   the maximum PDF being a difference value between a maximum output and a minimum output within the time scale t; and the difference value is positive if the maximum output appears after the minimum output, and the difference value is negative if the maximum output appears before the minimum output.   
     
     
         12 . The device according to  claim 8 , wherein the generation unit is further configured to: sequentially and randomly extract the weather types and corresponding relative outputs within the preset time scale according to the probabilities of transfer between each weather type, and calculate products of the relative outputs and a predetermined threshold value to generate the simulated time sequence of the photovoltaic output, wherein the simulated time sequence is a curve chart for reflecting changes of a Probability Density Function (PDF), Autocorrelation Function (ACF) and short-duration fluctuation characteristic of photovoltaic output of multiple time scales;
 wherein the short-duration fluctuation characteristic is a maximum PDF of the photovoltaic output within a time scale t, 15 min≤t≤60 min;   the maximum PDF being a difference value between a maximum output and a minimum output within the time scale t; and the difference value is positive if the maximum output appears after the minimum output, and the difference value is negative if the maximum output appears before the minimum output.   
     
     
         13 . A non-transitory computer-readable storage medium having stored therein instructions that, when executed by a processor, causes the processor to perform a method for modeling a long-time-scale photovoltaic output time sequence, the method comprising
 acquiring historical data of a photovoltaic power station, and selecting a photovoltaic output with a time length of one year and a time resolution of 15 mins;   acquiring weather types of days corresponding to the photovoltaic output, the weather types comprising at least one of clear weather, cloudy weather, overcast weather or changing weather;   calculating probabilities of transfer between each type of weather respectively;   generating a simulated time sequence of the photovoltaic output within a preset time scale; and   verifying validity of the simulated time sequence.   
     
     
         14 . The non-transitory computer-readable storage medium according to  claim 13 , wherein the step of calculating the probabilities of transfer between each type of weather respectively comprises: adopting a Markov chain to simulate transfer processes of each type of weather and acquire the probabilities of transfer between each weather type, an expression being: 
       
         
           
             
               
                 
                   
                     
                       
                         P 
                         k 
                       
                       = 
                       
                         
                           N 
                           k 
                         
                         
                           N 
                           1 
                         
                       
                     
                     , 
                   
                 
                 
                   
                     ( 
                     1 
                     ) 
                   
                 
               
             
           
         
         in formula (1), P k  being the probability of transfer of the clear weather to another weather type, k representing a weather type, N k  being a number of times of transfer and N 1  being a number of times of occurrence of the clear weather. 
       
     
     
         15 . The non-transitory computer-readable storage medium according to  claim 14 , the method further comprises: sequentially obtaining the probabilities of transfer between the other weather types by virtue of a method for calculating the probabilities of transfer of the clear weather to the other weather types. 
     
     
         16 . The non-transitory computer-readable storage medium according to  claim 13 , wherein the step of generating the simulated time sequence of the photovoltaic output within the preset time scale comprises: sequentially and randomly extracting the weather types and corresponding relative outputs within the preset time scale according to the probabilities of transfer between each weather type, and calculating products of the relative outputs and a predetermined threshold value to generate the simulated time sequence of the photovoltaic output, wherein the simulated time sequence is a curve chart for reflecting changes of a Probability Density Function (PDF), an Autocorrelation Function (ACF) and short-duration fluctuation characteristic of photovoltaic output of multiple time scales;
 wherein the short-duration fluctuation characteristic is a maximum PDF of the photovoltaic output within a time scale t, 15 min≤t≤60 min;   the maximum PDF being a difference value between a maximum output and a minimum output within the time scale t; and the difference value is positive if the maximum output appears after the minimum output, and the difference value is negative if the maximum output appears before the minimum output.   
     
     
         17 . The non-transitory computer-readable storage medium according to  claim 13 , wherein the step of verifying the validity of the simulated time sequence comprises:
 defining the PDF C f , short-duration fluctuation characteristic C d  and ACF C r  of the simulated time sequence respectively; and   adopting a Root-Mean-Square Error (RMSE) of each characteristic to quantitatively evaluate the validity of the time sequence, an expression being:   
       
         
           
             
               
                 RMSE 
                 = 
                 
                   
                     
                       1 
                       n 
                     
                     · 
                     
                       
                         ∑ 
                         
                           i 
                           = 
                           1 
                         
                         n 
                       
                        
                       
                           
                       
                        
                       
                         ( 
                         
                           
                             
                               y 
                               ^ 
                             
                             i 
                           
                           - 
                           
                             y 
                             i 
                           
                         
                         ) 
                       
                     
                   
                 
               
               , 
             
           
         
         where ŷ i  ∈[C f , C d , C r ], ŷ i  is a unit vector and represents a function value of each characteristic of the simulated time sequence, y i  represents a function value of each characteristic, corresponding to each characteristic of the simulated time sequence, of a historical time sequence, n is a length of a function value set of each characteristic of the time sequence, RMSE is smaller than ε with a value range of 0.1˜0.2.