發(fā)布時間：2018-06-01 01:14

  本文選題：空間負(fù)荷預(yù)測 + 元胞發(fā)展程度　； 參考：《東北電力大學(xué)》2017年碩士論文

【摘要】：空間負(fù)荷預(yù)測是對規(guī)劃區(qū)域內(nèi)電力負(fù)荷時空特性的預(yù)測,是一個涉及因素多、不確定性高的復(fù)雜問題,不但要預(yù)測出未來負(fù)荷量的多少,同時還需考慮到未來負(fù)荷空間位置的變化。空間電力負(fù)荷預(yù)測是電力系統(tǒng)規(guī)劃設(shè)計的先決條件,因此,提高空間負(fù)荷預(yù)測結(jié)果的精度對配電網(wǎng)的規(guī)劃指導(dǎo)具有重要意義。本文首先對空間負(fù)荷預(yù)測的研究現(xiàn)狀進(jìn)行詳細(xì)的介紹,總結(jié)空間負(fù)荷預(yù)測的方法,并對每類方法進(jìn)行簡要概述和優(yōu)缺點分析。對空間電力負(fù)荷進(jìn)行特性分析,包括負(fù)荷的非平穩(wěn)增長特性、負(fù)荷本位波動特性、負(fù)荷全局傳播特性和負(fù)荷的飽和特性。同時還完善了地理信息系統(tǒng)在空間負(fù)荷預(yù)測中的應(yīng)用,以及電力地理信息系統(tǒng)的構(gòu)建過程,在不同尺度的空間分辨率下生成元胞,分析了基于多尺度空間分辨率下的負(fù)荷特性。然后以大量歷史負(fù)荷數(shù)據(jù)分析為基礎(chǔ),針對分類負(fù)荷在不同元胞內(nèi)發(fā)展程度不同導(dǎo)致元胞負(fù)荷分布不均衡,從而影響空間負(fù)荷預(yù)測結(jié)果精度的問題,提出一種計及元胞發(fā)展程度的空間負(fù)荷預(yù)測方法。該方法結(jié)合分類負(fù)荷密度飽和值和生長曲線模型,揭示分類負(fù)荷密的發(fā)展曲線,確定各元胞內(nèi)分類負(fù)荷密度的發(fā)展程度,預(yù)測目標(biāo)年各元胞內(nèi)分類負(fù)荷密度,實現(xiàn)對元胞負(fù)荷值的預(yù)測,并用實例分析驗證了元胞發(fā)展程度法的有效性和實用性。最后針對以往對空間負(fù)荷預(yù)測方法研究主要集中于預(yù)測模型的提出與改進(jìn),對空間負(fù)荷的自身規(guī)律性的研究較少,在充分挖掘歷史負(fù)荷數(shù)據(jù)的基礎(chǔ)上,對負(fù)荷全局傳播特性進(jìn)行分析,提出了一種基于負(fù)荷全局傳播性的空間負(fù)荷預(yù)測方法。該方法先確定預(yù)測區(qū)內(nèi)的中心元胞,并建立中心元胞與各個元胞之間的傳播關(guān)系,利用負(fù)荷傳播特性實現(xiàn)空間負(fù)荷預(yù)測。本文所提出的方法不僅解決了元胞負(fù)荷發(fā)展不均衡的問題,還體現(xiàn)了電力負(fù)荷全局傳播規(guī)律,提高了空間負(fù)荷預(yù)測結(jié)果的精度,并都用實例分析驗證了所提出方法的有效性和實用性。
[Abstract]:Spatial load forecasting is a complex problem involving many factors and high uncertainty, not only to predict the future load, but also to predict the space-time characteristic of power load in the planning area. At the same time, the change of space position of future load should be taken into account. Spatial load forecasting is a prerequisite for power system planning and design. Therefore, it is of great significance to improve the accuracy of spatial load forecasting results for distribution network planning guidance. In this paper, the research status of spatial load forecasting is introduced in detail, the methods of spatial load forecasting are summarized, and the advantages and disadvantages of each kind of methods are analyzed. The characteristics of space power load are analyzed, including the non-stationary growth of load, the fluctuation of load standard, the global propagation of load and the saturation of load. At the same time, the application of GIS in spatial load forecasting and the construction process of power GIS are improved, and the load characteristics based on multi-scale spatial resolution are analyzed. Then, based on the analysis of a large number of historical load data, aiming at the problem that the distribution of cellular load is uneven due to the different degree of development of classified load in different cells, which affects the accuracy of spatial load forecasting results. A spatial load forecasting method considering the degree of cellular development is proposed. Based on the saturation value of classified load density and growth curve model, this method reveals the development curve of classified load density, determines the development degree of classified load density in each cell, and predicts the classified load density of each cell in the target year. The prediction of the cellular load is realized, and the validity and practicability of the Cellular development degree method are verified by an example. Finally, the research on spatial load forecasting method is mainly focused on the proposed and improved forecasting model, and the research on the regularity of spatial load is less, on the basis of fully mining historical load data, Based on the analysis of the global load propagation characteristics, a spatial load forecasting method based on load global transmission is proposed. The method first determines the central cell in the prediction area, and establishes the propagation relationship between the center cell and each cell, and realizes the spatial load forecasting by using the load propagation characteristics. The method proposed in this paper not only solves the problem of uneven development of cellular load, but also embodies the law of global transmission of power load, and improves the accuracy of the result of spatial load forecasting. The effectiveness and practicability of the proposed method are verified by examples.
【學(xué)位授予單位】：東北電力大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM715

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本文編號：1962243