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The penetration of wind power into global electric power systems is steadily increasing, with the possibility of 30% to 80% of electrical energy coming from wind within the coming decades. At penetrations below 10% of electricity from wind, the impact of this variable resource on power system operations is manageable with historical operating strategies. As this penetration increases, new methods for operating the power system and electricity markets need to be developed. As part of this process, the expected impact of increased wind penetration needs to be better understood and quantified. This paper presents a comprehensive modeling framework, combining optimal power flow with Monte Carlo simulations used to quantify the impact of high levels of wind power generation in the power system. The impact on power system performance is analyzed in terms of generator dispatch patterns, electricity price and its standard deviation, CO2 emissions and amount of wind power spilled. Simulations with 10%, 20% and 30% wind penetration are analyzed for the IEEE 39 bus test system, with input data representing the New England region. Results show that wind power predominantly displaces natural gas fired generation across all scenarios. The inclusion of increasing amounts of wind can result in price spike events, as the system is required to dispatch down expensive demand in order to maintain the energy balance. These events are shown to be mitigated by the inclusion of demand response resources. Benefits include significant reductions in CO2 emissions, up to 75% reductions at 30% wind penetration, as compared to emissions with no wind integration.


Wind Power, Power System Operations, Variable Energy Resources, Demand Response



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10.4236/eng.2013.510A007 P

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.


Copyright © 2013 C. Lindsay Anderson, Judith B. Cardell. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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