【摘要】：現(xiàn)有的低頻減載方法多基于區(qū)域變電站的就地信息進(jìn)行負(fù)荷開斷決策,沒有充分利用智能電網(wǎng)發(fā)展帶來的信息化、互動化和網(wǎng)絡(luò)化優(yōu)勢。本文圍繞基于信息共享的智能電網(wǎng)低頻減載優(yōu)化技術(shù),依次從信息基礎(chǔ)、技術(shù)架構(gòu)、決策方法三個層面展開研究,提出了一種網(wǎng)絡(luò)化的低頻減載優(yōu)化控制策略,在架構(gòu)上可實現(xiàn)用戶側(cè)協(xié)調(diào)和系統(tǒng)側(cè)協(xié)調(diào),在功能上可實現(xiàn)減載負(fù)荷與減載容量的智能決策。 依據(jù)低頻減載的動作流程梳理歸納其正確動作所應(yīng)掌握的關(guān)鍵信息,在系統(tǒng)、變電站與負(fù)荷不同層面上,深入挖掘智能電網(wǎng)環(huán)境下低頻減載可利用的各類信息,其中重點研究了負(fù)荷的典型特征信息與友好型用戶(電動汽車)的互動特性,并對信息的獲取途徑與傳輸架構(gòu)展開分析。 分析傳統(tǒng)低頻減載技術(shù)的特點與不足,研究符合智能電網(wǎng)發(fā)展趨勢的通信網(wǎng)絡(luò)化低頻減載技術(shù)。在此基礎(chǔ)上結(jié)合上述多類可用信息,研究以智能變電站為平臺的低頻減載優(yōu)化架構(gòu)與控制策略,研究以變電站為單元的低頻減載廣域協(xié)調(diào)控制策略,從而在技術(shù)架構(gòu)上實現(xiàn)智能電網(wǎng)低頻減載的“雙重協(xié)調(diào)”優(yōu)化。 針對用戶側(cè)的協(xié)調(diào)優(yōu)化,提出了基于灰色關(guān)聯(lián)分析的切負(fù)荷排序算法,以量化分析負(fù)荷重要性、負(fù)荷頻率效應(yīng)系數(shù)、負(fù)載率等負(fù)荷特征信息對低頻減載動作的影響。在滿足系統(tǒng)切負(fù)荷總量需求前提下,給出了基于實時負(fù)荷檢測的變電站精確切負(fù)荷策略,研究了計及電動汽車友好互動的低頻減載協(xié)調(diào)優(yōu)化策略,并通過仿真算例驗證了算法對低頻減載動作特性的優(yōu)化。 針對系統(tǒng)側(cè)的協(xié)調(diào)優(yōu)化,構(gòu)建了基于廣域?qū)崟r共享的減載容量智能分配模型。引入單位負(fù)荷切除因子來考量系統(tǒng)低頻減載控制的綜合代價,并給出了基于層次分析法的切除因子計算方法。采用頻率穩(wěn)定直接分析法,以廣域測量數(shù)據(jù)為輸入來計算模型的穩(wěn)態(tài)頻率約束。進(jìn)而,利用粒子群算法實現(xiàn)了模型在多約束條件下的最優(yōu)求解,并通過仿真算例驗證了模型有效性。 論文研究了智能電網(wǎng)環(huán)境下低頻減載智能決策減載負(fù)荷和分配減載容量的問題,為提高智能電網(wǎng)環(huán)境下低頻減載的適應(yīng)性開拓了思路。
[Abstract]:The existing low-frequency load-shedding methods are mostly based on the local information of regional substations to make load cut-off decision, and do not make full use of the advantages of information, interaction and network brought by the development of smart grid. This paper focuses on the intelligent grid low-frequency load-shedding optimization technology based on information sharing, then studies it from three aspects: information foundation, technical architecture and decision-making method, and puts forward a network-based low-frequency load-reducing optimization control strategy. User-side coordination and system-side coordination can be realized in architecture, and intelligent decision-making of load-shedding load and load-reducing capacity can be realized in function. According to the operation flow of low frequency load shedding, the key information that should be grasped in the correct operation is summarized. In the different levels of system, substation and load, the various kinds of information that can be used in low frequency load reduction in smart grid environment are deeply excavated. The typical characteristic information of load and the interactive characteristic of friendly user (electric vehicle) are studied, and the way of obtaining information and the structure of transmission are analyzed. This paper analyzes the characteristics and shortcomings of traditional low-frequency load-shedding technology and studies the communication network-based low-frequency load-reducing technology which accords with the development trend of smart grid. Based on the above-mentioned available information, the optimal architecture and control strategy of low-frequency load-shedding based on intelligent substation are studied, and the wide-area coordinated control strategy of low-frequency load-shedding based on substation is studied. So as to achieve the "dual coordination" optimization of smart grid low-frequency load-shedding on the technical framework. Aiming at the coordination and optimization of user side, a load shedding scheduling algorithm based on grey relational analysis is proposed to quantitatively analyze the influence of load characteristic information such as load importance, load frequency effect coefficient and load ratio on low frequency load shedding action. On the premise of meeting the demand of system load shedding, the accurate load shedding strategy of substation based on real-time load detection is given, and the coordination and optimization strategy of low frequency load shedding taking into account the friendly interaction of electric vehicles is studied. A simulation example is given to verify the optimization of the low-frequency load-shedding performance of the algorithm. Aiming at the coordination optimization of system side, the intelligent allocation model of load-reducing capacity based on wide-area real-time sharing is constructed. The unit load cutting factor is introduced to consider the overall cost of the low frequency load shedding control of the system, and the calculation method of the cutting factor based on the analytic hierarchy process (AHP) is presented. The steady-state frequency constraints of the model are calculated by direct frequency stability analysis with wide-area measurement data as input. Furthermore, the particle swarm optimization algorithm is used to realize the optimal solution of the model under multi-constraint conditions, and the validity of the model is verified by a simulation example. In this paper, the problem of low-frequency load-shedding intelligent decision-making and load-reducing capacity distribution in smart grid environment is studied in order to improve the adaptability of low-frequency load-shedding in smart grid environment.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TM76

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