建筑负荷用能行为习惯与负荷运行特性分析

李建标; 陈建福; 罗晓; 任鹏; 陈勇; 裴星宇; 林宝伟; 曾云洪

doi:10.16513/j.2096-2185.DE.2207608

PDF(1914 KB)

分布式能源 ›› 2022, Vol. 7 ›› Issue (6) : 60-67. DOI: 10.16513/j.2096-2185.DE.2207608

应用技术

建筑负荷用能行为习惯与负荷运行特性分析

李建标 ¹ ,
陈建福 ¹ ,
罗晓 ² ,
任鹏 ² ,
陈勇 ¹ ,
裴星宇 ¹ ,
林宝伟 ² ,
曾云洪 ²

作者信息 +

Analysis of Building Load Energy Use Behavior Habit and Load Operation Characteristic

Author information +

文章历史 +

摘要

在双碳目标政策驱动下，我国正构建以新能源为主体的新型电力系统。未来，建筑将成为集发储用于一身的新型能源综合体，不仅要满足绿色低碳的用能需求，还要满足电力系统灵活电力平衡的需求。为实现电力供需平衡，需要分析建筑负荷用能行为习惯与负荷运行特性，实现建筑负荷的高效控制。从源储网荷(备)网格化能源、分区分类维度，对典型家庭负荷、源储网荷(备)单元系统、典型负荷进行分析，得出家庭光储系统设计需根据家庭负荷及用能行为习惯确定，通过源储网荷(备)日周月季年的用能数据客观评价系统运行情况进而挖掘系统节能改善点，提出典型负荷空调分时启动分区控制、热水器定时控制等设想。

Abstract

Driven by the dual carbon target policy, our country is constructing new power system with new energy as the main body. In the future, the building will become a new energy complex integrating power generation and storage. The building should not only meet the demand of green and low-carbon energy use, but also meet the demand of flexible power balance in the power system. In order to realize the balance of power supply and demand, it is necessary to analyze the behavior habits of building load and load operation characteristics to realize the efficient control of building load. From the grid energy and zonal classification dimensions of source and storage network load (backup), the typical household load, source and storage network load (backup) unit system and typical load are analyzed. It is concluded that the design of the household optical storage system should be determined according to the household load and energy consumption behavior habits. The operation of the system is objectively evaluated through the energy consumption data of the source and storage network load (backup) day, week, month and year, and the improvement points of system energy conservation are explored. Some ideas are put forward, such as time-sharing start-up zoning control of typical load air conditioning and timing control of water heater.

导出引用

李建标, 陈建福, 罗晓, 等. 建筑负荷用能行为习惯与负荷运行特性分析[J]. 分布式能源. 2022, 7(6): 60-67 https://doi.org/10.16513/j.2096-2185.DE.2207608

Jianbiao LI, Jianfu CHEN, Xiao LUO, et al. Analysis of Building Load Energy Use Behavior Habit and Load Operation Characteristic[J]. Distributed Energy Resources. 2022, 7(6): 60-67 https://doi.org/10.16513/j.2096-2185.DE.2207608

中图分类号： TK01

参考文献

列表( 原文顺序 | 文献年度倒序 | 文中引用次数倒序 ) 可视化分析

[1]	刘振亚. 全球能源互联网[M]. 北京：中国电力出版社，2015: 71-100. 本文引用 [1]

[2]	叶季蕾，李斌，张宇，等. 基于全球能源互联网典型特征的储能需求及配置分析[J]. 发电技术，2021, 42(1): 20-30. YE Jilei, LI Bin, ZHANG Yu, et al. Energy storage requirements and configuration analysis based on typical characteristics of global energy internet[J]. Power Generation Technology, 2021, 42(1): 20-30. 本文引用 [1]

[3]	刘正学. 基于柔性负荷的西北乡村多能互补建筑能源系统优化研究[D]. 西安：西安建筑科技大学，2021. LIU Zhengxue. Research on optimization of multi-energy complementary building energy system in northwest of China based on flexible load[D]. Xi'an: Xi'an University of Architecture and Technology, 2021. 本文引用 [1]

[4]	查亚兵，张涛，黄卓，等. 能源互联网关键技术分析[J]. 中国科学：信息科学，2014, 44(6): 702-713. ZHA Yabin, ZHANG Tao, HUANG Zhuo, et al. Analysis of energy internet key technologies[J]. Science China: Information Sciences, 2014, 44(6): 702-713. 本文引用 [1]

[5]	方陈，张宇，廖望，等. 区域能源互联网多能协同优化中的储能效益评估[J]. 电力建设，2021, 42(5): 48-56. FANG Chen, ZHANG Yu, LIAO Wang, et al. Benefit evaluation of energy storage in multi-energy collaborative optimization of regional energy Internet[J]. Electric Power Construction, 2021, 42(5): 48-56. 本文引用 [1]

[6]	董明珠，谭建明，张雪芬，等. 全联接全开放的分布式能源信息智能网络[J]. 制冷与空调，2017, 17(5): 5-9, 23. DONG Mingzhu, TAN Jianming, ZHANG Xuefen, et al. Complete open and interconnection of distributed energy & information intelligent internet[J]. Refrigeration and Air-conditioning, 2017, 17(5): 5-9, 23. 本文引用 [1]

