Mohammad Rizwan
Delhi Technological University, India
Title: Short term PV power forecasting for demand response and storage control in smart grid energy management
Biography
Biography: Mohammad Rizwan
Abstract
The large scale penetration of photovoltaic power into sub-transmission and distribution grids can have a significant impact on a power system’s operation and stability because of inherently variable generation and weather dependent energy resources. It is well known that a sudden change in sunlight can initiate a rapid disconnection or reduction in a PV generating capacity. As the penetration of PV increases, this can lead to a problem of voltage variation and transient voltage instability in the case of a weak coupling with the grid. The large-scale penetration of PV units also has an impact on the short-term voltage and transient stability of a system, which is not only restricted to the distribution network but also influences the whole system. Solar photovoltaic forecasting can be used to mitigate these problems and provides the appropriate storage control and reduces the requirements of additional generating stations. In this work, fuzzy logic based one hour ahead short term forecasting of solar photovoltaic (PV) power using meteorological parameters is developed and presented. The solar photovoltaic power is forecasted using solar irradiance, ambient temperature, wind speed, humidity and type of the day or sky conditions as input parameters. The real data of PV plant has been used for the training, testing and validation purpose. The obtained results are evaluated on the basis of statistical indicators including RMSE, ARE, etc. The results of the proposed models are found better as compared to the existing models for different climatic zones. Further, the obtained results have been used for the demand response, storage control applications in the smart grid energy environment.