本文選題：風(fēng)險(xiǎn)理論 + 短期充裕性��； 參考：《華北電力大學(xué)》2014年博士論文

【摘要】：電力系統(tǒng)充裕性問題是貫穿電力系統(tǒng)規(guī)劃與運(yùn)行全過程的重要問題�？紤]不確定性因素的影響,對(duì)電力系統(tǒng)充裕性進(jìn)行評(píng)估與決策是保障電力系統(tǒng)安全、可靠運(yùn)行的前提和手段。近年來,大規(guī)模風(fēng)力發(fā)電的接入給原本可調(diào)、可控的電源出力帶來了較大的不確定性,加上用電側(cè)大量電動(dòng)汽車充、放電的不確定性,使得電力系統(tǒng)運(yùn)行調(diào)控的難度和風(fēng)險(xiǎn)都大大增加。傳統(tǒng)的電力系統(tǒng)充裕性評(píng)估指標(biāo)與方法已經(jīng)難以適應(yīng)目前電力系統(tǒng)短期運(yùn)行領(lǐng)域電源與負(fù)荷的新特點(diǎn)。在這樣的背景下,本論文以含風(fēng)電電力系統(tǒng)短期充裕性評(píng)估與決策研究為題,開展的主要工作和取得的成果如下。 針對(duì)由風(fēng)電不確定性引起的備用需求決策問題,在分析不同時(shí)間尺度下風(fēng)電功率的波動(dòng)特性、風(fēng)電功率短期預(yù)測(cè)誤差的分布特點(diǎn)的基礎(chǔ)上,借鑒風(fēng)險(xiǎn)理論,以風(fēng)電功率預(yù)測(cè)誤差為風(fēng)電不確定性的表征,提出了基于時(shí)間的和基于功率的風(fēng)電不確定性度量指標(biāo)；引入精算學(xué)中的Buhlmann信度模型,將2種指標(biāo)綜合起來,形成信度風(fēng)險(xiǎn)度量指標(biāo),并將其用于估計(jì)由風(fēng)電不確定性引起的系統(tǒng)運(yùn)行備用需求。算例分析及指標(biāo)的有效性檢驗(yàn)表明,信度指標(biāo)繼承了基于時(shí)間的和基于功率的2種指標(biāo)的優(yōu)點(diǎn),能夠恰當(dāng)?shù)貜臍v史數(shù)據(jù)信息和未來預(yù)測(cè)信息中獲得某置信度下風(fēng)電功率預(yù)測(cè)誤差的風(fēng)險(xiǎn)信息,能夠在不降低對(duì)實(shí)際損失覆蓋程度的前提下,合理地減少不必要的備用,對(duì)電力系統(tǒng)經(jīng)濟(jì)運(yùn)行起到一定的促進(jìn)作用。 針對(duì)計(jì)及電源與負(fù)荷不確定性風(fēng)險(xiǎn)的發(fā)電充裕性評(píng)估問題,在總結(jié)電力系統(tǒng)充裕性的基本知識(shí)以及常用的發(fā)電系統(tǒng)充裕性評(píng)估方法和評(píng)估指標(biāo)的基礎(chǔ)上,從短期運(yùn)行的角度,以系統(tǒng)可用發(fā)電容量缺額為充裕性表征函數(shù),對(duì)運(yùn)行失負(fù)荷概率(operational loss of load probability, OLOLP)、運(yùn)行失負(fù)荷期望(operational expected load not served, OELNS)指標(biāo)進(jìn)行了重新描述,提出了一個(gè)新的充裕性度量指標(biāo)：延遲失負(fù)荷概率(buffered loss of load probability, BLOLP);分別分析了充裕性評(píng)估指標(biāo)與負(fù)荷需求、負(fù)荷預(yù)測(cè)誤差、常規(guī)機(jī)組容量、常規(guī)機(jī)組停運(yùn)率、風(fēng)電機(jī)組停運(yùn)率和風(fēng)電功率預(yù)測(cè)誤差等影響因素之間的關(guān)系。對(duì)指標(biāo)的定性分析表明,所提出的充裕性評(píng)估指標(biāo)以一種概率性方法將系統(tǒng)運(yùn)行劃分為充裕、警戒和不充裕3種狀態(tài),有利于提高系統(tǒng)運(yùn)行的可靠性。仿真算例表明,所提出的概率評(píng)估指標(biāo)隱含著充裕性函數(shù)概率分布的尾部信息,反映的充裕性更全面。 針對(duì)不確定性對(duì)機(jī)組組合的影響,基于充裕性約束提出了一種含風(fēng)電電力系統(tǒng)機(jī)組組合模型。在傳統(tǒng)的基于機(jī)組投運(yùn)風(fēng)險(xiǎn)(unit commitment risk, UCR)和基于失負(fù)荷概率(loss of load probability, LOLP)、基于失負(fù)荷期望(expected load not served, ELNS)的充裕性約束的基礎(chǔ)上,建立了基于所提出的OLOLP和BLOLP的機(jī)組組合模型,研究了其充裕性約束的求解方法。與其它機(jī)組組合模型算例的對(duì)比表明,本文所提出的基于BLOLP的機(jī)組組合模型具有運(yùn)算速度快、結(jié)果可靠性高的優(yōu)勢(shì),還能夠給出在不同充裕性水平要求下系統(tǒng)機(jī)組的啟停方案,實(shí)現(xiàn)機(jī)組有功出力和提供備用的協(xié)調(diào)優(yōu)化,給出運(yùn)行方案相對(duì)應(yīng)的系統(tǒng)充裕性量化值,為調(diào)度工作提供直觀參考。 以電動(dòng)汽車作為用電側(cè)主要不確定性的代表,研究了含電動(dòng)汽車的配電系統(tǒng)短期充裕性動(dòng)態(tài)決策問題。在明確電動(dòng)汽車工作模式、充放電特性和參與調(diào)度的方式的基礎(chǔ)上,考慮來自電源側(cè)與負(fù)荷側(cè)的雙重不確定性因素,以系統(tǒng)運(yùn)行備用容量為充裕性表征函數(shù),定義了2個(gè)充裕性動(dòng)態(tài)度量指標(biāo),建立了以最大充裕性為目標(biāo)的多階段決策模型。仿真算例結(jié)果表明,所提出的充裕性動(dòng)態(tài)度量指標(biāo)在保證研究期內(nèi)系統(tǒng)整體充裕性的同時(shí),還能根據(jù)負(fù)荷大小協(xié)調(diào)各時(shí)段的可調(diào)度負(fù)荷資源；所建立的多階段決策模型同時(shí)優(yōu)化購電方案與電動(dòng)汽車充、放電方案,考慮了研究期內(nèi)不同時(shí)段的優(yōu)化變量之間的相互關(guān)聯(lián),體現(xiàn)了動(dòng)態(tài)優(yōu)化的本質(zhì)；配電系統(tǒng)的運(yùn)營部門可以通過適當(dāng)?shù)囊龑?dǎo)和管理,減少電動(dòng)汽車充、放電對(duì)系統(tǒng)運(yùn)行的負(fù)面影響,充分發(fā)揮其削峰填谷的正面作用。
[Abstract]:The problem of power system adequacy is an important problem throughout the whole process of power system planning and operation. Considering the influence of uncertain factors, the evaluation and decision of power system adequacy is the premise and means to ensure the safety and reliable operation of power system. In recent years, the access of large-scale wind power generation to the original and controllable power supply The difficulty and risk of power system operation and control are greatly increased by the uncertainty of the power supply and the uncertainty of discharge. The traditional power system adequacy evaluation index and method have been difficult to adapt to the new characteristics of power and load in the current power system in the short run field. Under the background of the sample, this paper focuses on the short-term adequacy assessment and decision making of wind power system. The main work and achievements are as follows.
