| 引用本文: | 刘沛津,史洁琳,孙昱,王柳月,晏东阳.边缘计算模式下的电力用户能效评估方法[J].哈尔滨工业大学学报,2023,55(12):93.DOI:10.11918/202209068 |
| LIU Peijin,SHI Jielin,SUN Yu,WANG Liuyue,YAN Dongyang.Energy efficiency evaluation method for power users in edge computing mode[J].Journal of Harbin Institute of Technology,2023,55(12):93.DOI:10.11918/202209068 |
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| 边缘计算模式下的电力用户能效评估方法 |
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刘沛津1,史洁琳1,孙昱2,王柳月1,晏东阳1
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(1.西安建筑科技大学 机电工程学院,西安 710055;2.西安建筑科技大学 理学院,西安 710055)
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| 摘要: |
| 为提高电力用户能效评估的客观性和准确性,并满足用户对于用电能效及时反馈调整的需求,提出一种在边缘架构下实时动态评估电力用户能效的方法。在构建边缘侧评估框架的基础上,首先,基于“压力-状态-响应”概念模型分析指标间的动态逻辑关系,从多维度选取动态评价指标,构建用户能效评估指标集合。考虑到边缘节点存储资源的受限,从集合中抽象出指标的重要性、均衡性、独立性三重指标属性进行量化,通过影响度和优化度模型对3种属性的量化值进行融合,并采用合作博弈论优选边缘侧精简指标集,从而有效地对边缘侧数据去冗余。其次,基于CRITIC(criteria importance though intercrieria correlation)权重计算法,充分利用指标的数据信息,对本方法所提指标赋予更为客观的权重系数。最后,通过改进灰色TOPSIS(technique for order preference by similarity to an ideal solution)评估方法构造绝对理想解,以有效避免用户数量动态变化时所产生的逆排序问题,引入的灰色关联度可弥补传统方法中欧式判据无法准确衡量用户优劣性的缺陷。结果表明,所提边缘能效评估方法不仅大幅降低了数据存储的需求,评估结果的可靠性和鲁棒性也得到了充分保证,这对于减少数据上传规模、快速完成用户能效评价方面具有明显优势。 |
| 关键词: 边缘节点 能效评估 指标属性特征 灰色关联度 逼近理想解法(TOPSIS) |
| DOI：10.11918/202209068 |
| 分类号:TM93 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(61903291) |
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| Energy efficiency evaluation method for power users in edge computing mode |
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LIU Peijin1,SHI Jielin1,SUN Yu2,WANG Liuyue1,YAN Dongyang1
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(1.School of Mechanical and Electrical Engineering,Xian University of Architecture and Technology, Xian 710055, China; 2.School of Mechatronic Science, Xian University of Architecture and Technology, Xian 710055, China)
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| Abstract: |
| To improve the objectivity and accuracy of energy efficiency evaluation of power users and meet the needs of userss demand for timely feedback and adjustment of energy efficiency, a real-time dynamic energy efficiency evaluation method for power users under edge architecture is proposed. On the basis of constructing the edge side evaluation framework, the dynamic logical relationship between the indicators is firstly analyzed based on the “Pressure-State-Response” conceptual model. The dynamic evaluation indicators are selected from multiple dimensions to construct the user energy efficiency evaluation index set. Considering the limited storage resources of edge nodes, the three attributes of importance, balance and independence of indicators are abstracted from the set to quantify. The quantified values of the three attributes are fused by the influence degree and optimization degree model, and the cooperative game theory is used to optimize the edge side to simplify the indicator set, so as to effectively remove the redundancy of the edge side data. Secondly, based on the CRITIC (criteria importance though intercrieria correlation) weight calculation method, the data information of the index is fully utilized, and a more objective weight coefficient is given to the index proposed in this method. Finally, the absolute ideal solution is constructed by improving the grey TOPSIS (technique for order preference by similarity to an ideal solution) evaluation method to effectively avoid the reverse ranking problem caused by the dynamic change of the number of users. The introduced grey correlation degree can make up for the defect that the European criterion cannot accurately measure the advantages and disadvantages of users in the traditional method. The experimental results show that the proposed edge energy efficiency evaluation method not only greatly reduces the demand for data storage, but also fully guarantees the reliability and robustness of the evaluation results, which has obvious advantages in reducing the scale of data upload and quickly completing user energy efficiency evaluation. |
| Key words: edge node energy efficiency assessment index attribute characteristics grey correlation degree TOPSIS |
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