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Research Of Coordinated Control Of Reactive Voltage Considering Reactive Power Regulation Of DFIG Wind Farm

Posted on:2018-09-30Degree:MasterType:Thesis
Country:ChinaCandidate:J Q ZhangFull Text:PDF
GTID:2322330512979251Subject:Power system and its automation
Abstract/Summary:PDF Full Text Request
As a new renewable energy power generation technology,wind power generation has become one of the most prospected distributed generation technology because of its wide distribution,non-pollution and inexhaustible.However,the instability of wind power output will bring some impact on the safety and stability,economic operation and power quality of the traditional power system,while the large scale wind farms access to the power system.The problem of reactive power and voltage is an important research direction.As the main model of wind farms in China,the doubly fed induction generator(DFIG)has the ability of active and reactive power decoupling control and has realized the continuous regulation of active and reactive power.Therefore,a reactive power and voltage coordination control strategy based on the reactive power optimization on steady state is studied from the aspects of static and dynamic reactive power optimization in this paper.That considers the use of reactive power adjustment capability of DFIG wind farm itself and the coordination with the traditional reactive power compensation device.In this paper,the relationship between active and reactive power of DFIG is analyzed based on the basic principle of DFIG.Based on the derivation of the mathematical model of DFIG,the calculation method of its active and reactive power is obtained.Moreover,the factors that affect the reactive power limit of DFIG are analyzed in detail to solve the reactive power regulation range of DFIG under different wind speed conditions.The whole wind farm output power is obtained by the lumped parameter model,which lays the foundation for the following work.Because the DFIG wind farm has the ability of reactive power regulation,it is considered as the reactive power source to participate in the power system static reactive power optimization.The traditional reactive power optimization model and the reactive power optimization model in electric power market are compared.The former considers only the active network loss of the system,while the latter considers the cost of wind farm reactive power compensation based on the former.A reactive power optimization model considering wind farm reactive power regulation is established by determining a suitable price for reactive power to mobilize the enthusiasm of the reactive power suppliers and reduce the reactive power cost of grid.Taking IEEE-30 node system as an example,the model is solved by improved particle swarm optimization(PSO)algorithm to verify the effectiveness and economy of the proposed method.The dynamic reactive power optimization method has considered the time variation of wind farm output and the operation times of the shunt reactive power compensation device,such as capacitor bank and the tap of the on-load-tap-changing transformer.Through the subsection of the wind power prediction curve,the discrete devices in each segment are kept in order to reduce the number of actions.The dynamic reactive power optimization model is established,which takes the minimum square sum of the system voltage deviation,the least number of discrete device actions and the maximum of continuous equipment reactive power margin as the objective function.That gives full play to the basic role of reactive power compensation based on discrete equipment and use reactive power reserve of the continuous equipment to deal with wind speed fluctuations,to ensure the safe and stable operation of the power system.The model is solved by multi-objective PSO algorithm,and the final solution is selected from the Pareto set by the analytic hierarchy process(AHP).The feasibility of the proposed model is verified by taking IEEE-30 node system as an example.
Keywords/Search Tags:DFIG, reactive power limit, reactive power optimization, PSO algorithm
PDF Full Text Request
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