【文章內(nèi)容簡(jiǎn)介】 otal installed capacity are Germany (20 621 MW), Spain (11 615MW), the USA (11603MW), India(6270 MW) and Denmark (3 136 MW). Thirteen countries around the world can now be counted among those with over 1000 MW of wind capacity, with France and Canada reaching this threshold in 2020. shows the top 10 cumulative installed capacity of the world until December, 沈陽(yáng)農(nóng)業(yè)大學(xué)學(xué)士學(xué)位論文外文翻譯 2020[2]. China started to develop wind power very late. It stepped into the stage of mercialized development and scale construction only in 1990s. Accumulated and newly added installed generating capacity over the years is shown in singleunit capacity increased from 100 kW, 200 kW, and 300 kW to 600 kW, 750 kW, and 1500 kW step by step. Fig. 1 Top 10 cumulative installed capacity of the world until December,2020 Fig. 2 Accumulative and newlyadded installed capacity of wind power in China China doubled more than its total installed capacity by installing 1 347 MW of wind energy in 2020, a 70% increase from last year’s figure. This brings China up to 2 604 MW of capacity, making it the sixth largest market world wide. the Chinese market has grown substantially in 2020, and this growth is expected to continue and speed up. According to the list of approved projects and those under construction, more than 1 500 MW will be installed in 2020. The goal for wind power in China by the end of 2020 is 5000 MW[3]. 2． Characteristics of wind power generation From the point of view of wind energy, the most striking characteristic of the wind resource is its variability. The stochastic variation of wind farms outputs root mainly in fluctuation of the wind 風(fēng)力發(fā)電對(duì)電力系統(tǒng)的影響 speeds and directions. The wind is highly variable, both geographically and temporally. Furthermore this variability persists over a very wide range of scales, both in space and time. The wind speed varies continuously as a function of time and height. The time scales of wind variations are presented in as a wind frequency spectrum[4]. The turbulent peak is caused by gusts in the sub second to minute range. The diurnal peak depends on daily wind speed variations and the synoptic peak depends on changing weather patterns, which typically vary daily to weekly but include also seasonal cycles. Fig. 3 Wind spectrum farm Brookhaven based on work by van der Hoven From a power system perspective, the turbulent peak may affect the power quality of wind power generation. The influence of turbulences on power quality depends very much on the turbine technology applied. Variablespeed wind turbines, for instance, may absorb shortterm power variations by the immediate storage of energy in the rotating masses of wind turbine drive trains. That means that the power output is smoother than strongly gridcoupled turbines, fixedspeed wind turbines. Diurnal and synoptic peaks, however, may affect the longterm balancing of power system, in which wind speed forecasts plays a significant role. Another important issue is the longterm variations of the wind resources. The wind speed up to the height of the hub should be known to calculate the wind farm output. A number of measurements of wind speeds show that wind speeds are mostly mild in a year。 their probabilities between 0 and 25m/s are considerable。 most of the average annual wind speeds subject to the Wei bull distribution[5], as in formula(1). (1) where: v is average wind speed。 k is shape parameter。 c is scale parameter. 沈陽(yáng)農(nóng)業(yè)大學(xué)學(xué)士學(xué)位論文外文翻譯 The relationship between the wind turbine output Pw and the wind speed up to the height of the hub v can be expressed approximately as the curve of wind turbine’s outputs vs. wind speed or a subsection function, as in formula (2). (2) where: Pw is rated output of the wind turbine。 v is wind speed up to the height of the hub。 VCI is cutin wind speed。 VCO is cutout wind speed。 VR is rated wind speed. 3． Influence of wind power generation on power systems High peration of wind power in the power systems faces fundamental technical limits with regard to the integration of largescale wind farms to the grid. The influence of wind power generation on power systems includes active and reactive power flow, voltage, system stability, power quality, shortcircuit capacity, system reserve and infrastructure due to the characteristics of highcapacity, dynamic and stochastic performance of wind power generation. Technically, it influences the gird in the following ways and has to be studied in detail: （ 1） Active and Reactive Power Flow. Wind power is a kind of intermittent and stochastic power source, which will plicate the power flow. Because many wind farms are built far away from load centers in order to capture more wind energy, there is always some obstacle of transmitting wind power. Some transmission or distribution lines and other electrical equipments may be overloaded when the additional wind power generation is introduced. So it should be ensured that the interconnecting transmission or distribution lines will not be overloaded. Both active and reactive power requirements should be investigated. Reactive power should be generated not only at PCC, but also throughout the work, and should be pensated locally[6]. The methods utilized for analysis of conventional generators are certain and ignore the uncertainty of wind speed and load forecasts. Therefore, the probabilistic method is more suitable for wind power generation. This model is based on the wind speed distribution, such as formula (1). The constraints are described by probabilistic forms and the expected values of parameters, such as voltages and powers can be puted. （ 2） Voltage Regulation. 風(fēng)力發(fā)電對(duì)電力系統(tǒng)的影響 Once a wind farm has identified its site, the point at which connection to the grid must be identified. Small wind farm can connect at lower