CAJ | 학술논문

随着风电机组大规模并网，风电对电力系统的影响逐渐显现。我国多次发生风电机组连锁脱网事故，影响了电力系统的运行。为了预警风电机组脱网，保证电力系统的安全运行，提出风电机组脱网的风险评估模型。由于故障组合数量爆炸，不可能在线分析所有的可能故障。因此，<br>　　建立风电机组脱网指标，来衡量发生故障时风电机组的脱网概率。该指标不但考虑电力系统故障，同时也考虑了风电场内部故障。根据脱网指标和风电场到故障点的电气距离，对预想故障进行排序和筛选，生成有效预想故障子集；仅对有效故障集内的可能故障进行在线风险评估和风电机组脱网预警。该模型可以给出风电机组脱网容量。对某省电网在线数据仿真分析，验证了理论方法的正确性和预警模型有效性。
수착풍전궤조대규모병망，풍전대전력계통적영향축점현현。아국다차발생풍전궤조련쇄탈망사고，영향료전력계통적운행。위료예경풍전궤조탈망，보증전력계통적안전운행，제출풍전궤조탈망적풍험평고모형。유우고장조합수량폭작，불가능재선분석소유적가능고장。인차，<br>　　건립풍전궤조탈망지표，래형량발생고장시풍전궤조적탈망개솔。해지표불단고필전력계통고장，동시야고필료풍전장내부고장。근거탈망지표화풍전장도고장점적전기거리，대예상고장진행배서화사선，생성유효예상고장자집；부대유효고장집내적가능고장진행재선풍험평고화풍전궤조탈망예경。해모형가이급출풍전궤조탈망용량。대모성전망재선수거방진분석，험증료이론방법적정학성화예경모형유효성。
With wind farms being rapidly integrated into power systems, the impacts of wind power on power system operation obviously emerges. Wind generator trip-off happens frequently in China, which has impacted power system operation. In order to keep a power system with wind generation operating safely, a risk assessment model for wind generator trip-off was established. It is impossible to calculate all of the possible faults online, because of the explosion of faults and the consumption of calculation time. Therefore, the wind generator trip-off index was designed to calculate the probability of wind generator trip-off when a fault occurs. Besides considering power system states, the failure in the wind farms was also taken into account based on the actual trip-off statistics in the index. The anticipating fault set was generated based on the index and the electrical distance from wind farm to fault location. The fault subset, which may cause wind generator trip-off, was sorted and filtered from the fault set by the probability of tripping off. Therefore, only the faults in the subset are scanning on line, and providing warning information simultaneously. The risk assessment model for wind generator trip-off can calculate wind farm trip-off capacity, and analyze the state of system stability. Both the accuracy and effectiveness of the proposed risk assessment model are verified by simulation results from Gansu Power Grid of China online data.