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Optimization Of Energy Storage System Capacity For Wind Farms Based On Cost

Posted on:2018-04-03Degree:MasterType:Thesis
Country:ChinaCandidate:Y M ChenFull Text:PDF
GTID:2322330533961677Subject:Master of Engineering
Abstract/Summary:PDF Full Text Request
Serious pollution of the environment was caused because of the sharp reduction of fossil energy reserves and the excessive using of human-beings,which has become one of the mainly problems in the current for human economic and social development.The development of new type of clean and pollution-free energy has become an important solution to solve the energy emergency and climate changing problems.Wind energy has a wide range of distribution on earth,also can be largely mined,the most important is wind energy is totally clean and pollution-free.So,wind energy has a great commercial potential and it may be large-scale applicate.However,despite the gradual maturity of wind power technology,some shortcomings of wind energy itself still cannot be solved,such as its volatility,intermittent,anti-peaking and difficult to predict.These natures of wind power have brought many problems to power grid.Not only has a significant negative impact on power quality,but also affect the sTablele operation of the power grid.All these impacts resist the further promotion and development of wind power,as well as new energy.Energy storage system is a kind of energy conversion device,it can make quick conversion between electrical energy and other forms of energy.When running with wind farms,energy storage system can be a good solution to deal with wind power fluctuations,intermittent,anti-peak and other characteristics of the impact,sTableilizing the fluctuations,achieving "cut peak fill valley" function and solving the power quality problem of power grid.It is also a practical and effective solution the large-scale use of wind energy in power grid system.Based on the existing theories and data,the optimization of capacity and power of energy storage system based on the annual cost is studied in this paper.Firstly,the characteristics of wind power are listed.The fluctuation,anti-peaking and unpredicTableility of wind power are analyzed by using the data of a wind farm located in East of China.Then,the characteristics of the energy storage system are analyzed.The energy devices system which is the most suiTablele as the energy storage of the wind farm is pointed through the analysis and comparison of the characteristics of various energy storage devices.Secondly,a wind power output model considering the prediction error is proposed according to the existing errors of wind power prediction.The wind power output forecasting model and the load demand are used to predict the power demand of the wind farm,then the charge and discharge strategy of the energy storage system under different rated power and capacity parameters is analyzed.The expression of the charge and discharge power at any time of the energy storage system is obtained based on different strategies.Finally,the rated power and rated capacity of the energy storage system are optimized.An objective function based on the annual cost,the amount of abandoned wind energy and the backup power generator capacity is obtained,the constraint condition and the evaluation index are also obtained.The results are calculated based on the particle swarm optimization.Optimal rated power and rated capacity are got according to the actual data of a typical wind farm,complete energy storage methods in the evaluation of indicators for evaluation and analysis.The optimal solution of the rated power and capacity of the energy storage system is proved that much more better than old way,which maximize power and capacity.Rate abandoned wind energy are only slightly increased,but the cost of energy storage system is greatly reduced,which indirectly improve the wind farm benefits,improve owner's intention of adding energy storage system.
Keywords/Search Tags:Wind farm, energy storage system, particle swarm optimization, joint operation, capacity optimization
PDF Full Text Request
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