SHIFTABLE LOAD GROUP AGGREGATION AND CHARACTERISTIC EVALUATION IN CHINA'S RURAL RESIDENTIAL COMMUNITIES IN SOLAR ENERGY ABUNDANT AREA

Luo Xi, Zhao Tianliang, Liu Yanfeng, Yang Yanzi

Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (12) : 1-8.

PDF(2077 KB)
Welcome to visit Acta Energiae Solaris Sinica, Today is
PDF(2077 KB)
Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (12) : 1-8. DOI: 10.19912/j.0254-0096.tynxb.2022-1347

SHIFTABLE LOAD GROUP AGGREGATION AND CHARACTERISTIC EVALUATION IN CHINA'S RURAL RESIDENTIAL COMMUNITIES IN SOLAR ENERGY ABUNDANT AREA

  • Luo Xi1,2, Zhao Tianliang1, Liu Yanfeng1,2, Yang Yanzi1
Author information +
History +

Abstract

In this paper, a typical rural area in northern Shaanxi province was investigated, Monte Carlo simulation was used to generate aggregated shiftable load curves on the basis of family clustering, and a comprehensive evaluation from the perspectives of time, energy, and randomness was given. The results show that the volume of cooking load is large but the time range to be shifted is small, while the volume of laundry load is small but the time range to be shifted was large. Overall, domestic hot water load is more comprehensive in the above three aspects, the heat storage properties of water tank makes the shiftable load potential more significant.

Key words

solar energy / demand-side management / Monte Carlo simulation / K-means clustering / shiftable load / grouping aggreation / characteristic evaluation

Cite this article

Download Citations
Luo Xi, Zhao Tianliang, Liu Yanfeng, Yang Yanzi. SHIFTABLE LOAD GROUP AGGREGATION AND CHARACTERISTIC EVALUATION IN CHINA'S RURAL RESIDENTIAL COMMUNITIES IN SOLAR ENERGY ABUNDANT AREA[J]. Acta Energiae Solaris Sinica. 2023, 44(12): 1-8 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1347

References

[1] ZHU L, LIAO H, HOU B D, et al.The status of household heating in northern China: a field survey in towns and villages[J]. Environmental science and pollution research, 2020, 27(14): 16145-16158.
[2] THEBAULT M, GAILLARD L.Optimization of the integration of photovoltaic systems on buildings for self-consumption-case study in France[J]. City and Environment Interactions, 2021, 10: 100057.
[3] ROTH L, YILDIZ Ö, LOWITZSCH J.An empirical approach to differences in flexible electricity consumption behaviour of urban and rural populations-lessons learned in Germany[J]. Sustainability, 2021, 13(16): 9028.
[4] NAN S B, ZHOU M, LI G Y.Optimal residential community demand response scheduling in smart grid[J]. Applied energy, 2018, 210: 1280-1289.
[5] GUPTA P, VERMA Y P.Optimization of deviation settlement charges using residential demand response under frequency linked pricing environment[J]. IET generation, transmission and distribution, 2019, 13(12): 2362-2371.
[6] 赫卫国, 夏俊荣, 刘志明, 等. 考虑用户缴费满意度与用电舒适度的用电优化策略[J]. 电力需求侧管理, 2020, 22(1): 69-74.
HE W G, XIA J R, LIU Z M, et al.Power optimal strategy considering user-charging satisfaction and user comfort[J]. Power demand side management, 2020, 22(1): 69-74.
[7] 杨秀, 傅广努, 刘方, 等. 考虑多重因素的空调负荷聚合响应潜力评估及控制策略研究[J]. 电网技术, 2022, 46(2): 699-714.
YANG X, FU G N, LIU F, et al.Potential evaluation and control strategy of air conditioning load aggregation response considering multiple factors[J]. Power system technology, 2022, 46(2): 699-714.
[8] 王珂, 姚建国, 姚良忠, 等. 电力柔性负荷调度研究综述[J]. 电力系统自动化, 2014, 38(20): 127-135.
WANG K, YAO J G, YAO L Z, et al.Survey of research on flexible loads scheduling technologies[J]. Automation of electric power systems, 2014, 38(20): 127-135.
[9] YIN R X, KARA E C, LI Y P, et al.Quantifying flexibility of commercial and residential loads for demand response using setpoint changes[J]. Applied energy, 2016, 177: 149-164.
[10] VELLEI M, LE DRÉAU J, ABDELOUADOUD S Y. Predicting the demand flexibility of wet appliances at national level: the case of France[J]. Energy and buildings, 2020, 214: 109900.
[11] D’HULST R, LABEEUW W, BEUSEN B, et al. Demand response flexibility and flexibility potential of residential smart appliances: experiences from large pilot test in Belgium[J]. Applied energy, 2015, 150: 79-90.
[12] LIU Y F, WANG P, LUO X, et al.Analysis of flexible energy use behavior of rural residents based on two-stage questionnaire: a case study in Xi’an, China[J]. Energy and buildings, 2022, 269: 112246.
[13] AL WAKEEL A, WU J, JENKINS N. k-means based load estimation of domestic smart meter Measurements[J]. Applied energy, 2017, 194: 333-342.
[14] 严强, 李扬, 樊友杰, 等. 基于加权表决集成聚类的居民用电行为回归分析[J]. 电网技术, 2021, 45(11): 4435-4446.
YAN Q, LI Y, FAN Y J, et al.Regression analysis of residential electricity consumption behavior based on weighted voting ensemble clustering[J]. Power system technology, 2021, 45(11): 4435-4446.
[15] 刘蓉晖, 李子林, 杨秀等. 考虑用户侧柔性负荷的社区综合能源系统日前优化调度[J]. 太阳能学报, 2019, 40(10): 2842-2850.
LIU R H, LI Z L, YANG X, et al.Optimal dispatch of community integrated energy system considering user-side flexible load[J]. Acta energiae solaris sinica, 2019, 40(10): 2842-2850.
PDF(2077 KB)

Accesses

Citation

Detail

Sections
Recommended

/