Research on Temperature Prediction Method Based on Photovoltaic Battery Components

　　Author ：Iflowpower – Portable Power Station Supplier

Compared with hydrocharged, hydropower, thermal power, etc., has a greater impact on intermittent, volatility, periodic characteristics, to the power grid. A more accurate prediction of photovoltaic power generation will enable the power scheduling department to know in advance.

The photovoltaic power station has changed and timely adjusts the scheduled plan, thereby reducing the spare capacity of the system, reducing the cost of operating in power system. 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, the research of photovoltaic power generation prediction has been actively carried out, and photovoltaic power generation is performed by physical methods and statistical methods, and some results have been obtained.

However, most of these prediction methods do not consider the temperature rise factors of photovoltaic components during use, but directly use the ambient temperature as the operating temperature of the photovoltaic module, 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 the parameters of the performance of most characteristic materials are affected, which in turn affect the electrical energy parameters of the components, which will cause the assembly's opening voltage to decrease, and the short circuit current will increase slightly, general The result is a decrease in power.

As the temperature increases in 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; and the photocharge is slightly rising, approximately every Elevated 1 ° C, the battery's photovoltaic current added one thousandth. In general, the temperature is 1 ° C per liter, and the power decreases by 0.35%.

It can be seen that the component temperature is an important factor affecting the conversion efficiency of solar cell modules. In order to improve the accuracy of the photovoltaic power prediction, it is urgent to carry out battery components. Temperature prediction method.

1 Component Temperature Prediction Method 1.1 Component Temperature Influence Factor Analysis About the photovoltaic power station that has been put into operation, the temperature of the solar cell module is related to the ambient temperature, the 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 fell, the temperature of the solar battery module is also 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 monitoring of national energy solar power development (experiment) central roof (Nanjing Pukou, Slenette 118.7 °, latitude 32.17 °).

As can be seen from Figure 1, the temperature of the solar cell module 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, remote transmission of wireless and very high frequency (VHF), universal packet radio service (GPRS), satellite, etc., etc.

, etc., and With the ability to continue working 15D in no sun. Real-time automatic meteorological monitoring station according to the technical requirements such as solar resource assessment method, ground meteorological observation specification, and reference related experience in the construction of the wind tower, through the total radiation, direct radiation, scattering, direct radiation, and scattering of the photovoltaic power station micro-regional environment Meteorological elements such as radiation, component temperature, ambient temperature, wind speed, perform real-time data, and send data receiving platforms to the data receiving platform every 5min, and the storage [12].

Specific meteorological monitoring element and technical indicators 1 listed. After collecting historical data such as sun radiation, component temperature, ambient temperature, etc. of the photovoltaic power station, and the data can be screened and analyzed.

Establish a photovoltaic power station meteorological history database. Based on the photovoltaic power plant meteorological history database, the component temperature relationship established by the statistical method 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 components of the national energy solar power development (experiment) center roof photovoltaic station are: y = t + 0.

0214X + 0.971.3 Component temperature prediction with relational y Based on T + 0.

0214X + 0.97, enter the future total radiation data and ambient temperature data acquired from numerical weather forecast, predict the temperature value of the component; Kalman filter, use the ground real-time component temperature monitoring data to real-time correction of the prediction value , More accurate predict the temperature value of future components. 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 Analysis According to the above method, the national energy solar power development (experiment) central roof photovoltaic station has been put into operation, and the system operation is stable and reliable. In accumulated data, it is distinguished by 5 minutes.

The absolute error distribution proportional statistics of the predictive component temperature and actual component temperature data are compared. 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 photovoltaic power generation in my country in recent years, it is urgent to predict the power generation power of the photovoltaic power station to ensure the safety scheduling of the grid under large-scale photovoltaic power generation, and component temperature prediction is photovoltaic power prediction. An important part of the ring. The prediction shows that the temperature prediction method proposed in this paper is highly predicted, and the demand for engineering applications can be fully satisfied.