DEMAND RESPONSE CONSIDERING AIR SOURCE HEAT PUMP LOAD AGGREGATED PARTICIPATION

Liang Haiping; Xie Xin; Li Shihang

doi:10.19912/j.0254-0096.tynxb.2023-0626

PDF(1895 KB)

Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (8) : 273-280. DOI: 10.19912/j.0254-0096.tynxb.2023-0626

DEMAND RESPONSE CONSIDERING AIR SOURCE HEAT PUMP LOAD AGGREGATED PARTICIPATION

Liang Haiping, Xie Xin, Li Shihang

Author information +

History +

Abstract

Based on the three-level architecture of "grid-aggregator-load", a control strategy for air source heat pump load aggregation to participate in demand response is proposed. As an aggregator of heat pump loads, heating operators use the energy storage capacity of the building itself, combined with time-of-use electricity prices, to minimize heating costs and evaluate the load adjustability potential on the basis of ensuring user thermal comfort. When the power grid dispatching department issues regulation instructions, it considers user comfort and grid regulation needs, and allocates each load adjustment amount based on a multi-objective genetic algorithm, which satisfies the regulation objectives while improving the aggregate power oscillation and large rebound load caused by regulation. question. Finally, simulation verifies the effectiveness of the proposed strategy.

Key words

air source heat pump / demand response / temperature-controlled load / model predictive control / aggregate regulation / load recovery

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Liang Haiping, Xie Xin, Li Shihang. DEMAND RESPONSE CONSIDERING AIR SOURCE HEAT PUMP LOAD AGGREGATED PARTICIPATION[J]. Acta Energiae Solaris Sinica. 2024, 45(8): 273-280 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0626

