摘要
针对配电网空间负荷预测过程中负荷密度指标难以选取的问题,在层次分析法的基础上,提出了基于区间层次分析(IAHP)法和逼近理想解排序(TOPSIS)法的负荷密度指标选取方法。该方法通过用区间数代替点值,对传统的层次分析法进行改进,并将IAHP法和TOPSIS法有效融合,将专家经验和定量计算相结合,处理决策因素的不确定性和专家判断的模糊性,增强了对负荷密度指标预测结果的可信度。采用类内相似度方法进行负荷密度修正,进一步提高了预测结果的精度。实例计算表明,所提出的方法预测结果更优、误差更小。
In view of the load density selection problem in spatial load forecasting in the distribution network, a load density index selection method based on the interval analytic hierarchy process （IAHP） and technique for order preference by similarity to ideal solution （TOPSIS） methods is proposed. The method is an improvement on the traditional analytic hierarchy process for using interval data instead of dot data while effectively combining the theory of the IAHP method with the TOPSIS method, and the advantages of human expertise with quantitative calculation in rationally handling the uncertainties of decision factors and fuzziness of experts＇ judgment. This has enhanced the reliability of prediction results of load density. Finally, the method of similarity is used to correct the load density, further improving the precision of forecast. A case study shows that the method proposed has better prediction results and smaller errors.
出处
《电力系统自动化》
EI
CSCD
北大核心
2012年第13期56-60,共5页
Automation of Electric Power Systems
基金
国家重点基础研究发展计划(973计划)资助项目(2009CB219700)~~
关键词
配电网
空间负荷预测
负荷密度指标
区间层次分析法
逼近理想解排序法
distribution network
spatial load forecasting
load density index
interval analytic hierarchy process （IAHP） method
technique for order preference by similarity to ideal solution （TOPSIS） method
