Probabilistic power quality indices for electric grids with increased penetration level of wind power generation

• Power quality is analyzed for wind turbine to find harmonics, voltage sag and flicker.
• Wind speed stochastic model using discrete Markov analysis is developed.
• Power quality indices are incorporated with discrete Markov analysis to find probabilistic power quality indices.
• Probabilistic power quality indices were estimated from real measured data from Zafarana site, Red sea, Egypt.

In future electric grids it is expected that the share of power produced by renewable energy systems will increase to supply large deficits in power demand. Wind energy is one of the most important sources of renewable energy generation systems. With increased penetration level of wind energy conversion systems in modern electric grid, the quality of power will inevitably be affected. Power quality (PQ) indices are used to quantify the quality of the power. They serve as the basis for comparing negative impacts of different disturbances on power networks. Previous research of PQ indices with electric grids including wind energy sources was mainly based on fixed wind speed. Therefore, the PQ indices were calculated as instantaneous values that do not reflect the overall power quality impact of the grid connected wind energy systems. The main objective of this paper is to propose new probabilistic PQ indices for electric grids including wind energy systems. The proposed PQ indices combine both the probabilistic nature of wind speed using discrete Markov analysis and the electric grid behavior. The main PQ indices proposed are those concerning harmonics, flicker, and voltage sag. The developed indices are suitable for electric grids that include high penetration level of wind based power sources. The method used is general and can be applied to other power quality indices or power system performance indices.