Thermal power load prediction system based on regional meteorology
A load forecasting and thermal power technology, applied in forecasting, system integration technology, information technology support system, etc., can solve problems such as inconvenient dispatching of load trends, reduce wind curtailment and solar power curtailment, improve thermal power compensation benefits, and improve rationality and efficiency. economical effect
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Embodiment 1
[0038] refer to Figure 1 to Figure 3 , a thermal power load forecasting system based on regional weather, including the following steps:
[0039] S1. Accumulate big data: collect thermal power load rate of thermal power plants and wind speed data of new energy wind power plants;
[0040] S2. Carry out data modeling: study the data of wind speed change and thermal power load rate change in the area, conduct linear relationship analysis, and form a preliminary model;
[0041] S3. Carry out the unit deep adjustment test.
[0042] Among them, S2 performs data modeling based on linear regression algorithm and gradient descent method to fit the linear relationship between wind power and thermal power, specifically:
[0043] Step 1. Wind-fire synergy parameter linear fitting:
[0044] Synergize the peak value of wind power with the peak value of thermal power, and convert it into a parameter fitting algorithm of wind power and peak value of thermal power to achieve wind-fire coor...
Embodiment 2
[0063] refer to Figure 1 to Figure 3 , this technical solution combines the wind field and the historical peak regulation of thermal power, and proposes to fit the linear relationship between wind power and thermal power based on linear regression algorithm and gradient descent method. The overall implementation process is described in detail as follows.
[0064] 1. Wind-fire synergy parameter linear fitting
[0065] It can be seen from the historical data of the north-south wind farm that the wind power output is a relatively stable value within a certain range, that is to say, the value of wind power and wind power is a stable corresponding relationship. Combining this law, we can On the basis of wind speed prediction, the peak value of electric power and wind force value are one-to-one correspondence, and the corresponding relationship between thermal power peak value and electric power peak value can be reduced to the relationship between fire point peak value and wind f...
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