Comparing the wind and solar power uncertainty in virtual power plants using IGDT method

Abstract

To decrease dependency on fossil fuels, almost all countries plan to invest more in renewable energy sources (RESs), e.g., wind and solar power plants. RESs provide substantial benefits for our climate and economy. However, there are still some technical and financial challenges to generate large amount of power through RESs. Increasing RESs capacities in a power system escalates the risk of instability. In this paper, RESs are deployed in the framework of virtual power plants (VPPs). The VPPs, as a new concept in power systems and electricity markets, have a substantial impact on increasing efficiency, engagement, and synergy effects of RESs in power systems. Optimal amounts of power generation of different generating units in a sample VPP are calculated and financial indicators are studied in this paper. To achieve more reasonable results with respect to stochastic nature of wind and solar generations, we apply Information Gap Decision Theory (IGDT) method to evaluate the system uncertainty. The results are achieved by GAMS software. Moreover, the impacts of different sources of uncertainties are compared with each other.