电网技术
電網技術
전망기술
Power System Technology
2015年
9期
2404-2410
,共7页
苏展%徐谦%孙黎滢%周明%李庚银
囌展%徐謙%孫黎瀅%週明%李庚銀
소전%서겸%손려형%주명%리경은
双馈风机%随机激励%小干扰稳定%随机微分方程
雙饋風機%隨機激勵%小榦擾穩定%隨機微分方程
쌍궤풍궤%수궤격려%소간우은정%수궤미분방정
double fed induction generator%stochastic excitation%small signal stability%stochastic differential equation
针对风功率随机波动给电力系统稳定分析带来的新问题,建立了计及风功率随机波动的双馈感应发电机(doubly fed induction generator,DFIG)的详细动态模型,以及用于分析含 DFIG的电力系统小干扰随机稳定性的随机微分方程.给出了随机稳定的判据,并推导出系统状态量期望和方差的解析表达式.通过对单机无穷大和IEEE 3机9节点系统进行算例分析,验证了所建随机模型的可行性.从理论上分析了风功率随机波动对系统状态变量的影响,还使用 Euler-Maruyama 数值方法验证了理论分析的正确性.结果表明,机械功率随机波动对不同状态变量的影响不同.状态变量的波动幅度由系统潮流、系统参数、随机项波动强度和时间决定.而在多机系统中,风机机械功率波动也会对系统中其他动态元件的状态变量造成影响.
針對風功率隨機波動給電力繫統穩定分析帶來的新問題,建立瞭計及風功率隨機波動的雙饋感應髮電機(doubly fed induction generator,DFIG)的詳細動態模型,以及用于分析含 DFIG的電力繫統小榦擾隨機穩定性的隨機微分方程.給齣瞭隨機穩定的判據,併推導齣繫統狀態量期望和方差的解析錶達式.通過對單機無窮大和IEEE 3機9節點繫統進行算例分析,驗證瞭所建隨機模型的可行性.從理論上分析瞭風功率隨機波動對繫統狀態變量的影響,還使用 Euler-Maruyama 數值方法驗證瞭理論分析的正確性.結果錶明,機械功率隨機波動對不同狀態變量的影響不同.狀態變量的波動幅度由繫統潮流、繫統參數、隨機項波動彊度和時間決定.而在多機繫統中,風機機械功率波動也會對繫統中其他動態元件的狀態變量造成影響.
침대풍공솔수궤파동급전력계통은정분석대래적신문제,건립료계급풍공솔수궤파동적쌍궤감응발전궤(doubly fed induction generator,DFIG)적상세동태모형,이급용우분석함 DFIG적전력계통소간우수궤은정성적수궤미분방정.급출료수궤은정적판거,병추도출계통상태량기망화방차적해석표체식.통과대단궤무궁대화IEEE 3궤9절점계통진행산례분석,험증료소건수궤모형적가행성.종이론상분석료풍공솔수궤파동대계통상태변량적영향,환사용 Euler-Maruyama 수치방법험증료이론분석적정학성.결과표명,궤계공솔수궤파동대불동상태변량적영향불동.상태변량적파동폭도유계통조류、계통삼수、수궤항파동강도화시간결정.이재다궤계통중,풍궤궤계공솔파동야회대계통중기타동태원건적상태변량조성영향.
Aimed at new problems induced by wind power random fluctuations brought to power system small signal stability, a detailed stochastic dynamic model of doubly fed induction generator (DFIG) was proposed and stochastic differential equations of power systems with DFIG were established to analyze small signal stochastic stability. Stochastic stable criterion of system was given and state variables' expectation and variance were deduced. Then an example analysis on single machine infinite bus and IEEE 3 machine 9-bus system were performed to verify feasibility of the proposed DFIG stochastic model. The impacts of wind power fluctuation on state variables were analyzed theoretically. Finally, the theoretical analysis was verified using Euler-Maruyama (EM) numerical method. Results showed that random fluctuation of mechanical power has different impacts on state variables. Fluctuation variance of state variables is determined by power flow, network parameters, time and intensity of random excitation. For multi-machine system, wind power fluctuation also has impacts on state variables of other dynamic elements.