智能家居用电能效指标体系研究
发布时间：2018-11-27 17:39
【摘要】：作为智能电网在智能用电方面的重要一部分,智能家居应具有优化居民用电方式、提高能耗效率的作用,因此提出评估智能家居电力能效方面的指标体系。首先根据全面性、客观性、有效性原则从用户侧因素、硬件及其功能配置、环保清洁特性、环境影响4个方面初步构建指标体系。然后为提高指标集科学及精炼性,在群组层次分析法及G1法的理论基础上,利用层次聚类算法挖掘专家群潜在评价偏好性,并构建三标度模型计算指标权重,得到弱权重指标筛选模型。最后应用该模型对初构的指标体系进行筛选优化,得到了最终的智能家居能效指标体系。
[Abstract]:As an important part of smart grid in smart power consumption, smart home should have the function of optimizing household power consumption mode and improving energy consumption efficiency. Therefore, an index system to evaluate the energy efficiency of smart home power is proposed. Firstly, according to the principles of comprehensiveness, objectivity and validity, the index system is constructed from four aspects: user side factors, hardware and its function configuration, environmental protection and cleanliness, and environmental impact. Then in order to improve the index set science and refinement, based on the theory of Group Analytic hierarchy process (AHP) and G1 method, the hierarchical clustering algorithm is used to mine the potential evaluation preference of expert group, and the three-scale model is constructed to calculate the index weight. The weak weight index screening model is obtained. Finally, the model is used to select and optimize the initial index system, and the final energy efficiency index system of smart home is obtained.
【作者单位】： 四川大学电气信息学院;国网北京市电力公司;
【分类号】：TM76;TU855
[Abstract]:As an important part of smart grid in smart power consumption, smart home should have the function of optimizing household power consumption mode and improving energy consumption efficiency. Therefore, an index system to evaluate the energy efficiency of smart home power is proposed. Firstly, according to the principles of comprehensiveness, objectivity and validity, the index system is constructed from four aspects: user side factors, hardware and its function configuration, environmental protection and cleanliness, and environmental impact. Then in order to improve the index set science and refinement, based on the theory of Group Analytic hierarchy process (AHP) and G1 method, the hierarchical clustering algorithm is used to mine the potential evaluation preference of expert group, and the three-scale model is constructed to calculate the index weight. The weak weight index screening model is obtained. Finally, the model is used to select and optimize the initial index system, and the final energy efficiency index system of smart home is obtained.
【作者单位】： 四川大学电气信息学院;国网北京市电力公司;
【分类号】：TM76;TU855
【参考文献】
相关期刊论文 前10条
1 曲朝阳;王冲;王蕾;任有学;;智能用电环境下的家庭电力能效评估指标体系[J];华东电力;2014年06期
2 杨小彬;李和明;尹忠东;蒋利民;孟s，
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