基于联盟链技术的商业建筑转供电主体需求响应策略

doi:10.11930/j.issn.1004-9649.202309098

中国电力 ›› 2024, Vol. 57 ›› Issue (12): 109-119.DOI: 10.11930/j.issn.1004-9649.202309098

基于联盟链技术的商业建筑转供电主体需求响应策略

唐志辉¹(), 张欣¹(), 宁艺飞¹(), 黄璜¹, 余昆², 华昊辰², 曹佳伟², 郑云天²

1. 国网江苏省电力有限公司南京供电分公司，江苏南京　210008
2. 河海大学电气与动力工程学院，江苏南京　210024

收稿日期:2023-09-21 接受日期:2024-04-01 出版日期:2024-12-28 发布日期:2024-12-27
作者简介:唐志辉（1995—），男，硕士，从事电价电费管理工作，E-mail：tang@jeffery.top
宁艺飞（1990—），男，通信作者，博士，工程师，从事电价电费管理工作，E-mail：yf_ning_hhu@126.com
基金资助:
国网江苏省电力有限公司重点科技项目（面向转供电环境的用电服务区块链关键技术开发服务，J2022096）。

Demand Response Strategy for Commercial Building Power Supply Conversion Entities Based on Alliance Chain Technology

Zhihui TANG¹(), Xin ZHANG¹(), Yifei NING¹(), Huang HUANG¹, Kun YU², Haochen HUA², Jiawei CAO², Yuntian ZHENG²

1. Nanjing Power Supply Company of State Grid Jiangsu Electric Power Co., Ltd., Nanjing 210008, China
2. School of Electrical and Power Engineering, Hohai University, Nanjing 210024, China

Received:2023-09-21 Accepted:2024-04-01 Online:2024-12-28 Published:2024-12-27
Supported by:
This work is supported by Key Science and Technology Project of State Grid Jiangsu Electric Power Co., Ltd. (Development Services for Key Blockchain Technologies of Electricity Services in the Context of Power Conversion, No.J2022096).

摘要/Abstract

摘要：

商业建筑柔性资源丰富，可以有效参与需求响应，但商业建筑中普遍存在的转供电行为会造成终端用户参与需求响应积极性不足。一方面，需求响应的结算信息不透明，终端用户对转供电主体缺乏信任；另一方面，转供电主体忽略了终端用户的用电效用，激励机制不合理。针对上述问题，将联盟链技术用于商业建筑转供电需求响应环节，构建基于联盟链的商业建筑转供电需求响应系统，实现需求响应的去中心化与可信传递。针对转供电环境下公共区域和终端用户用电特点，提出考虑商业建筑转供电特征的需求响应策略。将该联盟链系统用于南京市某小型商业建筑环境下进行验证，实现了联盟链在商业建筑需求响应过程中的透明化交易与结算功能。仿真结果表明，该策略成功将转供电主体的用电成本降低了33.6%，证实了所提出策略的有效性。

关键词: 商业建筑, 联盟链, 转供电主体, 需求响应策略

Abstract:

Commercial buildings have abundant flexible resources and can effectively participate in demand response. However, widespread power supply conversion in commercial buildings can lead to insufficient enthusiasm for end users to participate in demand response. On the one hand the settlement information of demand response is not transparent and end users lack trust in the power supply conversion entities, on the other hand, the main power supply conversion entities have ignored the electricity utility of end users, and the incentive mechanism is unreasonable. To address above issues, by applying the alliance chain technology to the demand response of commercial building power supply conversion, this article constructs an alliance chain-based commercial building power supply conversion demand response system to achieve decentralized and reliable transfer of demand response. Based on the electricity consumption characteristics of public areas and end users in the context of power supply conversion, a demand response strategy is proposed with consideration of the power supply conversion characteristics of commercial buildings. The proposed alliance chain system was validated in a small commercial building environment in Nanjing, achieving transparent transaction and settlement functions of the alliance chain in the demand response process of commercial buildings. At the same time, simulation results show that the proposed strategy successfully reduces the electricity consumption cost of the power supply conversion entities by 33.6%, confirming the effectiveness of the proposed strategy.

Key words: commercial building, alliance chain, power supply conversion entities, demand response strategy

唐志辉, 张欣, 宁艺飞, 黄璜, 余昆, 华昊辰, 曹佳伟, 郑云天. 基于联盟链技术的商业建筑转供电主体需求响应策略[J]. 中国电力, 2024, 57(12): 109-119.

