Research On Power Flow Optimization Of Power System Integrated With Large-scale Wind Farms

Considering the uncertainties of wind power such as randomness and correlations, itis necessary and urgent to consider about how to use wind energy rationally and ensurethe safety and reliability of the power supply. Optimal power flow(OPF) of power systemprovides an effective way to resolve this problem. In this thesis the following issuesrelated with the OPF problem of power system containing large-scale wind farms areresearched. The issues are grouping equivalent model of wind farm, modeling ofcorrelated wind speed among wind farms, optimal power flow model and calculation ofpower system containing wind farms. This thesis provides new modeling methods andalgorithm, which provides a new thought for the studies of OPF problem of powersystem containing wind farms.As to the influence of wake turbulence among wind turbines in a wind farm, a newequivalent modeling method considering wake effects is proposed. This method definesthe wake effect factor to show how one wind turbine is affected by the others, in addition,this factor can be used as a grouping rule of wind turbines. After grouping the windturbines and aggregating the same group, a wind farm model which is represented by fewturbines is obtained. Comparing with the traditional equivalence model, the simulationresults show that the equivalent model based on the proposed method more accuratelydescribes the power output of wind farms.Considering the correlations of wind speed in wind farms, a modeling method ofcorrelated wind speed based on Copula function is proposed. The modeling method usesCopula function to characterize the joint probability distribution of wind speed and togenerate correlated wind speed samples. Each wind farm’s output can be obtainedaccording to the wind turbine output characteristics. The result shows that the modeleffectively describes the correlated wind speed among wind farms. The multi-speedsamples obtained can be used to analyze the OPF problem of power system containedwind farm group.Traditional OPF model and algorithm mostly based on certainty principle, whilewind power brought uncertainty to power system. Considering the above-mentionedproblem, an optimal power flow model based on the theory of chance constrainedprogramming is proposed. To solve the proposed model, a particle swarm optimization algorithm(PSO) based on stochastic simulation technique is given.Wind farms’ access will inevitably have impact on the power system availabletransfer capability(ATC). Based on the above model, an ATC calculation model in windpower system based on optimal power flow is obtained. This model is solved by theproposed algorithm. Taking IEEE30-bus system and IEEE118-bus system as examples,the influence of issues on the results of ATC calculation is analyzed. The issues are windspeed randomness and correlations, the sites of wind farms and the chance constraintcredit level. The analysis provides reference and basis for the planning and operation ofpower system contained wind farms.