本文選題：飽和負荷 + 負荷預測　； 參考：《南昌大學》2016年碩士論文

【摘要】：隨著經(jīng)濟的快速發(fā)展,城市用電量也快速增長,常規(guī)的負荷預測方法,已經(jīng)難以適應(yīng)經(jīng)濟社會發(fā)展需求,難以做到適度超前的規(guī)劃以及與城市規(guī)劃的銜接。整個電網(wǎng)中最靠近用戶的就是配電網(wǎng),它對用電的可靠性和安全性起到至關(guān)重要的作用。科學規(guī)劃好這個部分,對電網(wǎng)的穩(wěn)定性和經(jīng)濟要求都有很現(xiàn)實的意義。本課題立足于城市發(fā)展的用電需求以及對城市的布局進行詳細的規(guī)劃,提出了基于生長曲線和計量經(jīng)濟模型的飽和負荷預測方法,與此同時,給出電力系統(tǒng)飽和負荷綜合預測法,給城市配電網(wǎng)遠期規(guī)劃作出負荷依據(jù)。城市飽和負荷密度是電網(wǎng)發(fā)展最后規(guī)模的關(guān)鍵性指標。研究它,就基本確定了城市電網(wǎng)發(fā)展的最后規(guī)模,可以超前規(guī)劃線路走廊的變電站布點,且可以將遠景電網(wǎng)規(guī)劃為目標對近期電網(wǎng)規(guī)劃與建設(shè)進行指導,就可以大大減少不必要的改、擴建工程,將因此產(chǎn)生的經(jīng)濟損失減到最少,協(xié)調(diào)經(jīng)濟發(fā)展和電網(wǎng)建設(shè)規(guī)劃之間的步調(diào)。本文以贛州市為分析算例,結(jié)合灰色理論中的灰色關(guān)聯(lián)法對社會經(jīng)濟系統(tǒng)中影響用電量的各因素進行分析,采用贛州新區(qū)GDP及人口微計量經(jīng)濟模型的最基本的指標。然后,運用了三種方法對未來贛州市電力系統(tǒng)的飽和負荷進行預測。實例證明,預測精度最高的辦法是基于生長曲線與計量經(jīng)濟模型法結(jié)合的綜合預測方法。
[Abstract]:With the rapid development of economy and the rapid growth of urban electricity consumption, it is difficult for the conventional load forecasting methods to adapt to the needs of economic and social development, to achieve moderate ahead planning and to link up with urban planning. The distribution network is the closest to the users in the whole power grid, which plays a vital role in the reliability and safety of power consumption. Scientific planning of this part is of practical significance to the stability and economic requirements of power grid. Based on the demand of urban development and the detailed planning of urban layout, this paper puts forward the saturation load forecasting method based on growth curve and econometric model, at the same time, The comprehensive forecasting method of saturated load of power system is presented, and the load basis for the long term planning of urban distribution network is given. Urban saturated load density is a key indicator of the final scale of power grid development. By studying it, the final scale of urban power network development is basically determined, the substation layout of line corridor can be planned ahead of time, and the long-term power network planning can be taken as the goal to guide the planning and construction of power grid in the near future. It can greatly reduce the unnecessary reform, expand the project, reduce the economic losses to the minimum, and coordinate the pace between economic development and power network construction planning. This paper takes Ganzhou City as an example and analyzes the factors affecting electricity consumption in the social economic system by combining the grey correlation method in grey theory. The most basic indexes of GDP and population microeconometric model in Ganzhou New area are adopted. Then, three methods are used to predict the saturation load of Ganzhou electric power system in the future. An example shows that the most accurate method is a comprehensive forecasting method based on the combination of growth curve and econometric model.
【學位授予單位】：南昌大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TM715

【參考文獻】

相關(guān)期刊論文 前10條

1 崔凱;張麗娟;李敬如;張振高;袁兆祥;;天津市中心城區(qū)飽和負荷分析與預測[J];電力技術(shù)經(jīng)濟;2008年05期

2 李艷梅;孫薇;;利用粗糙集約簡算法改進BP神經(jīng)網(wǎng)絡(luò)負荷預測模型[J];電力需求側(cè)管理;2008年05期

3 朱繼萍;戴君;;基于BP網(wǎng)的中長期負荷預測因素優(yōu)化選擇[J];計算機工程;2008年18期

4 張堯;席云華;胡金磊;夏成軍;林凌雪;;基于PCA和RBF神經(jīng)網(wǎng)絡(luò)的中長期負荷預測方法[J];電氣應(yīng)用;2008年02期

5 楊毅強;劉天琪;;BP人工神經(jīng)網(wǎng)絡(luò)負荷預測模型的L-M訓練算法[J];四川電力技術(shù);2006年03期

6 陳澤淮;張堯;武志剛;;RBF神經(jīng)網(wǎng)絡(luò)在中長期負荷預測中的應(yīng)用[J];電力系統(tǒng)及其自動化學報;2006年01期

7 韋鋼,賀靜,張一塵;中長期電力負荷預測的盲數(shù)回歸方法[J];高電壓技術(shù);2005年02期

8 牛東曉,邢棉,孟明;基于聯(lián)合數(shù)據(jù)挖掘技術(shù)的神經(jīng)網(wǎng)絡(luò)負荷預測模型研究(英文)[J];電工技術(shù)學報;2004年09期

9 劉遵雄;最小概率最大化回歸方法在電力負荷中期預測中的應(yīng)用[J];中國電力;2004年09期

10 游仕洪,程浩忠,謝宏,郭文鑄,盧金滇;模糊組合預測在中長期負荷預測中的應(yīng)用[J];電力系統(tǒng)及其自動化學報;2004年03期

，

本文編號：2001789