References

[1] 潘华, 梁作放, 薛强中, 等. 基于分时电价的含风-光-气-储虚拟电厂经济调度[J]. 太阳能学报, 2020, 41(8): 115-122.
PAN H, LIANG Z F, XUE Q Z, et al.Economic dispatch of wind/pv/gas/storage virtual power plant based on time-of-use power price[J]. Acta energiae solaris sinica, 2020, 41(8): 115-122.
[2] 罗毅, 邱实. 基于负荷侧响应的含储热热电联产的风电消纳模型[J]. 太阳能学报, 2021, 42(2): 90-96.
LUO Y, QIU S.A wind power consumption model of chp with thermal energy storage based on demand response[J]. Acta energiae solaris sinica, 2021, 42(2): 90-96.
[3] 王彦龙, 蒋绿林, 沈冰燕, 等. 空气源相变蓄能复叠式热泵供暖系统的研究[J]. 太阳能学报, 2021, 42(9): 14-18.
WANG Y L, JIANG L L, SHEN B Y, et al.Research on air source phase change energy storage cascade heat pump heating system[J]. Acta energiae solaris sinica, 2021, 42(9): 14-18
[4] 姜婷玉, 李亚平, 江叶峰, 等. 温控负荷提供电力系统辅助服务的关键技术综述[J]. 电力系统自动化, 2022, 46(11): 191-207.
JIANG T Y, LI Y P, JIANG Y F, et al.Review on key technologies for providing auxiliary services to power system by thermostatically controlled loads[J]. Automation of electric power systems, 2022, 46(11): 191-207.
[5] AFRAM A, JANABI-SHARIFI F.Theory and applications of HVAC control systems:a review of model predictive control (MPC)[J]. Building and environment, 2014, 72: 343-355.
[6] STURZENEGGER D, GYALISTRAS D, GWERDER M, et al.Model predictive control of a Swiss office building[C]//Clima 2013: 11th REHVA World Congress and 8th International Conference" Energy Efficient, Smart and Healthy Buildings", Prague, Czech Republic, 2013: 3227-3236.
[7] MASY G, GEORGES E, VERHELST C, et al.Smart grid energy flexible buildings through the use of heat pumps and building thermal mass as energy storage in the Belgian context[J]. Science and technology for the built environment, 2015, 21(6): 800-811.
[8] LI X W, MALKAWI A.Multi-objective optimization for thermal mass model predictive control in small and medium size commercial buildings under summer weather conditions[J]. Energy, 2016, 112: 1194-1206.
[9] 李亚平, 姚建国, 雍太有, 等. 居民温控负荷聚合功率及响应潜力评估方法研究[J]. 中国电机工程学报, 2017, 37(19): 5519-5528, 5829.
LI Y P, YAO J G, YONG T Y, et al.Estimation approach to aggregated power and response potential of residential thermostatically controlled loads[J]. Proceedings of the CSEE, 2017, 37(19): 5519-5528, 5829.
[10] 王怡岚, 童亦斌, 黄梅, 等. 基于需求侧响应的空调负荷虚拟储能模型研究[J]. 电网技术, 2017, 41(2): 394-401.
WANG Y L, TONG Y B, HUANG M, et al.Research on virtual energy storage model of air conditioning loads based on demand response[J]. Power system technology, 2017, 41(2): 394-401.
[11] 王丹, 兰宇, 贾宏杰, 等. 基于弹性温度可调裕度的中央空调集群需求响应双层优化[J]. 电力系统自动化, 2018, 42(22): 118-126, 134.
WANG D, LAN Y, JIA H J, et al.Double-layer optimization strategy of cluster central air-conditioner demand response based on elastic temperature adjustable margin[J]. Automation of electric power systems, 2018, 42(22): 118-126, 134.
[12] BASHASH S, FATHY H K.Modeling and control of aggregate air conditioning loads for robust renewable power management[J]. IEEE transactions on control systems technology, 2013, 21(4): 1318-1327.
[13] 武昕, 梁凯鑫, 焦点, 等. 面向清洁能源跟踪的空调分组协同方法[J]. 电力系统自动化, 2020, 44(11): 68-77.
WU X, LIANG K X, JIAO D, et al.Collaborative method of air conditioner grouping for clean energy tracking[J]. Automation of electric power systems, 2020, 44(11): 68-77.
[14] 程林, 万宇翔, 张放, 等. 基于负荷聚合商业务的空调服务运作模式及控制策略[J]. 电力系统自动化, 2018, 42(18): 8-16.
CHENG L, WAN Y X, ZHANG F, et al.Operation mode and control strategy for air-conditioning service based on business of load aggregator[J]. Automation of electric power systems, 2018, 42(18): 8-16.
[15] WANG J X, CHEN X Y, XIE J, et al.Dynamic control strategy of residential air conditionings considering environmental and behavioral uncertainties[J]. Applied energy, 2019, 250: 1312-1320.
[16] 周磊, 李扬, 高赐威. 聚合空调负荷的温度调节方法改进及控制策略[J]. 中国电机工程学报, 2014, 34(31): 5579-5589.
ZHOU L, LI Y, GAO C W.Improvement of temperature adjusting method for aggregated air-conditioning loads and its control strategy[J]. Proceedings of the CSEE, 2014, 34(31): 5579-5589.
[17] 刘萌, 褚晓东, 张文, 等. 基于多样性保持的空调负荷群调度控制策略[J]. 中国电机工程学报, 2014, 34(22): 3674-3682.
LIU M, CHU X D, ZHANG W, et al.Dispatch and control strategies for air-conditioning load groups based on maintenance of load diversity[J]. Proceedings of the CSEE, 2014, 34(22): 3674-3682.
[18] LIU M, TIAN Y Y, CHENG D Y, et al.Modelling and control of central air-conditioning loads for power system emergency frequency control[J]. IET generation, transmission & distribution, 2022, 16(20): 4054-4067.
[19] 程定一. 基于空调负荷建模的源-荷协同备用优化配置研究[D]. 济南: 山东大学, 2019.
CHENG D Y.Studies on co-optimization of reserve allocation for supply/demand sides based on modeling of air conditioning loads[D]. Ji’nan: Shandong University, 2019.