CAJ | 학술논문

传统的电网可靠性评估采用固定不变的元件年均故障率模型，难以适应电力系统短期风险评估需求。电网故障与灾害性天气具有较强的时间相关性，气象灾害具有明显的季节性特征，因此电网风险也具有时间波动性。在描述电网元件故障参数时，需要从原来的一维横向连续时间下的年均值模型，拓展到考虑历史同期(纵向)时间和导致故障的因素，特别是外部气象环境因素，以便更准确地描述时间及环境相依的电网故障率。在传统年均值模型的基础上建立了不同时间尺度、不同气象灾害类型下的元件故障模型，并依据此模型进行电网可靠性评估。按照该方法对西南某省级电网近3年内500 kV输电线路的故障数据进行了分析，对该电网的可靠性进行了评估。计算结果表明，不同时间段电网的可靠性指标与年均值相比具有较大差异，验证了时空环境相依的可靠性评估的必要性。
전통적전망가고성평고채용고정불변적원건년균고장솔모형，난이괄응전력계통단기풍험평고수구。전망고장여재해성천기구유교강적시간상관성，기상재해구유명현적계절성특정，인차전망풍험야구유시간파동성。재묘술전망원건고장삼수시，수요종원래적일유횡향련속시간하적년균치모형，탁전도고필역사동기(종향)시간화도치고장적인소，특별시외부기상배경인소，이편경준학지묘술시간급배경상의적전망고장솔。재전통년균치모형적기출상건립료불동시간척도、불동기상재해류형하적원건고장모형，병의거차모형진행전망가고성평고。안조해방법대서남모성급전망근3년내500 kV수전선로적고장수거진행료분석，대해전망적가고성진행료평고。계산결과표명，불동시간단전망적가고성지표여년균치상비구유교대차이，험증료시공배경상의적가고성평고적필요성。
The off-line and fixed annual average failure probability model is used in conventional reliability assessment, it is difficult to adapt to the current needs of power system operation. Power grid faults have great temporal relationship with disastrous weather, and meteorological disasters have distinct seasonal characteristic, thus power grid risk will fluctuate with time change. When descripting power component failure rate, it is necessary to expand from chronological time to historical period and taking consideration of the reasons especially external meteorological environments which cause faults, in order to describe the temporal and spatial environment dependent failure rate. The component failure rate model is established and applied to power grid reliability assessment, based on conventional statistical model in different timescale and under different meteorological disasters. The proposed models are utilized to analyze the 500 kV transmission lines failure data during nearly 3 years, meanwhile, the proposed method is applied to assess the reliability of a provincial power grid in southwest China. The results indicate that the reliability indexes in different time intervals have major difference with annual average index, and it proves the necessity of temporal and spatial environments dependent reliability assessment. This work is supported by National Natural Science Foundation of China (No. 50977094) and Natural Science Foundation of Chongqing (No. CSTC 2011BB6047).