發(fā)布時(shí)間：2018-06-20 21:30

  本文選題：智能電網(wǎng) + 存儲(chǔ)模型��； 參考：《遼寧大學(xué)》2012年碩士論文

【摘要】：近年來(lái)，隨著歐美等主要發(fā)達(dá)國(guó)家對(duì)能源供應(yīng)安全、應(yīng)對(duì)氣候變化等重大問(wèn)題關(guān)注度的不斷升級(jí)，尤其是在金融危機(jī)情況下對(duì)新技術(shù)產(chǎn)業(yè)帶動(dòng)作用的期待，智能電網(wǎng)已成為世界范圍內(nèi)的研究熱點(diǎn)和關(guān)注重點(diǎn)。 目前，世界各國(guó)的智能電網(wǎng)都處于理論研究與規(guī)劃試點(diǎn)階段，雖然在智能發(fā)電、輸電、變電、配電、用電以及智能調(diào)度等各個(gè)環(huán)節(jié)的試點(diǎn)項(xiàng)目都取得了突出的成就，但是這些試點(diǎn)項(xiàng)目的規(guī)模通常較小，借鑒的依然是在傳統(tǒng)電網(wǎng)中使用的基于集中式的關(guān)系數(shù)據(jù)庫(kù)存儲(chǔ)模型和存儲(chǔ)方法。然而，智能電網(wǎng)需要監(jiān)測(cè)的電氣設(shè)備分布范圍廣，獲取的數(shù)據(jù)以千位數(shù)量級(jí)增長(zhǎng)，對(duì)可靠性和實(shí)時(shí)性要求更高，面對(duì)這些海量、分布式、多源異構(gòu)的信息，常規(guī)的數(shù)據(jù)存儲(chǔ)方式會(huì)造成網(wǎng)絡(luò)的重載或阻塞。因此，傳統(tǒng)的集中式關(guān)系數(shù)據(jù)庫(kù)無(wú)法滿(mǎn)足智能電網(wǎng)對(duì)數(shù)據(jù)的存儲(chǔ)及實(shí)時(shí)讀取的要求。 本文針對(duì)未來(lái)大規(guī)模智能電網(wǎng)中海量動(dòng)態(tài)感知數(shù)據(jù)的存儲(chǔ)問(wèn)題進(jìn)行了深入研究，并充分考慮了智能電網(wǎng)對(duì)數(shù)據(jù)的傳輸、存儲(chǔ)與查詢(xún)的客觀要求，提出了一種以數(shù)據(jù)為中心的支持未來(lái)大規(guī)模智能電網(wǎng)的數(shù)據(jù)存儲(chǔ)方法，，具體工作如下： 針對(duì)智能電網(wǎng)地域分布范圍廣的特點(diǎn)，提出建立一種按照地理區(qū)域進(jìn)行邏輯劃分的新型數(shù)據(jù)存儲(chǔ)模型；針對(duì)智能電網(wǎng)需要大范圍傳輸數(shù)據(jù)以及對(duì)實(shí)時(shí)性的要求，提出了一種新的數(shù)據(jù)轉(zhuǎn)發(fā)方法，目的是能夠達(dá)到以最快速度、最少能量傳輸數(shù)據(jù)的目的；最后給出了一種新的合理有效的數(shù)據(jù)存儲(chǔ)方法，達(dá)到負(fù)載均衡的目的，同時(shí)能夠提高系統(tǒng)的可用性和存儲(chǔ)能力。 實(shí)驗(yàn)將本文提出的數(shù)據(jù)存儲(chǔ)與轉(zhuǎn)發(fā)方法與傳統(tǒng)方法進(jìn)行性能對(duì)比，結(jié)果表明本文給出的方法能夠達(dá)到負(fù)載均衡的目的，降低系統(tǒng)總能耗，增加系統(tǒng)存儲(chǔ)能力和存儲(chǔ)效率。
[Abstract]:In recent years, as major developed countries, such as Europe and the United States, have been paying more and more attention to major issues such as energy supply security and combating climate change, especially in the context of the financial crisis, they are looking forward to the leading role of the new technology industry. Smart grid has become a worldwide research hotspot and focus. At present, the smart grid all over the world is in the experimental stage of theoretical research and planning, although the pilot projects of intelligent power generation, transmission, substation, distribution, power consumption and intelligent dispatching have made outstanding achievements. However, the scale of these pilot projects is usually small, and the centralized relational database storage model and storage methods used in traditional power systems are still used for reference. However, the smart grid needs to monitor a wide range of electrical equipment, access to data in the order of thousands of digits, higher requirements for reliability and real-time, faced with these massive, distributed, multi-source heterogeneous information, Conventional data storage can cause overloading or blocking of the network. Therefore, the traditional centralized relational database can not meet the smart grid data storage and real-time reading requirements. In this paper, the storage problem of mass dynamic perceptual data in future large-scale smart grid is deeply studied, and the objective requirements of data transmission, storage and query for smart grid are fully considered. In this paper, a data-centric data storage method is proposed to support the future large-scale smart grid. The main work is as follows: aiming at the wide regional distribution of smart grid, In this paper, a new data storage model is proposed, which is divided logically according to geographical area, and a new data forwarding method is proposed to meet the need of large-scale data transmission in smart grid and the requirement of real-time. The aim is to transmit data with the fastest speed and the least energy. Finally, a new reasonable and effective data storage method is proposed to achieve load balancing, and at the same time, it can improve the availability and storage capacity of the system. The experimental results show that the proposed method can achieve the purpose of load balancing, reduce the total energy consumption of the system, and increase the storage capacity and storage efficiency of the system.
【學(xué)位授予單位】：遼寧大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類(lèi)號(hào)】：TM76;TP333

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