CORRELATION CHARACTERISTICS AND OPTIMAL REGULATION OF FLEXIBLE ENERGY CONSUMPTION LOAD IN RESIDENTIAL BUILDINGS

Luo Xi, Li Tingting

Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (6) : 385-392.

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (6) : 385-392. DOI: 10.19912/j.0254-0096.tynxb.2024-0283

CORRELATION CHARACTERISTICS AND OPTIMAL REGULATION OF FLEXIBLE ENERGY CONSUMPTION LOAD IN RESIDENTIAL BUILDINGS

  • Luo Xi1,2, Li Tingting1
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Abstract

In view of the problem that the existing researchs on the optimal scheduling of flexible load in residential buildings does not fully consider the correlation characteristics of different devices due to functional complementarity and user habituality in the use time law, resulting in a large deviation between the calculated value and the actual value of optimization scheduling, a model considering load correlation is proposed for the optimal scheduling of flexible loads in residential buildings. The model, aimed at economic efficiency, was then solved using the CPLEX solver under three different scenarios: that consideriing only temporal overlapping load correlation (scenario 1); that considering temporal order load correlation (scenario 2); and that considering both types of load correlation simultaneously (scenario 3). The results show that: in the load set of common residential buildings with correlation characteristics, the various loads in the cooking load set have temporal overlapping and temporal order load correlations, while the various loads in the domestic hot water load set and the laundry load set only contain the temporal order load correlation. In addition,compared with the results of flexible load optimization scheduling without considering load correlation, the increase proportions of users' electricity costs in scenarios 1, 2 and 3 are 0.00%, 7.57% and 7.57%, respectively, which shows that the timporal order load correlation characteristics cannot be ignored because they have a great influence on the optimal scheduling results of flexible load.

Key words

demand-side management / correlation rules / optimal regulation / flexible load / CPLEX

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Luo Xi, Li Tingting. CORRELATION CHARACTERISTICS AND OPTIMAL REGULATION OF FLEXIBLE ENERGY CONSUMPTION LOAD IN RESIDENTIAL BUILDINGS[J]. Acta Energiae Solaris Sinica. 2025, 46(6): 385-392 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0283

References

[1] 安源, 苏瑞, 郑申印, 等. 计及碳交易和源-荷侧资源的综合能源系统低碳经济优化[J]. 太阳能学报, 2023, 44(11): 547-555.
AN Y, SU R, ZHENG S Y, et al.Low carbon economic optimization of integrated energy system considering carbon trading and source-load side resources[J]. Acta energiae solaris sinica, 2023, 44(11): 547-555.
[2] 刘艳峰, 杨燕子, 罗西. 关中农村不同类型家庭夏季柔性用能负荷多目标优化调度研究[J]. 太阳能学报, 2023, 44(8): 110-118.
LIU Y F, YANG Y Z, LUO X.Multi-objective optimization scheduling model of flexible energy consumption load in summer for different types of rural households in Guanzhong plain[J]. Acta energiae solaris sinica, 2023, 44(8): 110-118.
[3] 罗西, 赵天亮, 刘艳峰, 等. 中国太阳能富集区农村居住社区可平移负荷分组聚合与特性评价[J]. 太阳能学报, 2023, 44(12): 1-8.
LUO X, ZHAO T L, LIU Y F, et al.Shiftable load groupaggregation and characteristic evaluation in China's rural residential communities in solar energyabundantarea[J]. Acta energiae solaris sinica, 2023, 44(12): 1-8.
[4] HAIDER H T, SEE O H, ELMENREICH W.A review of residential demand response of smart grid[J]. Renewable and sustainable energy reviews, 2016, 59: 166-178.
[5] NAN S B, ZHOU M, LI G Y.Optimal residential community demand response scheduling in smart grid[J]. Applied energy, 2018, 210: 1280-1289.
[6] LUO Z Y, PENG J Q, HU M M, et al.Multi-objective optimal dispatch of household flexible loads based on their real-life operating characteristics and energy-related occupant behavior[J]. Building simulation, 2023, 16(11): 2005-2025.
[7] HENGGELER ANTUNES C, ALVES M J, SOARES I.A comprehensive and modular set of appliance operation MILP models for demand response optimization[J]. Applied energy, 2022, 320: 119142.
[8] SHARDA S, SINGH M, SHARMA K.A complete consumer behaviour learning model for real-time demand response implementation in smart grid[J]. Applied intelligence, 2022, 52(1): 835-845.
[9] 龙伟. 基于智能电表的数据分析[D]. 深圳: 深圳大学, 2017.
LONG W.Data analysis based on smart meter[D]. Shenzhen: Shenzhen University, 2017.
[10] 郭晓利, 于阳. 基于云计算的家庭智能用电策略[J]. 电力系统自动化, 2015, 39(17): 114-119, 133.
GUO X L, YU Y.A residential smart power utilization strategy based on cloud computing[J]. Automation of electric power systems, 2015, 39(17): 114-119, 133.
[11] 王孝慈, 董树锋, 王莉, 等. 基于电器状态关联分析的民可平移负荷辨识[J]. 电工技术学报, 2020, 35(23): 4961-4970.
WANG X C, DONG S F, WANG L, et al.Resident shiftable loads monitoring based on load states set correlation analysis[J]. Transactions of China Electrotechnical Society, 2020, 35(23): 4961-4970.
[12] 孙毅, 刘迪, 李彬, 等. 基于家庭用电负荷关联度的实时优化策略[J]. 电网技术, 2016, 40(6): 1825-1829.
SUN Y, LIU D, LI B, et al.Research on real-time optimization strategy based on correlation of household electrical load[J]. Power system technology, 2016, 40(6): 1825-1829.
[13] 曲朝阳, 韩晶, 曲楠, 等. 考虑家电关联与舒适性相结合的用电行为多目标优化模型[J]. 电力系统自动化, 2018, 42(2): 50-57.
QU Y, HAN J, QU N, et al.Multi-objective optimization model of electricity consumption behavior considering combination of household appliance correlation and comfort[J]. Automation of electric power systems, 2018, 42(2): 50-57.
[14] 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.
[15] HAIDER H T, MUHSEN D H, AL-NIDAWI Y M, et al. A novel approach for multi-objective cost-peak optimization for demand response of a residential area in smart grids[J]. Energy, 2022, 254: 124360.
[16] MOTA B, FARIA P, VALE Z.Residential load shifting in demand response events for bill reduction using a genetic algorithm[J]. Energy, 2022, 260: 124978.
[17] LUO F J, KONG W C, RANZI G, et al.Optimal home energy management system with demand charge tariff and appliance operational dependencies[J]. IEEE transactions on smart grid, 2020, 11(1): 4-14.
[18] JIANG Z H, PENG J Q, YIN R X, et al.Stochastic modelling of flexible load characteristics of split-type air conditioners using grey-box modelling and random forest method[J]. Energy and buildings, 2022, 273: 112370.
[19] 杨明, 王元超, 向东, 等. 智能电网中的家庭用电系统建模与优化分析[J]. 电力需求侧管理, 2017, 19(4): 6-10.
YANG M, WANG Y C, XIANG D, et al.Model and optimization analysis for household electricity consumption system in smart grid[J]. Power demand side management, 2017, 19(4): 6-10.
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