电力系统自动化
電力繫統自動化
전력계통자동화
Automation of Electric Power Systems
2015年
22期
16-21,52
,共7页
陈逍潇%张粒子%杨萌%朱翊
陳逍瀟%張粒子%楊萌%硃翊
진소소%장입자%양맹%주익
光伏发电%功率波动%频谱分析%自动发电控制%备用
光伏髮電%功率波動%頻譜分析%自動髮電控製%備用
광복발전%공솔파동%빈보분석%자동발전공제%비용
photovoltaic(PV)power generation%power fluctuations%spectrum analysis%automatic generation control(AGC)%reserve
提出了基于自回归模型的频谱分析方法来分析光伏发电功率的波动特性。为获取足够分辨率的数据,以美国可再生能源实验室(NREL)的气象数据模拟仿真光伏阵列的出力,并用于分析不同时间尺度和空间尺度的光伏发电站的波动特性,确定光伏发电波动分量集中的时间尺度。研究表明,不同时间尺度的光伏发电波动量受天气影响显著,且随着光伏电站的规模扩大,不同光伏电站的整体出力也趋于平滑;此外,光伏发电波动主要集中在5 min 的时间尺度。在此基础上,验证了采用t 分布拟合关键时间尺度光伏发电波动量的概率分布效果良好,通过滚动平均法分离关键时间尺度的功率波动分量,并量化分析光伏发电并网引发的自动发电控制(AGC)备用需求。
提齣瞭基于自迴歸模型的頻譜分析方法來分析光伏髮電功率的波動特性。為穫取足夠分辨率的數據,以美國可再生能源實驗室(NREL)的氣象數據模擬倣真光伏陣列的齣力,併用于分析不同時間呎度和空間呎度的光伏髮電站的波動特性,確定光伏髮電波動分量集中的時間呎度。研究錶明,不同時間呎度的光伏髮電波動量受天氣影響顯著,且隨著光伏電站的規模擴大,不同光伏電站的整體齣力也趨于平滑;此外,光伏髮電波動主要集中在5 min 的時間呎度。在此基礎上,驗證瞭採用t 分佈擬閤關鍵時間呎度光伏髮電波動量的概率分佈效果良好,通過滾動平均法分離關鍵時間呎度的功率波動分量,併量化分析光伏髮電併網引髮的自動髮電控製(AGC)備用需求。
제출료기우자회귀모형적빈보분석방법래분석광복발전공솔적파동특성。위획취족구분변솔적수거,이미국가재생능원실험실(NREL)적기상수거모의방진광복진렬적출력,병용우분석불동시간척도화공간척도적광복발전참적파동특성,학정광복발전파동분량집중적시간척도。연구표명,불동시간척도적광복발전파동량수천기영향현저,차수착광복전참적규모확대,불동광복전참적정체출력야추우평활;차외,광복발전파동주요집중재5 min 적시간척도。재차기출상,험증료채용t 분포의합관건시간척도광복발전파동량적개솔분포효과량호,통과곤동평균법분리관건시간척도적공솔파동분량,병양화분석광복발전병망인발적자동발전공제(AGC)비용수구。
A spectrum analyzing method based on the autoregressive (AR) model is proposed to analyze the fluctuation characteristics of photovoltaic (PV) power.In order to obtain data with sufficient resolution,the PV array output is simulated based on meteorological data from the National Renewable Energy Laboratory (NREL) of America,which is used to analyze the fluctuation characteristics of PV power stations on different time scales and spatial scales,and determining the time scale on which the photovoltaic power fluctuation component is concentrated.Research shows that PV power fluctuations on different time scales are significantly affected by weather.With the expansion of PV power station scale,the whole output of different PV power stations tends to be smooth.In addition,PV power output fluctuation is mainly concentrated on the 5 min time scale.On this basis,the performance of fitting the probability distribution of PV power fluctuation on the critical time scale with t-distribution is verified.The power fluctuation component on the critical time scale is separated by a rolling average method.Finally,the automatic generation control(AGC)reserve demand caused by PV power grid-connection is quantitatively analyzed.