| Large-scale wind power penetration will certainly affect the safety and reliability of the grid, especially on the regional power grid whose network structure is relatively weak. So it is need to analyze the reliability of wind power and its impact on the grid theoretically and quantitative.According to the characteristics of a regional power grid, the impact of weather, environment, natural disasters and operating conditions, etc. on wind turbines, generators, transformers and transmission lines outage was studied. The calculation method of failure rate is proposed taking elements of weather, environment and operating conditions of grid into account. On this basis, the time-varying outage model of the wind turbine and major power system equipments were studied.According to the operating characteristics of the wind turbine, the three-state outage model of wind turbine based on Markov chain method was developed, inwhich the running, outage and derating status were taken into account. On this basis, the reliable model of wind farm was developed taking the randomness of the wind speed, wake effects of wind farm into account. Based on this model, the assessment methods and processes were given, and then the Monte Carlo method was emploied to assess the probabilistic characteristics of the active output of wind farms. On the basis of the three-state fault model, the time series model of wind status were given based on State-Duration sampling method. Based on ARMA model of wind speed, the reliable model of wind farm for sequential Monte Carlo simulation was developed taking account the complexity wake effects. For the multi-state model of wind turbine, the dual sampling methods of sequential Monte Carlo was proposed, and based on this method the active output of the wind farm reliability assessment was carried out.Procedures wwere ritten in MATLAB, through the simulation of installed capacity of 150MW wind farms verify the effectiveness and adaptability of the developed model and the proposed method.The reliability evaluation model of generation system was developed taking into account the wind power output randomness, random outages of conventional generator and randomness of load forecast. Monte-Carlo simulation often used in power generation system need large sample size and has low efficiency. So the scattered sampling technique which have [0,1] sub-interval divided into several sub-interval is applied into Monte-Carlo simulation, and in each sub-interval the system status and index need to calculate while they will be calculated one time in [0,1] by common sampling technique. The scattered sampling technique can increase the sampling frequency of a fault condition; thereby it could improve the efficiency of the sampling.The reliability model of wind farm was developed taking into account the randomness of wind speed, the correlation of multiple wind farms and outage and derating state of wind turbine. The reliability of power system is often evaluated based on Monte-Carlo simulation normally with random sampling, namely MC_RS, but it is not suitable for the power system containing wind power, especially when the wind farms are composed of a plurality of wind turbines, because it needs a large number of sample size and have low assessment efficiency. This paper proposes an improved assessment method by MC_LHS which is based on the combination of traditional MC(Monte Carlo) method and LHS(Latin Hypercube Sampling) method which could improve coverage of sample values for input spaces of random variables and increase the sampling efficiency. Using this integrated assessment method could improve assessment efficiency and reduce variance of repeated assessment results.The related assessment procedures were established in MATLAB, and the examples of 150MW wind farm,10-machine power system with two wind farms and improved IEEE-RTS79 systems were studied. The calculation and simulation results validate the built model and the proposed method effectiveness. |
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