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The fire produce harms and damage environment. The fire assessment of photovoltaic power stations is based on testimony, photographic and some next records of during fire, data recorded by Weather Station of photovoltaic’ s station and from inspection of fireplace after extinguishing of fire.

This paper makes a prediction about the daily power generation of the photovoltaic power station in Wuhan International Exhibition Center by the application of multivariable grey theory model and compares the forecasted results with the real results. This research proves that the application of the theory of multivariable grey model on short-term prediction of photovoltaic power generation can achieve a good prediction effect, which also has certain engineering application value.

Grid-connected PV power station is one of the most important applications of photovoltaic system, generating low cost and high-quality electric power without non-renewable energy, as well as relaxing the tightness of daytime power demand. In China, it is usually installed on remote open area for low cost to guarantee the abundant solar power. However, this kind of place usually comes with tough weather conditions. In this paper, the property of the PV test field is estimated by its output characteristic. One inevitable and two avoidable reasons which affect the plant output are proposed. Firstly, the inevitable factor is weather, and the assessment analyzing the performance of PV power system under different weather conditions, such as sunny, cloudy, rainy and snowy is then presented. Secondly, losses owing to the mounting type and partial shading, which can be reduced by well designing and installing, are also mentioned and analyzed.

As the installed capacity of photovoltaic power station is growing, the power prediction techonology is of great important to reduce the random damage to the power system. A prediction model using neural network is proposed in the paper, the solar radiation model is adopt to ensure the accuracy of the prediction results in clear sky contions.Through the analysis of photovoltaic power station output power influence factors, the the solar radiation intensity, humidity and temperature are chosen as the input of the neural network prediction model.At the same time, in order to improve accuracy the photovoltaic power station power prediction model, the power adopt numerical weather forecast information. And the prediction model is tested by the photovoltaic power station historical operation data, and the short-term power prediction has a good performance.

According to the requirements of the PV station remote monitoring system, such as big information flow, far distance transmission, high-performance, this article has designed a remote PV station monitoring system based on CAN bus and GPRS with mechanical properties. After lucubrated CAN bus and GPRS communication technology, this article details the hardware circuit of the slave computer, the communication protocol of CAN bus and the design of communication network. It has solved the problems that bad real-time, low degree of automation, few nodes can be accommodated, weak anti-interference ability which exits in the past design of PV station remote monitoring system.

The output of photovoltaic generation system is influenced by the factors such as solar radiation, temperature and so on. So the change of photovoltaic generation power is a non-stationary random process that will impact on the grid. In order to promote large-scale photovoltaic generation connected to the grid, we need to configure energy storage devices for photovoltaic power station and in order to coordinate the allocation of photovoltaic system with energy storage system, we requires a thorough understanding of output characteristics of the photovoltaic system. This paper firstly analyzes the influence brought by the large-scale photovoltaic generation system connected to the grid and then introduces the effect factors of photovoltaic output. Based on the history data of the 100 kWp photovoltaic power station and the statistical method, the paper qualitatively and quantitatively analyzes the photovoltaic output performance; finally puts forward the PV output power evaluation index. The conclusions of this study will provide powerful data references for follow-up studies and have practical value.

This paper made some researches of modeling on the systems of the large-scale photovoltaic（PV） power station, and established the PV model, the rectifier and inverter circuits and so on. Using MATLAB and PSASP, simulation and analysis of grid-connected characteristics about the large-scale PV power station in weak grid systems were carried out, focusing on the transient stability in the fault condition of the line-side and the power quality. These two simulation results had good consistency, which demonstrated the accuracy of the large-scale PV power station model in this paper and the analysis of its grid-connected characteristics. The conclusion of this paper will provide some theoretical basis of improving the stability of grid-connected and reducing the harmonic current in weak grid systems, and will also provide some theoretical basis and the guide of grid-connected for the new energy strategy of our country in the future.