基于風險評估的電力系統(tǒng)安全預警分級研究
發(fā)布時間：2018-10-29 16:22
【摘要】：隨著電網(wǎng)互聯(lián)規(guī)模的增大和復雜性的提高,電力系統(tǒng)的安全運行問題日益突出,國內外頻繁發(fā)生的大停電事故不但造成了巨大的經(jīng)濟損失,而且嚴重影響社會穩(wěn)定,進而引起了各國電力學者對電網(wǎng)安全可靠運行的廣泛關注。隨著我國電力需求的快速增長,以及西電東送、全國聯(lián)網(wǎng)戰(zhàn)略的實施,中國電網(wǎng)將成為世界上規(guī)模最大、最復雜的電網(wǎng)之一,提高電網(wǎng)運行可靠性、保證電網(wǎng)安全已成為電力系統(tǒng)面臨的迫切性問題。因此對電網(wǎng)進行全面風險評估及安全預警具有十分重要的意義。鑒于此,本文對含風電場并網(wǎng)的電力系統(tǒng)風險評估及安全預警等問題開展一系列研究,主要工作歸納如下： 研究了電力系統(tǒng)安全評估方法發(fā)展的三個階段,分析了幾種電力系統(tǒng)可靠性評估方法的特點,確定了本文采用的風險評估方法為蒙特卡洛法；研究了效用函數(shù)理論,通過計及負荷的重要程度與電壓等級等因素,改進了故障后果嚴重度模型,使模型更加符合電力系統(tǒng)實際情況；改進了海南電網(wǎng)的現(xiàn)有風險評估量化方法,消除了遮蔽現(xiàn)象；提出了基于風險評估的安全預警分級算法,因電力系統(tǒng)風險評估受故障概率和故障后果嚴重度的影響,研究了基于模糊C均值聚類方法的故障概率分級算法,提出了基于模糊推理原則的故障后果嚴重度分級算法,通過模糊運算確定了安全預警等級；建立了基于時間序列-狀態(tài)轉移法的風速預測模型和考慮尾流效應的風電機組出力模型及停運模型。 運用MATLAB軟件編制的算法程序,結合IEEE-RTS79測試系統(tǒng)對風電場不同接入形式下以及用相同容量的風電場替代常規(guī)發(fā)電機組后的系統(tǒng)風險進行了仿真計算分析,驗證了本文所提方法的有效性。仿真結果表明：風電的直接接入會導致系統(tǒng)風險指標及預警等級的提高,元件故障率對系統(tǒng)預警分級的影響較小,系統(tǒng)安全水平隨負荷水平提高而降低。
[Abstract]:With the increase of interconnection scale and complexity of power network, the safe operation of power system is becoming more and more serious. Frequent power outages at home and abroad not only cause huge economic losses, but also seriously affect social stability. Therefore, electric power scholars all over the world pay more attention to the safe and reliable operation of power grid. With the rapid growth of power demand in China, the transmission of electricity from the west to the east, and the implementation of the national networking strategy, China's power grid will become one of the largest and most complex power grids in the world, improving the reliability of the power grid operation. To ensure the security of power system has become an urgent problem in power system. Therefore, it is of great significance to carry out comprehensive risk assessment and security early warning for power grid. In view of this, this paper carries out a series of research on power system risk assessment and safety early warning with wind farm connected to the grid. The main work is summarized as follows: the three stages of the development of power system security assessment method are studied. This paper analyzes the characteristics of several power system reliability assessment methods and determines that the risk assessment method used in this paper is Monte Carlo method. The utility function theory is studied. The model of fault consequence severity is improved by taking into account the important degree of load and voltage grade, which makes the model more suitable for the actual situation of power system. The existing quantitative risk assessment method of Hainan Power Grid is improved, and the sheltering phenomenon is eliminated. A security early warning classification algorithm based on risk assessment is proposed. Because the power system risk assessment is affected by fault probability and fault consequence severity, a fault probability classification algorithm based on fuzzy C-means clustering method is studied. A fault consequence severity classification algorithm based on fuzzy reasoning principle is proposed, and the security early warning level is determined by fuzzy operation. The wind speed prediction model based on time series-state transfer method and wind turbine output model and outage model considering wake effect are established. By using the algorithm program compiled by MATLAB software and the IEEE-RTS79 test system, the system risk of replacing conventional generator sets with wind farms with the same capacity and different forms of access is simulated and analyzed. The validity of the proposed method is verified. The simulation results show that the direct access of wind power will lead to the increase of system risk index and warning level, the failure rate of components will have little effect on the early warning classification of the system, and the system safety level will decrease with the increase of load level.
【學位授予單位】：華北電力大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM732
本文編號：2298198
[Abstract]:With the increase of interconnection scale and complexity of power network, the safe operation of power system is becoming more and more serious. Frequent power outages at home and abroad not only cause huge economic losses, but also seriously affect social stability. Therefore, electric power scholars all over the world pay more attention to the safe and reliable operation of power grid. With the rapid growth of power demand in China, the transmission of electricity from the west to the east, and the implementation of the national networking strategy, China's power grid will become one of the largest and most complex power grids in the world, improving the reliability of the power grid operation. To ensure the security of power system has become an urgent problem in power system. Therefore, it is of great significance to carry out comprehensive risk assessment and security early warning for power grid. In view of this, this paper carries out a series of research on power system risk assessment and safety early warning with wind farm connected to the grid. The main work is summarized as follows: the three stages of the development of power system security assessment method are studied. This paper analyzes the characteristics of several power system reliability assessment methods and determines that the risk assessment method used in this paper is Monte Carlo method. The utility function theory is studied. The model of fault consequence severity is improved by taking into account the important degree of load and voltage grade, which makes the model more suitable for the actual situation of power system. The existing quantitative risk assessment method of Hainan Power Grid is improved, and the sheltering phenomenon is eliminated. A security early warning classification algorithm based on risk assessment is proposed. Because the power system risk assessment is affected by fault probability and fault consequence severity, a fault probability classification algorithm based on fuzzy C-means clustering method is studied. A fault consequence severity classification algorithm based on fuzzy reasoning principle is proposed, and the security early warning level is determined by fuzzy operation. The wind speed prediction model based on time series-state transfer method and wind turbine output model and outage model considering wake effect are established. By using the algorithm program compiled by MATLAB software and the IEEE-RTS79 test system, the system risk of replacing conventional generator sets with wind farms with the same capacity and different forms of access is simulated and analyzed. The validity of the proposed method is verified. The simulation results show that the direct access of wind power will lead to the increase of system risk index and warning level, the failure rate of components will have little effect on the early warning classification of the system, and the system safety level will decrease with the increase of load level.
【學位授予單位】：華北電力大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM732
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