A Comprehensive Evaluation Model of Buildings Based on Improved TOPSIS

doi:10.16183/j.cnki.jsjtu.2022.117

Abstract

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

CLC Number:

TM925

JIANG Yi, FU Juncheng, LI Zewen, ZHANG Yuqing, YIN Jungang, YAO Jiangang. A Comprehensive Evaluation Model of Buildings Based on Improved TOPSIS[J]. Journal of Shanghai Jiao Tong University, 2023, 57(7): 868-877.

Figures/Tables 10

Fig.1

Tab.1

Fig.2

Tab.2

Tab.3

Tab.4

Fig.3

Tab.5

Evaluation results by using improved TOPSIS

楼宇单元	$L_{i}^{+}$ $L i +$	$L_{i}^{-}$ $L i -$	T_i	评分排序
#1	0.707	0.492	0.590	4
#2	0.617	0.529	0.538	6
#3	0.825	0.516	0.615	2
#4	0.668	0.564	0.542	5
#5	0.859	0.583	0.596	3
#6	0.776	0.451	0.632	1
#7	0.529	0.677	0.439	8
#8	0.553	0.624	0.470	7

Tab.5

Fig.4

Tab.6

References 22

[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.
	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.
	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.
	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.
	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.
	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.
	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.
	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.
	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.
	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. doi: 10.1016/j.enpol.2009.08.014 URL
[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.
	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.
	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.
	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.
	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.
	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.
	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.
	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.
	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.
	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.
	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.
	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.

指标		编号	指标类型
一级	二级	编号	指标类型
E₁	投资成本	E₁₁	成本型
E₁	运维成本	E₁₂	成本型
E₁	购能成本	E₁₃	成本型
E₂	用电量	E₂₁	成本型
E₂	主要设备能效	E₂₂	效益型
E₃	CO₂年排放量	E₃₁	成本型
E₃	NO_x年排放量	E₃₂	成本型
E₃	可再生能源利用率	E₃₃	效益型

楼宇单元	投资成本	运维成本	购能成本	用电量	主要设备能效	CO₂年排放量	NO_x年排放量	可再生能源利用率
#1	0.213	0.101	0.217	0.347	0.233	0.154	0.121	0.324
#2	0.221	0.097	0.174	0.275	0.192	0.132	0.089	0.267
#3	0.304	0.114	0.193	0.288	0.214	0.201	0.096	0.421
#4	0.187	0.103	0.181	0.323	0.228	0.167	0.126	0.305
#5	0.247	0.125	0.244	0.315	0.216	0.145	0.097	0.299
#6	0.226	0.133	0.248	0.324	0.225	0.218	0.101	0.314
#7	0.277	0.159	0.251	0.297	0.195	0.199	0.124	0.322
#8	0.241	0.121	0.212	0.284	0.197	0.177	0.132	0.412

参数	第一主成分系数	第二主成分系数
投资成本	0.5112	0.2014
运维成本	-0.0025	0.0171
购能成本	0.3521	0.4428
用电量	0.2037	0.3212
主要设备能效	0.4057	-0.1546
CO₂年排放量	0.1282	0.5143
NO_x年排放量	0.2143	0.3012
可再生能源利用率	0.1733	-0.2938