上海交通大学学报

上海交通大学学报 >

2023 , Vol. 57 >Issue 7: 868 - 877

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2022.117

新型电力系统与综合能源

基于改进TOPSIS的楼宇多指标综合评价

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  • 1.国网湖南省电力有限公司,长沙 410004
    2.长沙理工大学 电气与信息工程学院,长沙 410114
    3.三峡大学 电气与新能源学院,湖北 宜昌 443002
    4.湖南大学 电气与信息工程学院,长沙 410082
蒋毅(1971-),硕士,从事综合能源系统能效优化与治理研究.

收稿日期: 2022-04-18

  修回日期: 2023-01-18

  录用日期: 2023-02-24

  网络出版日期: 2023-04-17

基金资助

国家自然科学基金(51877012)

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A Comprehensive Evaluation Model of Buildings Based on Improved TOPSIS

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  • 1. State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China
    2. School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China
    3. College of Electrical Engineering and New Energy,China Three Gorges University, Yichang 443002, Hubei, China
    4. College of Electrical and Information Engineering, Hunan University, Changsha 410082, China

Received date: 2022-04-18

  Revised date: 2023-01-18

  Accepted date: 2023-02-24

  Online published: 2023-04-17

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摘要

为综合评价大型办公楼宇在能耗、环保、经济性等方面的运行情况,提出基于改进灰色关联逼近理想解排序法(TOPSIS)的多指标综合评价模型.在对楼宇运行实际情况分析的基础上,构建包含楼宇运行能耗、环境因素、经济性的多指标评价体系;引入改进TOPSIS评价方法,利用灰色关联度算法和层次分析法-熵权法确定TOPSIS评估模型距离测度;建立楼宇多属性加权评价模型,全面分析楼宇运行状况.分析8栋电力办公楼宇单元的多指标评价可知:楼宇综合评价结果随时间变化,能耗指标评分起主要作用;与采用其他评价方法的评价结果进行对比,验证了所提楼宇多指标评价模型的有效性.

关键词： 改进灰色关联逼近理想解排序法; 层次分析法; 熵权法; 灰色关联度算法; 办公楼宇

本文引用格式

蒋毅, 傅俊诚, 李泽文, 张雨青, 尹骏刚, 姚建刚 . 基于改进TOPSIS的楼宇多指标综合评价[J]. 上海交通大学学报, 2023 , 57(7) : 868 -877 . DOI: 10.16183/j.cnki.jsjtu.2022.117

Abstract

In order to evaluate the operation of energy consumption, environmental protection, and economy, a multi-index comprehensive evaluation model based on an improved technique for order preference by similarity to ideal solution (TOPSIS) is proposed. Based on the analysis of building operation, a multi-index evaluation system is constructed. Then, an improved TOPSIS evaluation method is introduced and a distance measure of the TOPSIS evaluation model by the gray correlation algorithm and analytic hierarchy process (AHP)-entropy weight method is determined. Next, a multi-attribute weighted evaluation model is established to analyze the building operation comprehensively. The multi-index evaluation of eight power office buildings indicates that the building comprehensive evaluation results vary with time and the energy consumption index score plays the main role in all indexes. A comparison of the evaluation results with those obtained by other evaluation methods verifies the effectiveness of the proposed building multi-index evaluation model.

Key words： improved technique for order preference by similarity to ideal solution (TOPSIS); analytic hierarchy process (AHP); entropy weight method; gray correlation algorithm; office buildings

