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利用电参数的工业用户能效模糊综合评估
引用本文:孟金岭,胡嘉骅,文福拴,林国营,党三磊.利用电参数的工业用户能效模糊综合评估[J].电力建设,2016(11):16-22.
作者姓名:孟金岭  胡嘉骅  文福拴  林国营  党三磊
作者单位:1. 广东电网有限责任公司电力科学研究院,广州市,510600;2. 浙江大学电气工程学院,杭州市,310027
基金项目:国家自然科学基金项目(51477151),南方电网公司科研项目(K-GD2014-192) Project supported by National Natural Science Foundation of China(51477151)
摘    要:在对工业用户进行节能改造之前,有必要对其能效水平进行比较准确的评估。现有的一些能效评估方法存在指标选取受限、数据获取困难、主观因素较强等问题。在此背景下,针对工业用户提出基于电参数的能效模糊综合评估方法。具体地,以计量电表能够准确测量并记录的电参数为候选评估指标。首先,利用主成分分析法(principal component analysis,PCA)识别并删除次要指标,在此基础上确定工业用户综合能效评估指标体系。之后,利用熵权法计算所选各个指标的权重,并考虑到能效评估结果所呈现的模糊性,采用模糊综合评估方法对工业用户的能效进行评估。最后,用广东省的实际数据说明该方法的可行性与基本特性。

关 键 词:工业用户  能效评估  电参数  模糊评估  主成分分析法(PCA)  熵权法

Fuzzy Comprehensive Evaluation for Energy Efficiency of Industrial Consumers Employing Electric Parameters
Abstract:It is necessary to accurately evaluate the energy efficiency of an industrial consumer before implementing an energy-saving scheme. Several existing evaluation methods for energy efficiency have some problems such as limited selection of indices, limited access to data and strong subjectivity. Given this background, this paper presents a fuzzy comprehensive evaluation method for the energy efficiency of industrial consumers based on electric parameters. Specifically, the electric parameters are candidate evaluation index, which can be accurately measured and recorded by smart meters. Firstly, we adopt principal component analysis ( PCA) to identify and remove secondary indicators, on this basis determine the comprehensive energy efficiency evaluation index system for industrial consumers. Then, we calculate the weights of all selected indices with using entropy weight method and evaluate the energy efficiency of industrial consumer with using fuzzy evaluation method, considering the exhibited fuzziness of evaluation results. Finally, the actual data from Guangdong province are served for demonstrating the feasibility and features of the proposed method.
Keywords:industrial consumer  energy efficiency evaluation  electric parameters  fuzzy evaluation  principal component analysis ( PCA)  entropy weight method
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