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Research On Multi-objective Collaborative Scheduling Of Smart Grid Wind Storage Combined System

Posted on:2017-02-19Degree:MasterType:Thesis
Country:ChinaCandidate:B Q DaiFull Text:PDF
GTID:2352330503486299Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
Large-scale acceptance of renewable energy power and intelligence has become the development trends and directions of future power. As one of the most potential development of renewable energy, the wind energy has run to a stage of large-scale development and utilization. However, contrast to conventional energy, the nature of uncertainty and intermittence of wind power leads to large fluctuations of the wind power output. The fluctuations in wind power will bring a great challenge to the integration of wind power and power grids. But, with the development of energy storage technology,smart grid can use the energy storage devices to solve this problem effectively and reduce many kings of disturbances caused by the wind power.Configuring the energy storage system for the wind farm can not only be used in smoothing the wind power output so as to improve the intelligent level of electric power network, but also can improve the benefits of wind farm with implementing the peak and valley price in the power market reform. At present, the pumped storage is the most extensive energy storage mode.This paper builds the joint operation model of wind farm and pumped storage power stations. First, the theoretical knowledge of wind power generation and pumped storage power station in smart grid will be introduced. Then, a single objective scheduling model of stabilizing the output fluctuation of wind storage combined system and is built, which is solved by particle swarm optimization algorithm. Based on this, a multi-objective coordinated scheduling model is established, which takes the minimized output fluctuation and the maximized income of wind farm as objective function. A virtual ideal molecular based on multi-objective improved particle swam optimization algorithm is proposed, and the established model is solved by the proposed algorithm. The simulation calculation is based on the historical data of the wind farm. The simulation results show that the output fluctuation of wind-storage generation can be effectively suppressed and the income of wind-storage hybrid system can be increased. Besides, the results also prove that wind-storage hybrid system is a good choice to absord the excess wind power,which make human maximize the development and utilization of wind energy resources.
Keywords/Search Tags:Smart grid, Wind power generation, Pumped storage power station, Improved particle swarm optimization algorithm, Multi-objective coordinated dispatch
PDF Full Text Request
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