Method for quantitatively evaluating output fluctuation of photovoltaic field stations based on RankBoost
A quantitative evaluation, photovoltaic station technology, applied in the direction of AC network circuits, electrical components, single-network parallel feeding arrangements, etc., can solve problems such as inconvenient operation and planning, not comprehensive and scientific enough, and indicators that are not intuitive and concise.
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Embodiment 1
[0111] see Figure 1 to Figure 5 , a RankBoost-based quantitative evaluation method for fluctuations in photovoltaic field output, which mainly includes the following steps:
[0112] 1) Obtain the historical output data of the photovoltaic field station, and eliminate invalid data, and establish a valid data set V. The main steps are as follows:
[0113] 1.1) Read the historical output data set of the photovoltaic field station Y={D 1 ,D 2 ,...D 365}; Among them, the output data D in the i-th day i =(P i,1 ,P i,2 ,...,P i,g ...,P i,G ), i=1,2,...,365; P i,g Output at the gth sampling point on the i-th day, g=1,2,...,G;
[0114] 1.2) Parameter initialization, that is, the date i=1, the number of valid days N=0, and the valid data set
[0115] 1.3) Calculate the output starting point g of the photovoltaic station on the i-th day respectively 1,i and output termination point g 2,i ,which is:
[0116] g 1,i =min{g,P i,g ≤0 and P i,g+1 >0} (1)
[0117] g 2,i =ma...
Embodiment 2
[0220] An experiment to verify the quantitative evaluation method of photovoltaic field output fluctuation based on RankBoost mainly includes the following steps:
[0221] 1) Data acquisition: 3-year output data of 6 photovoltaic stations in a certain area in southern China on a 15-minute scale and 3-year sunrise and sunset time data of each station location. Eliminate empty data in photovoltaic output data.
[0222] 2) Calculate the starting time and ending time of each day's output of 6 stations in 3 years, and according to the characteristics of the problem data, identify and eliminate the data that do not meet the requirements at the starting and ending time, and obtain a new data set V.
[0223] 3) Based on the data set V and the sunrise and sunset time data of each station location for 3 years, calculate various randomness and volatility indicators.
[0224] 3.1) Substituting the output start time and end time data of the 6 stations calculated in step 2 for 3 years each...
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