Abstract
Large penetration of wind power in congested and weak power networks could lead to severe problems due to variation in wind speed. Hence, severe voltage and frequency fluctuations occur due to fast intermittent power generation. In this work, quasi-static models have been implemented to investigate the effect of wind power variations on classical power generation as well as network frequency. Probabilistic PHEVs models are deployed to absorb wind power fluctuations and improve system frequency response. The developed control strategy for PHEVs demand management is integrated with existing control infrastructure on both power plant and center control levels. The developed control reduces frequency fluctuations due to fast wind power transients and guarantees charging of the PHEVs plugged into the system by the end of their connection period. The developed quasi-static time-series (QSTS) simulation model accounts for primary control, optimized unit participation, and economic dispatch. The frequency is represented as state variable whereas the continuous power-flow is solved using Gauss-Seidel method. PHEVs are aggregated through the network based on probabilistic distribution of both traveling distance and parking time. The results calculated for the IEEE 30-bus shows that integration of PHEVs with wind power energy systems improves the system frequency response and provide fast and dynamic power supply in case of power shortcoming along the day.