计及元胞发展程度的空间负荷预测方法研究

发布时间：2018-06-01 01:14

本文选题：空间负荷预测 + 元胞发展程度　；参考：《东北电力大学》2017年硕士论文

【摘要】：空间负荷预测是对规划区域内电力负荷时空特性的预测,是一个涉及因素多、不确定性高的复杂问题,不但要预测出未来负荷量的多少,同时还需考虑到未来负荷空间位置的变化。空间电力负荷预测是电力系统规划设计的先决条件,因此,提高空间负荷预测结果的精度对配电网的规划指导具有重要意义。本文首先对空间负荷预测的研究现状进行详细的介绍,总结空间负荷预测的方法,并对每类方法进行简要概述和优缺点分析。对空间电力负荷进行特性分析,包括负荷的非平稳增长特性、负荷本位波动特性、负荷全局传播特性和负荷的饱和特性。同时还完善了地理信息系统在空间负荷预测中的应用,以及电力地理信息系统的构建过程,在不同尺度的空间分辨率下生成元胞,分析了基于多尺度空间分辨率下的负荷特性。然后以大量历史负荷数据分析为基础,针对分类负荷在不同元胞内发展程度不同导致元胞负荷分布不均衡,从而影响空间负荷预测结果精度的问题,提出一种计及元胞发展程度的空间负荷预测方法。该方法结合分类负荷密度饱和值和生长曲线模型,揭示分类负荷密的发展曲线,确定各元胞内分类负荷密度的发展程度,预测目标年各元胞内分类负荷密度,实现对元胞负荷值的预测,并用实例分析验证了元胞发展程度法的有效性和实用性。最后针对以往对空间负荷预测方法研究主要集中于预测模型的提出与改进,对空间负荷的自身规律性的研究较少,在充分挖掘历史负荷数据的基础上,对负荷全局传播特性进行分析,提出了一种基于负荷全局传播性的空间负荷预测方法。该方法先确定预测区内的中心元胞,并建立中心元胞与各个元胞之间的传播关系,利用负荷传播特性实现空间负荷预测。本文所提出的方法不仅解决了元胞负荷发展不均衡的问题,还体现了电力负荷全局传播规律,提高了空间负荷预测结果的精度,并都用实例分析验证了所提出方法的有效性和实用性。
[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.
【学位授予单位】：东北电力大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM715

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