Scenario based technique applied to photovoltaic sources uncertainty

There is an increasing need to forecast power generated by photovoltaic sources in day-ahead power system operation. The electrical energy generated by these renewable sources is an uncertain variable and depends on solar irradiance, which is out of control and depends on climate conditions. The stochastic programming based on various scenarios is an efficient way to deal with such uncertainties. In this research paper, the long term hourly recorded irradiance data in 15 past years are applied to generate the next day's irradiance scenarios. Irradiance determines the operating point of PV panel as well as the generated electrical power. Also, the scenario generation method based on autoregressive and moving average time series is proposed. For decreasing the number of scenarios, backward reduction based on Kantorovich distance is applied. The obtained results confirm the accuracy and ability of the proposed method in forecasting the relevant data. ling ideal wind turbines, ideal rotating devices or ideal wind farms either numerically or experimentally and gives the maximum possible power extractions; thus, any improvement to the performance of a system can be made by this method.