本文選題：城市小區(qū)負(fù)荷密度預(yù)測 + 語言信息決策理論　； 參考：《長沙理工大學(xué)》2014年碩士論文

【摘要】：隨著我國城鎮(zhèn)化事業(yè)的不斷發(fā)展,對城市配電網(wǎng)的要求也越來越高,如何建設(shè)出智能、可靠的城市供電系統(tǒng),正日益成為電力系統(tǒng)規(guī)劃關(guān)注的焦點(diǎn)之一。作為城市配網(wǎng)規(guī)劃的基礎(chǔ)領(lǐng)域,城市小區(qū)負(fù)荷密度預(yù)測在智能電網(wǎng)的建設(shè)中扮演著極其重要的角色,是配電網(wǎng)發(fā)展的基礎(chǔ)和前提。當(dāng)前已有大量的城市小區(qū)負(fù)荷密度預(yù)測方法,每種方法都有各自的優(yōu)勢和特點(diǎn),然而不論哪種方法其所依賴的基礎(chǔ)都是需要收集大量的樣本數(shù)據(jù)。目前由于我國正處于發(fā)展階段,許多地區(qū)的信息系統(tǒng)還不完善,因此在實(shí)際應(yīng)用中有時(shí)難以收集到完整的樣本數(shù)據(jù)以滿足預(yù)測的需求。針對這一問題,依據(jù)城市自身特點(diǎn)和原始數(shù)據(jù)采集的結(jié)果,提出一種采用語言信息決策理論的電力負(fù)荷密度預(yù)測法。樣本數(shù)量的完整性將決定最終的預(yù)測精度,因此在無法收集實(shí)際數(shù)據(jù)的前提下通過運(yùn)用專家的知識與經(jīng)驗(yàn)合理地對城市小區(qū)的各類指標(biāo)進(jìn)行語言評判能夠有效的彌補(bǔ)數(shù)據(jù)收集殘缺的問題。在預(yù)測過程中,為使預(yù)測結(jié)果更加可信,探究了在專家對城市小區(qū)的語言評判過程中,建立城市小區(qū)負(fù)荷密度評判體系、消除專家語言信息的混合性、集成專家語言信息以及如何協(xié)調(diào)專家評價(jià)沖突的問題,并從考慮城市小區(qū)綜合評分、專家語言信息同典型預(yù)測模型相結(jié)合、采用比較沖突度交互式協(xié)調(diào)專家信息這三個(gè)方面討論了語言信息決策理論在城市小區(qū)負(fù)荷密度預(yù)測中的應(yīng)用。以若干城市小區(qū)為樣本實(shí)例,檢驗(yàn)在不同預(yù)測方法下,語言信息決策理論在城市小區(qū)負(fù)荷密度預(yù)測中的應(yīng)用效果,結(jié)果表明由于采用比較沖突度交互式協(xié)調(diào)專家信息的預(yù)測方法,能夠使專家達(dá)成更為統(tǒng)一的評價(jià)結(jié)果,因此利用該方法進(jìn)行的城市小區(qū)負(fù)荷密度預(yù)測其預(yù)測精度最佳。采用語言信息決策理論的城市小區(qū)負(fù)荷密度預(yù)測法,能夠在實(shí)際數(shù)據(jù)收集困難的前提下,作為一種有效的輔助補(bǔ)充手段引入至小區(qū)負(fù)荷密度的預(yù)測中,具有很強(qiáng)的工程實(shí)際意義,其預(yù)測結(jié)果可為城市配電網(wǎng)規(guī)劃提供重要的輔助依據(jù)。
[Abstract]:With the continuous development of urbanization in China, the demand for urban distribution network is becoming higher and higher. How to build an intelligent and reliable urban power supply system is becoming one of the focus of power system planning. As the basic field of urban distribution network planning, urban residential area load density forecasting plays an extremely important role in the construction of smart grid, is the basis and premise of distribution network development. At present, there are a large number of load density forecasting methods for urban residential areas, each method has its own advantages and characteristics. However, no matter which method is based on the need to collect a large number of sample data. At present, because our country is in the stage of development and the information system in many areas is not perfect, it is sometimes difficult to collect complete sample data in practical application to meet the demand of forecast. In order to solve this problem, according to the characteristics of the city and the results of the original data collection, a power load density forecasting method based on the linguistic information decision theory is proposed. The completeness of the sample size will determine the final prediction accuracy, Therefore, under the premise that the actual data can not be collected, the problem of incomplete data collection can be effectively remedied by using the knowledge and experience of experts to reasonably judge all kinds of indexes in urban residential areas. In the process of forecasting, in order to make the prediction result more credible, this paper probes into the establishment of the evaluation system of load density of urban residential area in the process of expert language evaluation to eliminate the mixture of expert language information. Integrating expert language information and how to coordinate expert evaluation conflict, and considering the comprehensive score of urban residential area, the expert language information is combined with typical prediction model. This paper discusses the application of language information decision theory in urban residential area load density forecasting by using the three aspects of comparative conflict degree interactive coordinated expert information. Taking several urban districts as sample examples, this paper tests the application effect of language information decision theory in forecasting load density of urban residential areas under different forecasting methods. The results show that the prediction method of comparative conflict degree and interactive coordination of expert information can make the experts reach a more unified evaluation result, so the forecasting accuracy of load density prediction of urban residential area is the best. The load density forecasting method based on linguistic information decision theory can be introduced into the prediction of cell load density as an effective supplementary means on the premise of difficult data collection. It is of great practical significance, and the prediction results can provide an important auxiliary basis for urban distribution network planning.
【學(xué)位授予單位】：長沙理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TM715
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本文編號：1853756