The question of determining the possible capacity of a photovoltaic power plant is very acute due to the growing demand for renewable energy, coupled with the fact that during the day we have limited time to generate energy from such a source. Thus, based on the obtained analytical data, which allows to predict weather conditions, it is possible to regulate the amount of energy supplied to the network in a certain way due to more maneuverable power plants. In previous years, electrical engineering scientists and researchers from different countries have developed and implemented methods for determining weather conditions, such as clouds, air temperature, atmospheric dust and others, as well as their impact on the energy output of a solar power plant. A photovoltaic panel is a complex nonlinear object with many variables. In addition to the structural features of the module, the output is most affected by solar radiation and panel temperature. When researching the prediction of the amount of energy produced, it is important to find sufficiently reliable and consistent data. At the forefront of these issues are US universities and research centers. For example, the University of Nevada in Las Vegas, in 2006 put into operation a set of measurements of weather conditions: the level of sunlight, ambient temperature, wind speed, humidity and others. When calculating the power generated by the panels, it is assumed that the system operates at the point of maximum power. The scheme works as follows: we set the values of temperature (Temperature) and irradiation (Irradiance); we apply voltage to the output terminals of the array by changing its value from 0 to Voc. We take current readings at each point, we find the power for each point, we find the maximum among the obtained array of points. Repeat over the entire range of input values. Thus, we obtain a graph of the output power of Figs. 4 pre-considering the losses in the inverter.
Solar Power Plant Generation Short-Term Forecasting Model
