本文選題：交叉熵 + 重采樣��； 參考：《浙江大學(xué)》2014年博士論文

【摘要】：智能電網(wǎng)的全面推進給電力系統(tǒng)的發(fā)展注入了生機與活力。對新型系統(tǒng)開展深入研究的同時,各種不確定因素相伴而生。系統(tǒng)可靠性評估對于預(yù)測、防控系統(tǒng)遭遇各種隨機因素時發(fā)生大面積停電事故具有重要的意義。在復(fù)雜電力系統(tǒng)短期可靠性評估問題中,由于待考察的前置期通常較短,危害性較大的停電事故發(fā)生概率較低,導(dǎo)致傳統(tǒng)蒙特卡洛方法采樣效率極其低下,阻礙了其工程應(yīng)用的進程。本文立足于電力系統(tǒng)可靠性評估領(lǐng)域中得以廣泛應(yīng)用的蒙特卡洛仿真方法,以信息學(xué)領(lǐng)域衍生的交叉熵理論為基礎(chǔ),分別針對非序貫蒙特卡洛和序貫蒙特卡洛兩種典型方法進行了算法開發(fā),提出了三種基于交叉熵理論的電力系統(tǒng)短期可靠性重要度采樣評估方法,分別是： (1)考慮多狀態(tài)采樣問題的離散多狀態(tài)電力系統(tǒng)非序貫重采樣評估方法。 (2)考慮時齊馬爾科夫過程的三段式序貫重采樣短期可靠性評估方法。 (3)考慮非時齊馬爾科夫過程的自適應(yīng)序貫重采樣短期可靠性評估方法。 這些方法的共同之處是本質(zhì)上均屬于眾多方差減小方法之一的重采樣方法,并利用預(yù)采樣樣本進行畸變采樣概率的迭代尋優(yōu)。不同之處在于,根據(jù)所考慮的問題和仿真機理的不同,畸變采樣概率的迭代尋優(yōu)遵循不同的優(yōu)化模型。通過在IEEE-RTS79和Roy Billinton Reliability Test System改造系統(tǒng)上進行測試,分別論證了所提算法的精度并分析了相較于傳統(tǒng)蒙特卡洛方法的效率優(yōu)勢。 為進一步闡述算法的應(yīng)用價值,以考慮多狀態(tài)采樣問題的離散多狀態(tài)非序貫重采樣評估方法為工具,在本文所提出的改進well-being框架下實現(xiàn)了對考慮風(fēng)電的系統(tǒng)旋轉(zhuǎn)備用響應(yīng)能力進行了評估。傳統(tǒng)well-being框架體系在電力系統(tǒng)旋轉(zhuǎn)備用充裕性評估問題中應(yīng)用廣泛,對波動性、間歇性較強的風(fēng)電系統(tǒng)尤為適用,本文提出一種適用于旋轉(zhuǎn)備用響應(yīng)能力評估的新well-being框架。該框架體系考慮了風(fēng)電間歇性、隨機性的特點以及傳統(tǒng)well-being框架體系的不足,提出用四狀態(tài)體系代替三狀態(tài)體系,通過在IEEE RTS-79改造系統(tǒng)的算例分析揭示了新well-being框架體系的價值。
[Abstract]:The overall advance of smart grid has injected vitality into the development of power system. At the same time, all kinds of uncertain factors come along with the further study of the new system. The evaluation of system reliability is of great significance for forecasting large area blackouts when the control system encounters various random factors. In the short-term reliability evaluation of complex power systems, the sampling efficiency of the traditional Monte Carlo method is extremely low due to the short pre-period to be investigated and the low probability of power outages, which are more harmful than others. It hinders the progress of its engineering application. Based on the Monte Carlo simulation method, which is widely used in the field of power system reliability evaluation, this paper is based on the cross-entropy theory derived from the field of informatics. In this paper, two typical methods of non-sequential Monte Carlo and sequential Monte Carlo are developed, and three methods based on cross-entropy theory are proposed to evaluate the short-term reliability importance of power system. 1) Non-sequential resampling evaluation method for discrete multi-state power systems considering multi-state sampling. 2) A three-stage sequential resampling method for short term reliability evaluation considering time-homogeneous Markov processes. An adaptive sequential resampling method for short term reliability evaluation considering non-time homogeneous Markov processes is proposed. The common point of these methods is that they all belong to the resampling method which is one of the many variance reduction methods in essence and the presampled samples are used for iterative optimization of the distorted sampling probability. The difference is that the iterative optimization of distortion sampling probability follows different optimization models according to the problem considered and the different simulation mechanism. By testing on IEEE-RTS79 and Roy Billinton Reliability Test System, the accuracy of the proposed algorithm is demonstrated and the efficiency advantages compared with the traditional Monte Carlo method are analyzed. In order to further expound the application value of the algorithm, the discrete multi-state non-sequential resampling evaluation method considering the multi-state sampling problem is used as a tool. Based on the improved well-being framework proposed in this paper, the capability of rotating standby response of wind power system is evaluated. The traditional well-being framework is widely used in the evaluation of power system rotation reserve adequacy, especially for wind power systems with strong volatility and intermittence. This paper presents a new well-being framework for the evaluation of rotational standby response ability. Considering the intermittent and stochastic characteristics of wind power and the shortcomings of the traditional well-being frame system, the four-state system is proposed to replace the three-state system, and the value of the new well-being frame system is revealed by the example analysis in the IEEE RTS-79 reconstruction system.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TM732

【參考文獻】

相關(guān)期刊論文 前1條

1 孫元章,程林,劉海濤;基于實時運行狀態(tài)的電力系統(tǒng)運行可靠性評估[J];電網(wǎng)技術(shù);2005年15期

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本文編號：1990394