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Forecasting the urban power load in China based on the risk analysis of land-use change and load density

机译:基于土地利用变化和负荷密度风险分析的中国城市电力负荷预测

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摘要

Along with the increasing development of the urban society and economy, urban power is facing an increasing number of risk factors. The conventional load forecasting methods cannot guarantee the accuracy of the prediction; however, scientific urban load forecasting has a greatly significant meaning to urban power planning and supply. This paper firstly analyzes the risk factors that affect the fluctuation of the power load. From the perspective of the spatial load, the factors influencing the fluctuation of the urban power load are mainly determined by the change in land use and load density per unit area. Secondly, based on the basic principle of cellular automata, the rules and model of land-use change are established by considering the risk factors. From the aspect of land-use change, the cellular change rules of the land use with the risk factors are proposed and the methods of land classification change are presented by combining them with geographic information system (GIS) technology. Meanwhile, after comprehensively considering the effect of the risk factors on the load density fluctuations, the power load forecasting model is established based on the risk analysis of the land-use change and load density. Finally, taking a specific city as an example, the case study results show that this model is scientific. (C) 2015 Elsevier Ltd. All rights reserved.
机译:随着城市社会和经济的不断发展,城市电力面临着越来越多的风险因素。传统的负荷预测方法不能保证预测的准确性。但是,科学的城市负荷预测对城市电力规划和供应具有重要意义。本文首先分析了影响电力负荷波动的风险因素。从空间负荷的角度来看,影响城市电力负荷波动的因素主要由土地利用变化和单位面积负荷密度决定。其次,基于元胞自动机的基本原理,考虑风险因素,建立了土地利用变化的规律和模型。从土地利用变化的角度出发,提出了具有风险因素的土地利用的细胞变化规律,并结合GIS技术提出了土地分类变化的方法。同时,综合考虑风险因素对负荷密度波动的影响,基于土地利用变化和负荷密度的风险分析,建立了电力负荷预测模型。最后,以一个特定城市为例,案例研究结果表明该模型是科学的。 (C)2015 Elsevier Ltd.保留所有权利。

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