[7]	王灵军，蒋世用，赵志刚，等. 基于需求侧视角的能源互联网[J]. 制冷与空调，2017, 17(12): 17-23. WANG Lingjun, JIANG Shiyong, ZHAO Zhigang, et al. Demand side perspective of energy internet[J]. Refrigeration and Air-conditioning, 2017, 17(12): 17-23. 本文引用 [1]

[8]	李新家，陈霄，严永辉，等. 基于家庭智慧用能的负荷协同优化调节技术研究[J]. 电器与能效管理技术，2021(1): 77-83. LI Xinjia, CHEN Xiao, YAN Yonghui, et al. Research on load coordination optimization and regulation technology based on household smart energy[J]. Electrical & Energy Management Technology, 2021(1): 77-83. 本文引用 [1]

[9]	石凯. 基于模型预测控制的建筑供冷负荷节能优化策略研究[D]. 广州：华南理工大学，2019. SHI Kai. Energy-saving optimization strategy of building cooling load based on model predictive control[D]. Guangzhou: South China University of Technology, 2019. 本文引用 [1]

[10]	熊真真，刘晓春，张皓，等. 商业楼宇负荷可调能力与负荷特征的相关性研究[J]. 电力与能源，2021, 42(4): 392-395, 413. XIONG Zhenzhen, LIU Xiaochun, ZHANG Hao, et al. Study on correlation between load adjustable capacity and load characteristices of commercial buildings[J]. Power & Energy, 2021, 42(4): 392-395, 413. 本文引用 [1]

[11]	赵志刚，唐文强，张雪芬，等. 直流电器及家居直流供用电系统研究与应用[J]. 制冷，2019, 38(3): 1-9. ZHAO Zhigang, TANG Wenqiang, ZHANG Xuefen, et al. Research and application of DC electrical appliances and home DC power supply system[J]. Refrigeration, 2019, 38(3): 1-9. 本文引用 [1]

[12]	余晓丹，徐宪东，陈硕翼，等. 综合能源系统与能源互联网简述[J]. 电工技术学报，2016, 31(1): 1-13. YU Xiaodan, XU Xiandong, CHEN Shuoyi, et al. A brief review to integrated energy system and energy internet[J]. Transactions of China Electrotechnical Society, 2016, 31(1): 1-13. 本文引用 [1]

[13]	罗晓，赵志刚，王灵军. 能源互联网系统与能源路由器[J]. 现代电信科技，2020, 50(1): 144-146. LUO Xiao, ZHAO Zhigang, WANG Lingjun. Energy internet system and energy router[J]. Modern Science & Technology of Telecommunications, 2020, 50(1): 144-146. 本文引用 [1]

[14]	董文杰，田廓，陈云斐，等. 能源互联网下基于博弈与证据理论的综合能源系统评价方法研究[J]. 智慧电力，2020, 48(7): 73-80. DONG Wenjie, TIAN Kuo, CHEN Yunfei, et al. Evaluation method of comprehensive energy system based on game theory & evidence theory under energy internet[J]. Smart Power, 2020, 48(7): 73-80. 本文引用 [2]

[15]	王梦月. 建筑中庭空调负荷及热环境模拟研究[D]. 济南：山东建筑大学，2021. WANG Mengyue. Simulation study on air conditioning load and thermal environment of building atrium[D]. Jinan: Shandong Jianzhu University, 2021. 本文引用 [1]

[16]	宋爽，李中伟，刘勇，等. 住宅小区负荷群用电优化策略研究[J]. 电测与仪表，2021, 58(8): 57-66. SONG Shuang, LI Zhongwei, LIU Yong, et al. Study on optimization strategy of load group power consumption in residential area[J]. Electrical Measurement & Instrumentation, 2021, 58(8): 57-66. 本文引用 [1]

[17]	王晓. 基于负荷特征分析的高校建筑及能源设备组合优化研究[D]. 保定：华北电力大学，2021. WANG Xiao. Research on combination optimization of university buildings and energy equipment based on load characteristic analysis[D]. Baoding: North China Electric Power University, 2021. 本文引用 [1]

[18]	卢一涵，余晓丹，靳小龙，等. 考虑用户用电灵活性的社区能源系统双层优化[J]. 全球能源互联网，2021, 4(2): 133-141. LU Yihan, YU Xiaodan, JIN Xiaolong, et al. Bi-level optimization framework of community energy system considering user flexibility[J]. Journal of Global Energy Interconnection, 2021, 4(2): 133-141. 本文引用 [1]

[19]

郭兴国，敖宇强，刘向伟. 夏热冬冷和夏热冬暖地区家用空气能热水器的经济性分析[J]. 流体机械，2019, 47(7): 80-84, 71.

GUO

Xingguo

, AO

Yuqiang

, LIU

Xiangwei

, ec al. The economic analysis of air energy water heater for household purpose in hot summer and cold winter and hot summer and warm winter areas[J]. Fluid Machinery, 2019, 47(7): 80-84, 71.

本文引用 [1]