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计及城市发展程度的多阶段空间负荷预测方法
引用本文:肖白,穆冠男,姜卓,施永刚,孙德强.计及城市发展程度的多阶段空间负荷预测方法[J].电网技术,2019(7):2251-2257.
作者姓名:肖白  穆冠男  姜卓  施永刚  孙德强
作者单位:东北电力大学电气工程学院;北华大学计算机科学技术学院;国网吉林省电力有限公司通化供电公司
基金项目:国家自然科学基金项目(51177009);吉林省产业创新专项基金项目(2019C058-7);吉林省教育厅科技项目(JJKH20180442KJ)资助~~
摘    要:针对现有空间负荷预测方法通常以单一水平年为目标,没有考虑城市规划的多阶段性对各阶段空间负荷预测模型的不同需求,以及待预测区域为新建小区或缺少历史负荷数据时预测方法失效的问题,提出一种计及城市发展程度的多阶段空间负荷预测方法。该方法以解决城市发展多阶段规划的负荷预测需求为目标,首先建立与城市发展各阶段相对应的电力地理信息系统。其次根据用地信息、业扩报装计划和有限的历史负荷数据等信息建立近期空间负荷预测模型。然后确定分类负荷密度饱和值。最后利用近期空间负荷预测结果、分类负荷密度饱和值和城市建设信息等构建计及城市发展程度的中、远期空间负荷预测模型,实现待预测区域的多个发展建设阶段的空间负荷预测。工程实例证明了该方法的实用性和有效性。

关 键 词:空间负荷预测  地理信息系统  城市发展程度  分类负荷  新建小区

Multi-stage Spatial Load Forecasting Method Based on Urban Development Degree
XIAO Bai,MU Guannan,JIANG Zhuo,SHI Yonggang,SUN Deqiang.Multi-stage Spatial Load Forecasting Method Based on Urban Development Degree[J].Power System Technology,2019(7):2251-2257.
Authors:XIAO Bai  MU Guannan  JIANG Zhuo  SHI Yonggang  SUN Deqiang
Affiliation:(School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, Jilin Province, China;School of Computer Science and Technology, Beihua University, Jilin 132021, Jilin Province, China;Tonghua Power Supply Company, State Grid Jilin Electric Power Company Co., Ltd., Tonghua 134001, Jilin Province, China)
Abstract:Existing spatial load forecasting methods usually take a single level year as the goal, not considering the multiple stages of urban planning. Therefor, the demand for spatial load forecasting models at different stages is different, and the prediction method would be invalid when the area to predict is a new community or historical load data are insufficient. For these reasons, a multi-stage spatial load forecasting method based on urban development degree is proposed. The method aims to solve the load forecasting demand of multi-stage planning of urban development. Firstly, a power geographic information system corresponding to urban development stages is established. Secondly, based on land use information, industry expansion plan and limited historical load data, a recent space load forecasting model is established. Then load density saturation value is determined. Finally, based on the basic information of recent forecast, load saturation and urban construction, medium- and long-term spatial load forecasting models for urban development are established, realizing space load forecasting of multiple development and construction stages in the forecasted area. Engineering project proves practicability and effectiveness of the proposed method.
Keywords:spatial load forecasting  geographic information system  degree of urban development  classified load  new community
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