Zhihui TANG, Xin ZHANG, Yifei NING, Huang HUANG, Kun YU, Haochen HUA, Jiawei CAO, Yuntian ZHENG. Demand Response Strategy for Commercial Building Power Supply Conversion Entities Based on Alliance Chain Technology[J]. Electric Power, 2024, 57(12): 109-119.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202309098

https://www.electricpower.com.cn/CN/Y2024/V57/I12/109

图/表 11

图 1 转供电场景下的需求响应业务关系

Fig.1 Demand response business relationship in power supply conversion scenarios

图 2 基于联盟链的商业建筑转供电需求响应系统架构

Fig.2 Alliance chain-based commercial building power supply conversion demand response system architecture

图 3 双层博弈模型优化算法流程

Fig.3 Optimization algorithm flow chart for double-layer game model

图 4 室外温度和太阳辐照度

Fig.4 Outdoor temperature and solar irradiance

图 5 各用户无需求响应的基本负荷

Fig.5 Base load without demand response of different users

图 6 公共区域无需求响应的基本负荷

Fig.6 Base load without demand response of public areas

图 7 转供电电价优化的迭代结果

Fig.7 Iteration result of power supply conversion price optimization

表 1 优化后的转供电电价

Table 1 Power supply conversion electricity prices after optimization

时段	参与需求响应优化后电价/(元·(kW·h)^–1)	未参与需求响应优化后电价/(元·(kW·h)^–1)
09:00—10:00	1.28	1.28
10:00—11:00	1.28	1.31
11:00—12:00	1.26	1.31
12:00—13:00	1.28	1.30
13:00—14:00	1.31	1.31
14:00—15:00	1.30	1.26
15:00—16:00	1.32	1.32
16:00—17:00	1.30	1.30
17:00—18:00	1.25	1.26
18:00—19:00	1.22	1.31
19:00—20:00	1.26	1.22
20:00—21:00	1.21	1.31
21:00—22:00	1.21	1.21
22:00—23:00	1.31	1.31

