基于负荷密度指标的空间负荷预测方法研究

发布时间：2018-04-15 21:34

本文选题：空间负荷预测 + 元胞　；参考：《东北电力大学》2014年硕士论文

【摘要】：空间负荷预测（Spatial Load Forecasting，SLF）的主要任务是预测未来负荷出现的位置及大小，是城市电网规划中不可或缺的重要环节，其预测结果是确定所需配置供电设备容量和分布的基础，预测结果的准确程度对城市电网建设及其运行的经济性和安全性具有深远影响。本文对空间负荷预测方法研究现状做了详细的介绍，并对各类SLF方法的优缺点及适用场合等进行了分析。针对我国城市规划日渐规范化，未来城市土地使用性质已经基本指定的情况，对负荷密度指标法进行了系统深入的研究。本文首先对空间负荷预测的重要工具和平台——地理信息系统进行了介绍，并重点分析了地理信息系统在空间负荷预测中的应用；然后，综合考虑影响电力负荷发展的多个因素，建立计及其作用效果的预测模型来改善预测效果，提出了基于多变量分析的负荷密度指标法；在基于多变量分析的负荷密度指标法基础上，针对已有负荷密度指标的求取方法往往忽视了对实测历史负荷数据的挖掘，，或是忽略了同类负荷的非均匀分布问题，提出了一种基于元胞历史负荷数据的负荷密度指标法，最后，本文提出的方法通过对东北某城市的一个行政区的工程实例分析，证明了是可行的、有效的。
[Abstract]:The main task of spatial Load forecasting is to predict the location and size of future load, which is an indispensable and important link in urban power network planning. The prediction result is the basis for determining the capacity and distribution of power supply equipment.The accuracy of the prediction results has a profound impact on the economy and security of urban power grid construction and operation.In this paper, the research status of spatial load forecasting methods is introduced in detail, and the advantages and disadvantages of various SLF methods and their applications are analyzed.In view of the fact that urban planning in China is becoming more and more standardized and the nature of urban land use has been basically designated in the future, the method of load density index is studied systematically and deeply.This paper first introduces the important tool and platform of spatial load forecasting, geographic information system (GIS), and analyzes the application of GIS in spatial load forecasting.Considering several factors that affect the development of electric power load, a forecasting model considering its effect is established to improve the forecasting effect, and a load density index method based on multivariate analysis is put forward.On the basis of the load density index method based on multivariate analysis, the method of calculating the existing load density index often neglects the mining of the measured historical load data or the non-uniform distribution of the same load.A load density index method based on cellular historical load data is proposed. Finally, the method presented in this paper is proved to be feasible and effective by analyzing an engineering example of a city in northeast China.
【学位授予单位】：东北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM715

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