Solar power forecasting

Solar power forecasting involves knowledge of the Sun´s path, the atmosphere's condition, the scattering processes and the characteristics of a solar energy plant which utilizes the Sun's energy to create solar power. Solar photovoltaic systems transform solar energy into electric power. The power output depends on the incoming radiation and on the solar panel characteristics. Photovoltaic power production is increasing nowadays. Forecast information is essential for an efficient use, the management of the electricity grid and for solar energy trading. Common solar forecasting method include stochastic learning method, local and remote sensing method, and hybrid method (Chu et al. 2016). Solar power forecasting involves knowledge of the Sun´s path, the atmosphere's condition, the scattering processes and the characteristics of a solar energy plant which utilizes the Sun's energy to create solar power. Solar photovoltaic systems transform solar energy into electric power. The power output depends on the incoming radiation and on the solar panel characteristics. Photovoltaic power production is increasing nowadays. Forecast information is essential for an efficient use, the management of the electricity grid and for solar energy trading. Common solar forecasting method include stochastic learning method, local and remote sensing method, and hybrid method (Chu et al. 2016). The energy generation forecasting problem is closely linked to the problem of weather variables forecasting. Indeed, this problem is usually split into two parts, on one hand focusing on the forecasting of solar PV or any other meteorological variable and on the other hand estimating the amount of energy that a concrete power plant will produce with the estimated meteorological resource.In general, the way to deal with this difficult problem is usually related to the spatial and temporal scales we are interested in, which yields to different approaches that can be found in the literature. In this sense, it is useful to classify these techniques depending on the forecasting horizon, so it is possible to distinguish between now-casting (forecasting 3–4 hours ahead), short-term forecasting (up to 7 days ahead) and long-term forecasting (months, years…)Solar radiation closely follows the physical and biological development of the earth. Its spatial and sequential heterogeneity powerfully influence the forcing of environmental and hydrological organisms by manipulating air temperature, soil moisture and vapor transpiration, snow cover and lots of photochemical procedures. Therefore, solar radiation drives place efficiency and plant life allotment, organism a key feature in undeveloped and forestry sciences that be obliged to be known precisely. The quantity of solar radiation obtainable at the earth’ surface is at the outset controlled at worldwide balance, organism above all precious by the Sun Earth geometry and the atmosphere. On the other hand, a complete explanation of its freedom time unpredictability require deliberation of limited procedure which frequently turn out to be also applicable, as is the casing in mountainous region. Predominantly, limited territory adjust the inward bound solar radiation by shadow casts, slope of elevation, surface gradient and compass reading, as a result, precise spatial model of inward bound solar radiation be supposed to regard as the pressure of the terrain surface. In the final time, more than a few events to consist of the confined terrain special effects in the solar radiation countryside have been projected, such as the use of Geographical Information Systems (GIS), artificial intelligence or post dispensation of satellite stand technique. Solar radiation can be also evaluated using numerical weather forecast (NWP) models. Nevertheless, the space and time balance determined with them and the incomplete computational ability frequently avoid the deliberation of terrain connected property.