表 2 优化后的电动汽车充电电量

Table 2 Electric vehicle charging capacity after optimization

车辆	期望充电量/(kW·h)	实际充电量/(kW·h)
1	30	27.6
2	20	18.5
3	15	12.9

图 8 公共区域负荷

Fig.8 Load of public areas

图 9 用户总负荷

Fig.9 Total user load

参考文献 25

1	CHEN X Y. Green and low-carbon energy-use[J]. The Innovation Energy, 2024, 1 (1): 100003. DOI
2	国家发展改革委. 国家发展改革委办公厅关于清理规范电网和转供电环节收费有关事项的通知. (发改价格〔2018〕787号)[A]. 2018.
3	袁勇, 王飞跃. 区块链技术发展现状与展望[J]. 自动化学报, 2016, 42 (4): 481- 494.
	YUAN Yong, WANG Feiyue. Blockchain: the state of the art and future trends[J]. Acta Automatica Sinica, 2016, 42 (4): 481- 494.
4	周蠡, 熊川羽, 柯方超, 等. 基于区块链和禀赋效应的主动配电网经济运行方法[J]. 中国电力, 2023, 56 (12): 58- 68.
	ZHOU Li, XIONG Chuanyu, KE Fangchao, et al. Economic operation method of active distribution network based on blockchain and endowment effect[J]. Electric Power, 2023, 56 (12): 58- 68.
5	POP C, CIOARA T, ANTAL M, et al. Blockchain based decentralized management of demand response programs in smart energy grids[J]. Sensors, 2018, 18 (2): 162. DOI
6	WEN S , XIONG W , TAN J , et al. Blockchain enhanced price incentive demand response for building user energy network in sustainable society[J]. Sustainable Cities and Society, 2021(2): 102748.
7	MENGELKAMP E, NOTHEISEN B, BEER C, et al. A blockchain-based smart grid: towards sustainable local energy markets[J]. Computer Science-Research and Development, 2018, 33 (1): 207- 214.
8	KOLAHAN A, MAADI S R, TEYMOURI Z, et al. Blockchain-based solution for energy demand-side management of residential buildings[J]. Sustainable Cities and Society, 2021, 75: 103316.
9	孙毅, 刘昌利, 刘迪, 等. 计及滚动评价的居民群需求响应策略[J]. 中国电力, 2019, 52 (2): 34- 45.
	SUN Yi, LIU Changli, LIU Di, et al. Residents demand response strategy considering rolling evaluation[J]. Electric Power, 2019, 52 (2): 34- 45.
10	ZHANG X Y, BIAGIONI D, CAI M M, et al. An edge-cloud integrated solution for buildings demand response using reinforcement learning[J]. IEEE Transactions on Smart Grid, 2021, 12 (1): 420- 431. DOI
11	JINDAL A, AUJLA G S, KUMAR N, et al. GUARDIAN: blockchain-based secure demand response management in smart grid system[J]. IEEE Transactions on Services Computing, 2020, 13 (4): 613- 624. DOI
12	李昭昱, 艾芊. 分时电价下居民用户用电需求响应估计方法[J]. 电力自动化设备, 2023, 43 (10): 121- 127.
	LI Zhaoyu, AI Qian. Demand response estimation method of electricity consumption for residential customer under time of use price[J]. Electric Power Automation Equipment, 2023, 43 (10): 121- 127.
13	胡可心, 李康平, 刘春阳, 等. 动态分时电价下居民用户需求响应基线负荷预测方法[J/OL]. 电测与仪表, 2023: 1–11. (2023-01-17).https://kns.cnki.net/kcms/detail/23.1202.TH.20230116.1821.002.html.
	HU Kexin, LI Kangping, LIU Chunyang, et al. A baseline load forecasting method for residential demand response under dynamic time-of-use electricity price[J/OL]. Electrical Measurement & Instrumentation, 2023: 1–11. (2023-01-17).https://kns.cnki.net/kcms/detail/23.1202.TH.20230116.1821.002.html.
14	WANG F, ZHOU L D, REN H, et al. Multi-objective optimization model of source-load-storage synergetic dispatch for a building energy management system based on TOU price demand response[J]. IEEE Transactions on Industry Applications, 2018, 54 (2): 1017- 1028. DOI
15	姜昊, 王玉峰. 基于在线学习的面向居民用户激励型需求响应[J]. 电工电能新技术, 2023, 42 (6): 23- 33.
	JIANG Hao, WANG Yufeng. Incentive demand response for residential users based on online learning[J]. Advanced Technology of Electrical Engineering and Energy, 2023, 42 (6): 23- 33.
16	ZHANG Y R, GLOCK C H, CHEN Z X. Estimating the participation value of electricity demand-response programmes for a two-stage production system[J]. International Journal of Production Research, 2022, 60 (21): 6508- 6528. DOI
17	CHEN X, NIE Y T, LI N. Online residential demand response via contextual multi-armed bandits[J]. IEEE Control Systems Letters, 2021, 5 (2): 433- 438. DOI
18	KRIŽAN F, KUNC J, BILKOVÁ K, et al. Transformation and sustainable development of shopping centers: case of Czech and Slovak Cities[J]. Sustainability, 2021, 14 (1): 62.
19	颜拥, 陈星莺, 文福拴, 等. 从能源互联网到能源区块链: 基本概念与研究框架[J]. 电力系统自动化, 2022, 46 (2): 1- 14.
	YAN Yong, CHEN Xingying, WEN Fushuan, et al. From energy internet to energy blockchain: basic concept and research framework[J]. Automation of Electric Power Systems, 2022, 46 (2): 1- 14.
20	阎红灿, 陈子昂, 刘盈. 面向区块链应用的密码算法研究[J]. 华北理工大学学报(自然科学版), 2023, 45 (2): 76- 83.
	YAN Hongcan, CHEN Ziang, LIU Ying. Research on cryptographic algorithms for blockchain applications[J]. Journal of North China University of Science and Technology (Natural Science Edition), 2023, 45 (2): 76- 83.
21	DI SILVESTRE M L, GALLO P, SANSEVERINO E R, et al. Aggregation and remuneration in demand response with a blockchain-based framework[J]. IEEE Transactions on Industry Applications, 2020, 56 (4): 4248- 4257.
22	IFTEKHAR A, CUI X, TAO Q, ZHENG C. Hyperledger fabric access control system for internet of things layer in blockchain-based applications[J]. Entropy, 2021, 23 (8): 1054.
23	MENGELKAMP E, NOTHEISEN B, BEER C, et al. A blockchain-based smart grid: towards sustainable local energy markets[J]. Computer Science-Research and Development, 2018, 33 (1-2): 207- 214.
24	CHEN X Y, BU L, CHEN C, et al. An operational optimization method of regional multi-energy system considering thermal quasi-dynamic characteristics[J]. CSEE Journal of Power and Energy Systems, 2021, PP (99): 1- 13.
25	DU P W, LU N. Appliance commitment for household load scheduling[J]. IEEE Transactions on Smart Grid, 2011, 2 (2): 411- 419. DOI

[1]	吴桐, 惠红勋, 张洪财. 商业建筑空调系统参与城市电网负荷调控综述[J]. 中国电力, 2023, 56(7): 1-11.
[2]	赵建立, 向佳霓, 汤卓凡, 漆磊, 艾芊, 王帝, 殷爽睿. 虚拟电厂在上海的实践探索与前景分析[J]. 中国电力, 2023, 56(2): 1-13.
[3]	石庆松, 秦蕊, 肖鹏, 欧阳丽炜, 熊刚, 张宏鑫, 王飞跃. 基于联盟链的电力物资采购数据共享激励机制[J]. 中国电力, 2022, 55(3): 87-96.

基于联盟链技术的商业建筑转供电主体需求响应策略

Demand Response Strategy for Commercial Building Power Supply Conversion Entities Based on Alliance Chain Technology

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 11

参考文献 25

相关文章 3

编辑推荐

Metrics

模态框（Modal）标题

基于联盟链技术的商业建筑转供电主体需求响应策略

Demand Response Strategy for Commercial Building Power Supply Conversion Entities Based on Alliance Chain Technology

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 11

参考文献 25

相关文章 3

编辑推荐

Metrics