In view of the decision problem of standby demand caused by wind power uncertainty, on the basis of analyzing the characteristics of wind power fluctuation under different time scales and the distribution characteristics of wind power short-term prediction error, using risk theory, the wind power prediction error is characterized by wind power uncertainty, and the wind based on time and power based wind is proposed. By introducing the Buhlmann reliability model in the actuarial science, the 2 indexes are combined to form the reliability risk measurement index, and it is used to estimate the standby demand caused by the wind power uncertainty. The calculation example analysis and the validity test table of the index show that the reliability index inherits the time based and based on the work. The advantages of the 2 indexes of the rate can be properly obtained from the historical data and future prediction information to obtain the risk information of the prediction error of the wind power of a certain confidence lower. It can reduce the unnecessary reserve reasonably without reducing the coverage of the actual loss, and it can play a certain role in the economic operation of the electric power system.
On the basis of summarizing the basic knowledge of power system adequacy and the commonly used evaluation method and evaluation index of power generation system adequacy, based on the summary of the basic knowledge of power system adequacy and the evaluation index of power generation system adequacy, the shortage of power generation capacity is used as an abundant characterization function, and the running load is lost. The probability (operational loss of load probability, OLOLP), the running load loss expectation (operational expected load not served, OELNS) is redescribed, and a new margin index is proposed. The relationship between the load demand, the load forecasting error, the conventional unit capacity, the conventional unit outage rate, the wind turbine outage rate and the prediction error of the wind power. The qualitative analysis of the indexes shows that the proposed adequacy evaluation index divides the system into abundant, alert and 3 states with a probability method. It is beneficial to improve the reliability of the system operation. The simulation example shows that the proposed probability evaluation index implies the tail information of the probability distribution of the abundant function, and the sufficiency of the reflection is more comprehensive.
In view of the influence of uncertainty on the unit combination, a combination model of wind power system is proposed based on the adequacy constraints. In the traditional unit commitment risk (UCR) and the load loss probability (loss of load probability, LOLP), the load loss expectation (expected load not) is filled. On the basis of margin constraints, the unit combination model based on the proposed OLOLP and BLOLP is set up, and the method of solving the adequacy constraints is studied. The comparison with other unit combination models shows that the proposed BLOLP based unit model has the advantages of fast operation speed and high reliability, and can also be given in this paper. The starting and stopping scheme of the system unit at different adequacy levels is required to realize the unit active power output and provide the coordination and optimization of the reserve, and give the quantitative value of the system adequacy in order to provide a visual reference for the scheduling work.
Taking the electric vehicle as the representative of the main uncertainty of the electric side, the dynamic decision problem of the short term adequacy of the power distribution system containing electric vehicles is studied. The dual uncertainty factors from the power side and the load side are considered on the basis of the working mode of the electric vehicle, the charging discharge characteristics and the mode of participating in the scheduling. The capacity is an abundant characterization function, and 2 abundant dynamic metrics are defined, and a multi-stage decision model with maximum adequacy is established. The simulation example shows that the proposed adequacy dynamic metric can also coordinate the adjustable periods according to the load size while guaranteeing the overall system adequacy in the study period. The multi stage decision model is set up to optimize the power purchase scheme and electric vehicle charging and discharging scheme at the same time, considering the interrelation between the optimized variables in the different period of the study period, reflecting the essence of dynamic optimization; the operation Department of the distribution system can reduce the charge and discharge of electric vehicles through proper guidance and management. The negative impact of electricity on the operation of the system will give full play to its positive role in cutting the peak and filling the valley.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM614

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本文編號(hào)：2105874