Studies On The Effects Of Wind Power Integration On The Reliability And Reserve Capacity Of Electric Power System

As a main green energy source in 21st century, Wind power also is one of the most important alternations for non-renewable energy. Along with the rapid development of wind power technology and equipment level, wind power generation has become the most mature new energy technology with large-scale development conditions and has prospects for commercial development. However, for the high randomness and volatility of wind power, the wind power penetration connected to power system presents severe fluctuation characteristic. With the increase of wind power penetration, grid-connected wind farm has more and more serious influences on power system and can even destroys the economic, secure, stable and reliable operating state and makes the operation and dispatching of power system specifically difficult.This paper mainly analyzes the influence on the power system reliability of large-scale grid-connected wind farm and finds out the optimum of system reserve in order to achieve unifying the maximum utilization of new energy and meanwhile high reliability of power systemThe wind speed forecasting model based on neural network is built in this paper. At first, the correlation between wind speed and meteorological information is analyzed, and the most important meteorological factor which influences wind speed is found out. Then the change characteristic of the wind is studied, and the seasonal periodicity and time continuity of wind speed are pointed out. In order to improve the accuracy of the model, the sample most similar to forecasting day is selected and the wind speed model values in forecasting day are generated using neural network method. The wind speed forecasting model can reflect the local wind speed characteristics and the generated data is consistent with historical data in wind speed probability distribution, wind speed annual variation and other characteristics. So the model is applicable to reliability evaluation of power system with grid-connect wind farm.Then using Monte Carlo method as a technical measure, the reliability evaluation model of power system with grid-connect wind farm is built. Through sequential sampling, Monte Carlo method gets a state of system. By evaluating on the system, the reliability parameters in the state are also gained. If the sampling satisfies certain accuracy and reaches a certain number of times, a large number of states and their reliability data will be obtained. The reliability level of system can be determined after doing statistic analysis on these reliability data. The influence of wind power integrated is observed by changing the way in which wind power connected to the system. The example shows that with the difference of wind power capacity and access point, the influences on power system reliability are also different.Afterwards, the system reserve with grid-connected wind is optimized. Assume that the wind power capacity and access point is fixed, the value and location of system reserve capacity have different contribution to the power system reliability. This paper adopts Particle Swarm Optimal algorithm to optimize farm. In this way, the influence on power system reliability of wind power can be stabilized using minimum system reserve. Moreover, this paper also evaluates the reliability of Shanghai generating system with grid-connected wind farm and estimates the reserve requirement with different amount of wind power.The research work of this paper is supported by the project of Shanghai Power Company named"the operation model and risk management of power system with large-scale grid-connected wind farm".