参考文献

[1] 赵景茜, 米翰宁, 程昊文, 等. 考虑岸电负荷弹性的港区综合能源系统规划模型与方法[J]. 上海交通大学学报, 2021, 55(12): 1577-1585.
[1] ZHAO Jingqian, MI Hanning, CHENG Haowen, et al. A planning model and method for an integrated port energy system considering shore power load flexibility[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1577-1585.
[2] 王文彬, 郑蜀江, 范瑞祥, 等. “双碳”背景下微网分布式电能交易绩效评价指标与方法[J]. 上海交通大学学报, 2022, 56(3): 312-324.
[2] WANG Wenbin, ZHENG Shujiang, FAN Ruixiang, et al. Performance evaluation index and method of micro-grid distributed electricity trading under the background of “carbon peaking and carbon neutrality”[J]. Journal of Shanghai Jiao Tong University, 2022, 56(3): 312-324.
[3] 王立斌, 孙寻航, 杨迪, 等. 基于大数据的专变客户用能健康状态综合评价[J]. 智慧电力, 2021, 49(12): 96-103.
[3] WANG Libin, SUN Xunhang, YANG Di, et al. Comprehensive evaluation of energy utilization health status of specialized transformer customers based on big data[J]. Smart Power, 2021, 49(12): 96-103.
[4] 陈柏森, 廖清芬, 刘涤尘, 等. 区域综合能源系统的综合评估指标与方法[J]. 电力系统自动化, 2018, 42(4): 174-182.
[4] CHEN Baisen, LIAO Qingfen, LIU Dichen, et al. Comprehensive evaluation indices and methods for regional integrated energy system[J]. Automation of Electric Power Systems, 2018, 42(4): 174-182.
[5] 张世翔, 吕帅康. 面向园区微电网的综合能源系统评价方法[J]. 电网技术, 2018, 42(8): 2431-2439.
[5] ZHANG Shixiang, Lü Shuaikang. Evaluation method of park-level integrated energy system for microgrid[J]. Power System Technology, 2018, 42(8): 2431-2439.
[6] 李金良, 刘怀东, 王睿卓, 等. 基于交叉超效率CCR模型的综合能源系统综合效率评价[J]. 电力系统自动化, 2020, 44(11): 78-86.
[6] LI Jinliang, LIU Huaidong, WANG Ruizhuo, et al. Comprehensive efficiency evaluation of integrated energy system based on cross-super-efficiency CCR model[J]. Automation of Electric Power Systems, 2020, 44(11): 78-86.
[7] 董福贵, 张也, 尚美美. 分布式能源系统多指标综合评价研究[J]. 中国电机工程学报, 2016, 36(12): 3214-3223.
[7] DONG Fugui, ZHANG Ye, SHANG Meimei. Multi-criteria comprehensive evaluation of distributed energy system[J]. Proceedings of the CSEE, 2016, 36(12): 3214-3223.
[8] 郭艳飞, 任雪桂, 鞠力, 等. 基于层次分析法的综合能源系统能效评估方法研究及应用[J]. 电力科学与技术学报, 2018, 33(4): 121-128.
[8] GUO Yanfei, REN Xuegui, JU Li, et al. The comprehensive efficiency evaluation method for integrated energy system based on AHP[J]. Journal of Electric Power Science & Technology, 2018, 33(4): 121-128.
[9] 赵洪山, 李静璇. 基于PSR和改进灰色TOPSIS的园区客户能效评估模型[J]. 中国电力, 2022, 55(3): 203-212.
[9] ZHAO Hongshan, LI Jingxuan. Energy efficiency evaluation model of park customers based on PSR and improved grey TOPSIS[J]. Electric Power, 2022, 55(3): 203-212.
[10] REN H B, GAO W J, ZHOU W S, et al. Multi-criteria evaluation for the optimal adoption of distributed residential energy systems in Japan[J]. Energy Policy, 2009, 37(12): 5484-5493.
[11] 姜雅男, 于永进, 李长云. 基于改进TOPSIS模型的绝缘纸机-热老化状态评估方法[J]. 电工技术学报, 2022, 37(6): 1572-1582.
[11] JIANG Yanan, YU Yongjin, LI Changyun. Evaluation method of insulation paper deterioration status with mechanical-thermal synergy based on improved TOPSIS model[J]. Transactions of China Electrotechnical Society, 2022, 37(6): 1572-1582.
