Capacity Allocation Method of Key Equipment in PV System Applied in Office Buildings

doi:10.11930/j.issn.1004-9649.202305114

Abstract

Abstract:

With the goal of carbon peak and carbon neutrality, the photovoltaics, energy storage, direct current, and flexibility (PEDF) system applied in buildings is developing rapidly. The photovoltaic output in urban office buildings is generally lower than the building electricity load. In view of the two optimization objectives of improving the system load supply rate and the smoothness of the electricity curve, this paper studies the equipment capacity allocation methods of various main devices in the PEDF system. In addition, the coordinated configuration and regulation of different internal resources are analyzed, so as to give full play to the flexible capabilities of energy storage and electric vehicles, improve the overall performance of the system, and provide a reference for the subsequent development of the PEDF system in office buildings. The results show that the configuration of the PEDF system in the building can greatly improve the system's self-sufficiency rate and power smoothness and reduce the AC/DC capacity configuration. While increasing the system's flexible adjustment ability, the charging pile for electric vehicles may bring a new peak power load. The energy storage capacity of about 0.2 times the daily load can achieve more than 90% photovoltaic consumption, effectively improving the power curve stability and reducing the AC/DC capacity by 29.1%.

Key words: office building, PEDF, capacity configuration, battery, AC/DC, electric vehicle

Lei ZHANG, Weidong XIAO, Chunbing JIANG, Yao LIU, Shaojie LI, Ji ZHANG. Capacity Allocation Method of Key Equipment in PV System Applied in Office Buildings[J]. Electric Power, 2024, 57(3): 152-159, 169.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202305114

https://www.electricpower.com.cn/EN/Y2024/V57/I3/152

Figures/Tables 10

Fig.1 Topology of PEDF system applied in office building

Table 1 Key equipment parameter

设备	参数	数值
储能	充/放电效率/%	95
	S_OCmax	0.95
	S_OCmin	0.1
	电池充放电倍率/C	0.5
电动汽车	P_EV,max/kW	5
AC/DC	K	1.2

