Author ：Iflowpower – Portable Power Station Supplier
Compared with routine power supplies such as hydropower, electric power, thermal power and other conventional power supplies, there is a big impact on the power grid. A more accurate prediction of photovoltaic power generation will enable the power scheduling department to make ahead of the photovoltaic station to change the performance change and timely adjust the scheduling plan, thereby reducing the spare capacity of the system, reducing power system operating costs. This is an effective means of reducing the adverse effects of photovoltaic power generation on the grid, improve the scale of photovoltaic power generation in the system, and improve the effective means of operating safety and economic performance in the system.
At present, there have been actively developed the photovoltaic power prediction of photovoltaic power generation, and the photovoltaic power generation prediction is performed through physical approaches and statistical methods. However, most of these prediction methods do not consider the temperature rise factors in the use of photovoltaic components, but the ambient temperature is used as the working temperature of the photovoltaic assembly, which greatly affects the accuracy of photovoltaic power prediction. Similar to all other semiconductor devices, solar cells are very sensitive to temperature.
The increase in temperature will reduce the width of the silicon material, so that most of the parameters of the performance of the characterization materials are affected, which in turn affect the electrical performance parameters of the components, which will cause the assembly's open circuit voltage to decrease, and the short circuit current will increase slightly, overall The result is a decrease in power. As the temperature of the photovoltaic cell, the open circuit voltage is reduced, in the range of 20 ~ 100 ° C, about 1 ° C per liter, the voltage of the photovoltaic battery is reduced; the photovoltaic flow rate has a slight increase, about each Elevated 1 ° C, the battery's photovoltaic current added one thousandth. In general, the temperature is 1 ° C per liter, and the power is reduced by 0.
35%. It can be seen that the component temperature is a tight factor affecting the conversion efficiency of solar cell packages. In order to improve the accuracy of photovoltaic power prediction, it is urgent to carry out the temperature prediction method of battery pack.
1 Component Temperature Forecast Measures 1.1 Component Temperature Influence Factor Decomposition Confused PV Power Station I have put into operation, the temperature of the solar battery pack is related to the ambient temperature, solar radiation intensity. During the actual use, in addition to the ambient temperature change caused by the seasonal change, the solar radiation intensity varies in the range of 0 to 1300 W / m2 every day, the spectrum changes from AM∞ to AM1, the ambient temperature changes from the lowest sunrise temperature to the highest noon Temperature is declining, the temperature of the solar battery pack is also constantly changing.
Figure 1 shows the total radiation and components temperature and ambient temperature and ambient temperature and ambient temperature and ambient temperature and ambient temperature and ambient temperature and ambient temperature and ambient temperature surveillance of national energy solar power development (experimentation) central roof (Nanjing Pukou, Slenette 118.7 °, latitude 32.17 °).
As can be seen from Figure 1, the temperature of the solar battery pack is related to the ambient temperature, and the total radiation of the sun. 1.2 Component Temperature Statistical Modeling By building a real-time automatic weather monitoring station to obtain instantaneous solar radiation intensity, component temperature and ambient temperature, such as the ground layer of the national energy solar power planting center.
The monitoring station consists of a data acquisition module, a communication module, a meteorological sensor, and a solar power module. The system has a multi-channel access capability, according to the actual communication conditions of the site, the remote transmission of wireless and very high frequency (VHF), universal packet radio service (GPRS), satellite, etc., etc.
, and has a remote transmission of data for cable channels, and With the ability to continue working 15D without sunk. Real-time automatic meteorological monitoring station, according to the technical requirements such as solar resource assessment, the ground meteorological observation specification, and reference related related experience in the construction of the wind tower, through all weather sensors, the total radiation, straight radiation, straight radiation, straight radiation, Impact radiation, component temperature, ambient temperature, wind speed direction, etc. Detailed meteorological monitoring elements and technical indicators are listed in Table 1.
After collecting historical data such as the sun radiation, component temperature, ambient temperature and other historical data of the photovoltaic station, the data can be screened, and the meteorological history database of photovoltaic power station can be established. Based on the photovoltaic power plant meteorological history database, the component temperature relationship established by the statistical approach is as follows: Y = T + KX + C (1), y is the component temperature; T is ambient temperature; X is total radiation; K , C is the coefficient. Using the data statistic as of December 2011, the national energy solar power development (test) center roof photovoltaic station is: y = t + 0.
0214x + 0.971.3 Component temperature prediction with relational y = T + 0.
0214X + 0.97, input from the numerical weather forecast acquisition, the total radiation data and ambient temperature data, predict the component temperature value; Kalman filter, use ground real-time component temperature monitoring data to real-time correction of the prediction value Further, it is more accurate to predict the future component temperature value. Component Temperature Prediction Flow Chart As shown in Figure 2.
Figure 3 shows the total radiation and air temperature prediction flow chart of numerical weather forecast. 2 Example Decomposition According to the above-mentioned March 2012 National Energy Solar Power Generation R & D (Test) Central Roof Photo Water Supply, the system is running stable and reliable, in the accumulated data, 5min is time to distinguish Rate, the prediction component temperature, the actual component temperature data, the specific error distribution proportional decomposition is shown in Table 2. From Table 2, it can be concluded that the absolute error is in 5 ° C, which is 0.
9334, and the predictive effect is ideal. 3 Conclusion As the rapid aggregation of photovoltaic power generation in recent years, it is urgent to predict the power generation power of the photovoltaic power station to ensure the safety scheduling of grids under large-scale photovoltaic power generation, and component temperature prediction is photovoltaic power prediction. Middle one.
The prediction results declare that the prediction accuracy of the photovoltaic battery pack temperature prediction this paper is high, and it is possible to fully meet the demand for engineering use.
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