[12] 张守华, 孙树栋. 基于AHP和区间模糊TOPSIS法的高新技术科研项目评价[J]. 上海交通大学学报, 2011, 45(1): 134-138.
[12] ZHANG Shouhua, SUN Shudong. Evaluation of high-tech research project based on internal fuzzy TOPSIS and AHP[J]. Journal of Shanghai Jiao Tong University, 2011, 45(1): 134-138.
[13] 周怀亮. 建筑能效评估系统设计[D]. 济南: 山东大学, 2014.
[13] ZHOU Huailiang. Design of building energy efficiency evaluation system[D]. Jinan: Shandong University, 2014.
[14] 林顺富, 胡飞, 郝朝, 等. 基于数据挖掘的楼宇电力能耗分析模型研究[J]. 电测与仪表, 2018, 55(20): 52-59.
[14] LIN Shunfu, HU Fei, HAO Chao, et al. Study on the power consumption analysis model of building based on data mining[J]. Electrical Measurement & Instrumentation, 2018, 55(20): 52-59.
[15] 林顺富, 田二伟, 符杨, 等. 基于信息熵分段聚合近似和谱聚类的负荷分类方法[J]. 中国电机工程学报, 2017, 37(8): 2242-2253.
[15] LIN Shunfu, TIAN Erwei, FU Yang, et al. Power load classification method based on information entropy piecewise aggregate approximation and spectral clustering[J]. Proceedings of the CSEE, 2017, 37(8): 2242-2253.
[16] 郑玉平, 王丹, 万灿, 等. 面向新型城镇的能源互联网关键技术及应用[J]. 电力系统自动化, 2019, 43(14): 2-15.
[16] ZHENG Yuping, WANG Dan, WAN Can, et al. Key technology and application of energy Internet oriented to new-type towns[J]. Automation of Electric Power Systems, 2019, 43(14): 2-15.
[17] 刘豪, 朱彤, 张涛. 上海地区不同类型建筑的CCHP-ORC系统评价与分析[J]. 中国电机工程学报, 2016, 36(12): 3198-3206.
[17] LIU Hao, ZHU Tong, ZHANG Tao. Evaluation and analysis of CCHP-ORC system for different buildings in Shanghai[J]. Proceedings of the CSEE, 2016, 36(12): 3198-3206.
[18] 张涛, 朱彤, 高乃平, 等. 分布式冷热电能源系统优化设计及多指标综合评价方法的研究[J]. 中国电机工程学报, 2015, 35(14): 3706-3713.
[18] ZHANG Tao, ZHU Tong, GAO Naiping, et al. Optimization design and multi-criteria comprehensive evaluation method of combined cooling heating and power system[J]. Proceedings of the CSEE, 2015, 35(14): 3706-3713.
[19] ROSEN M A, LE M N, DINCER I. Exergetic analysis of cogeneration-based district energy systems[J]. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power & Energy, 2004, 218(6): 369-375.
[20] 刘万勋, 于琳琳, 张丽华, 等. 基于AHP和多级模糊综合评判的电网发展水平评估[J]. 智慧电力, 2020, 48(5): 80-85.
[20] LIU Wanxun, YU Linlin, ZHANG Lihua, et al. Evaluation of power grid development level based on AHP and multi-level fuzzy comprehensive evaluation[J]. Smart Power, 2020, 48(5): 80-85.
[21] 邓燕国, 王冰, 曹智杰, 等. 基于熵权法与GRA-ELM的配电网空间负荷预测[J]. 电力工程技术, 2021, 40(4): 136-141.
[21] DENG Yanguo, WANG Bing, CAO Zhijie, et al. Spatial load forecasting of distribution network based on entropy weight method and GRA-ELM[J]. Electric Power Engineering Technology, 2021, 40(4): 136-141.
[22] 丁胜, 徐承美, 饶尧, 等. 楼宇空调需求响应实时控制仿真与实践研究[J]. 电力需求侧管理, 2022, 24(6): 91-98.
[22] DING Sheng, XU Chengmei, RAO Yao, et al. Simulation and practice on demand response real-time control of building air conditioning[J]. Power Demand Side Management, 2022, 24(6): 91-98.
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