Fig.2 Load data and PV data

Fig.3 Battery capacity configuration at maximum RSS

Fig.4 Overall system energy allocation when PE = 0.8

Fig.5 Battery capacity configuration at maximum α

Fig.6 Comparison of optimization results of two objective functions

Fig.7 System operation power on a typical day

Fig.8 AC/DC capacity configuration

Fig.9 Effect of EV's number on system performance

References 18

1	金晨, 任大伟, 肖晋宇, 等. 支撑碳中和目标的电力系统源-网-储灵活性资源优化规划[J]. 中国电力, 2021, 54 (8): 164- 174.
	JIN Chen, REN Dawei, XIAO Jinyu, et al. Optimization planning on power system supply-grid-storage flexibility resource for supporting the "carbon neutrality" target of China[J]. Electric Power, 2021, 54 (8): 164- 174.
2	詹天津, 谢玉荣. 国内分布式光伏发展形势分析及思考[J]. 华电技术, 2021, 43 (12): 60- 65.
	ZHAN Tianjin, XIE Yurong. Development status analysis and consideration on domestic distributed PV energy[J]. Huadian Technology, 2021, 43 (12): 60- 65.
3	金国. 分布式光伏技术在商业写字楼建筑中的应用[J]. 光源与照明, 2022, (11): 83- 85.
4	谢敏, 高浩睿, 胡海峰. 分布式光伏+储能在民用建筑应用研究与探讨[J]. 建筑电气, 2022, 41 (12): 62- 66.
	XIE Min, GAO Haorui, HU Haifeng. Research and discussion on application of distributed PV+energy storage in civil buildings[J]. Building Electricity, 2022, 41 (12): 62- 66.
5	唐哲. 寒冷地区钢结构工业建筑与太阳能光伏一体化设计研究[D]. 济南: 山东建筑大学, 2015.
	TANG Zhe. Cold region steel structure industrial building and the integration of solar photovoltaic design research[D]. Jinan: Shandong Jianzhu University, 2015.
6	丁明, 王伟胜, 王秀丽, 等. 大规模光伏发电对电力系统影响综述[J]. 中国电机工程学报, 2014, 34 (1): 1- 14.
	DING Ming, WANG Weisheng, WANG Xiuli, et al. A review on the effect of large-scale PV generation on power systems[J]. Proceedings of the CSEE, 2014, 34 (1): 1- 14.
7	李叶茂, 郝斌, 李雨桐. 直流建筑技术展望[J]. 建筑科学, 2022, 38 (2): 40- 49, 98.
	LI Yemao, HAO Bin, LI Yutong. Technological outlook on DC buildings[J]. Building Science, 2022, 38 (2): 40- 49, 98.
8	江亿. 光储直柔: 助力实现零碳电力的新型建筑配电系统[J]. 暖通空调, 2021, 51 (10): 1- 12.
	JIANG Yi. PSDF(photovoltaic, storage, DC, flexible)—a new type of building power distribution system for zero carbon power system[J]. Heating Ventilating & Air Conditioning, 2021, 51 (10): 1- 12.
9	刘晓华, 张涛, 刘效辰, 等. “光储直柔” 建筑新型能源系统发展现状与研究展望[J]. 暖通空调, 2022, 52 (8): 1- 9, 82.
	LIU Xiaohua, ZHANG Tao, LIU Xiaochen, et al. Development statuses and research prospects of PEDF(photovoltaics, energy storage, direct current and flexibility)building energy systems[J]. Heating Ventilating & Air Conditioning, 2022, 52 (8): 1- 9, 82.
10	李叶茂, 李雨桐, 郝斌, 等. 低碳发展背景下的建筑“光储直柔” 配用电系统关键技术分析[J]. 供用电, 2021, 38 (1): 32- 38.
	LI Yemao, LI Yutong, HAO Bin, et al. Key technologies of building power supply and distribution system towards carbon neutral development[J]. Distribution & Utilization, 2021, 38 (1): 32- 38.
11	贾禾, 彭晋卿, 李念平, 等. 动态电价下分布式光伏-储能系统优化与经济性分析[J]. 太阳能学报, 2021, 42 (5): 187- 193.
	JIA He, PENG Jinqing, LI Nianping, et al. Optimization and economic analysis of distributed photovoltaic-energy storage system under dynamic electricity price[J]. Acta Energiae Solaris Sinica, 2021, 42 (5): 187- 193.
12	王超, 胡浩, 郑炼, 等. 基于智慧蓄电池的光伏储能系统及其控制策略[J]. 可再生能源, 2022, 40 (4): 506- 512.
	WANG Chao, HU Hao, ZHENG Lian, et al. Photovoltaic energy storage system based on smart battery and its control strategy[J]. Renewable Energy Resources, 2022, 40 (4): 506- 512.
13	吴小刚, 刘宗歧, 田立亭, 等. 独立光伏系统光储容量优化配置方法[J]. 电网技术, 2014, 38 (5): 1271- 1276.
	WU Xiaogang, LIU Zongqi, TIAN Liting, et al. Optimized capacity configuration of photovoltaic generation and energy storage device for stand-alone photovoltaic generation system[J]. Power System Technology, 2014, 38 (5): 1271- 1276.
14	王文宾, 朱燕舞, 韩天华, 等. 基于随机规划的分布式光伏并网最大准入容量计算[J]. 燕山大学学报, 2018, 42 (6): 510- 518.
	WANG Wenbin, ZHU Yanwu, HAN Tianhua, et al. Maximum access capacity calculation of distributed PV grid connected based on stochastic programming[J]. Journal of Yanshan University, 2018, 42 (6): 510- 518.
15	赵安军, 王鹏柱, 荆竞, 等. 考虑电动汽车影响的农村家庭新能源容量优化配置方法[J]. 中国电力, 2022, 55 (8): 31- 39, 50.
	ZHAO Anjun, WANG Pengzhu, JING Jing, et al. Optimal configuration method of new energy capacity for rural households considering impact of electric vehicles[J]. Electric Power, 2022, 55 (8): 31- 39, 50.
16	苏粟, 蒋小超, 王玮, 等. 计及电动汽车和光伏—储能的微网能量优化管理[J]. 电力系统自动化, 2015, 39 (9): 164- 171.
	SU Su, JIANG Xiaochao, WANG Wei, et al. Optimal energy management for microgrids considering electric vehicles and photovoltaic-energy storage[J]. Automation of Electric Power Systems, 2015, 39 (9): 164- 171.
17	HESSE H, MARTINS R, MUSILEK P, et al. Economic optimization of component sizing for residential battery storage systems[J]. Energies, 2017, 10(7): 835.
18	荣秀婷, 张辉, 朱刘柱, 等. “双碳” 目标下商务楼宇 “光储直柔” 恒功率运行研究[J]. 机械制造与自动化, 2022, 51 (5): 223- 227.
	RONG Xiuting, ZHANG Hui, ZHU Liuzhu, et al. Research on 'photovoltaic, storage and dc flexibility' based constant power operation in commercial buildings under targets of 'Carbon Peak' and 'Carbon Neutral'[J]. Machine Building & Automation, 2022, 51 (5): 223- 227.

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