Electric Power ›› 2024, Vol. 57 ›› Issue (1): 140-147.DOI: 10.11930/j.issn.1004-9649.202309093
• Low-Carbon Planning and Operation for New-Type Power Systems • Previous Articles Next Articles
Juncheng ZHANG1(), Min LI1(
), Zhiwen LIU2(
), Jing TAN1, Yigang TAO1, Tianlu LUO1
Received:
2023-09-20
Accepted:
2023-12-19
Online:
2024-01-23
Published:
2024-01-28
Supported by:
Juncheng ZHANG, Min LI, Zhiwen LIU, Jing TAN, Yigang TAO, Tianlu LUO. Hierarchical Cluster Control Method for Flexible Load in Distribution Network Based on Improved Alternating Direction Multiplier Method[J]. Electric Power, 2024, 57(1): 140-147.
接入类型 | 接入数量/个 | 总容量/kW | ||||
常规负荷 | 200 | 1000 | ||||
柔性负荷 | 温控型负荷 | 160 | 800 | |||
可削减负荷 | 160 | 800 | ||||
电动汽车充电桩 | 75 | 750 | ||||
分布式储能装置 | 1 | 1200 |
Table 1 Load and energy storage access
接入类型 | 接入数量/个 | 总容量/kW | ||||
常规负荷 | 200 | 1000 | ||||
柔性负荷 | 温控型负荷 | 160 | 800 | |||
可削减负荷 | 160 | 800 | ||||
电动汽车充电桩 | 75 | 750 | ||||
分布式储能装置 | 1 | 1200 |
指标 | 本文方法 | k-means | ||
轮廓系数 | 0.963 | 0.782 | ||
紧密度/kW | 0.334 | 0.768 | ||
分割度/kW | 0.826 | 0.659 |
Table 2 Comparison of clustering indicators
指标 | 本文方法 | k-means | ||
轮廓系数 | 0.963 | 0.782 | ||
紧密度/kW | 0.334 | 0.768 | ||
分割度/kW | 0.826 | 0.659 |
算法 | 是否收敛 | 收敛时间/s | ||
分散式调控+ADMM | 否 | — | ||
集群后调控+ADMM | 是 | 253 | ||
集群后调控+改进ADMM | 是 | 14 |
Table 3 Comparison of convergence speed of three algorithms
算法 | 是否收敛 | 收敛时间/s | ||
分散式调控+ADMM | 否 | — | ||
集群后调控+ADMM | 是 | 253 | ||
集群后调控+改进ADMM | 是 | 14 |
类型 | 参与调控前日成本/元 | 参与调控后日成本/元 | ||
温控型负荷 | 379.96 | 345.14 | ||
可削减负荷 | 352.27 | 322.05 | ||
电动汽车充电桩 | 316.52 | 291.68 | ||
分布式储能 | 0 | –54.06 |
Table 4 Cost of various types of flexible loads and energy storage
类型 | 参与调控前日成本/元 | 参与调控后日成本/元 | ||
温控型负荷 | 379.96 | 345.14 | ||
可削减负荷 | 352.27 | 322.05 | ||
电动汽车充电桩 | 316.52 | 291.68 | ||
分布式储能 | 0 | –54.06 |
类型 | 高方案/元 | 中方案/元 | 低方案/元 | |||
温控型负荷 | 343.08 | 345.14 | 346.95 | |||
可削减负荷 | 319.27 | 322.05 | 323.86 | |||
电动汽车充电桩 | 290.42 | 291.68 | 293.50 | |||
分布式储能 | –60.43 | –54.06 | –49.71 |
Table 5 Cost of various types of flexible loads and energy storage under different time of use electricity prices
类型 | 高方案/元 | 中方案/元 | 低方案/元 | |||
温控型负荷 | 343.08 | 345.14 | 346.95 | |||
可削减负荷 | 319.27 | 322.05 | 323.86 | |||
电动汽车充电桩 | 290.42 | 291.68 | 293.50 | |||
分布式储能 | –60.43 | –54.06 | –49.71 |
1 | 宁剑, 江长明, 张哲, 等. 可调节负荷资源参与电网调控的思考与技术实践[J]. 电力系统自动化, 2020, 44 (17): 1- 8. |
NING Jian, JIANG Changming, ZHANG Zhe, et al. Thinking and technical practice of adjustable load resources participating in dispatching and control of power grid[J]. Automation of Electric Power Systems, 2020, 44 (17): 1- 8. | |
2 |
齐宁, 程林, 田立亭, 等. 考虑柔性负荷接入的配电网规划研究综述与展望[J]. 电力系统自动化, 2020, 44 (10): 193- 207.
DOI |
QI Ning, CHENG Lin, TIAN Liting, et al. Review and prospect of distribution network planning research considering access of flexible load[J]. Automation of Electric Power Systems, 2020, 44 (10): 193- 207.
DOI |
|
3 | 孙银锋, 夏大朋, 高梓淳. 基于蒙特卡罗模拟法的柔性交直流混联配电网概率潮流计算[J]. 东北电力大学学报, 2023, 43 (2): 82- 92. |
SUN Yinfeng, XIA Dapeng, GAO Zichun. Flexible AC/DC hybrid distribution network based on Monte Carlo simulation probabilistic load flow calculation[J]. Journal of Northeast Electric Power University, 2023, 43 (2): 82- 92. | |
4 |
OKUR Ö, VOULIS N, HEIJNEN P, et al. Aggregator-mediated demand response: minimizing imbalances caused by uncertainty of solar generation[J]. Applied Energy, 2019, 247, 426- 437.
DOI |
5 |
BRUNINX K, PANDŽIĆ H, LE CADRE H, et al. On the interaction between aggregators, electricity markets and residential demand response providers[J]. IEEE Transactions on Power Systems, 2020, 35 (2): 840- 853.
DOI |
6 | CHEN S J, CHEN Q X, XU Y. Strategic bidding and compensation mechanism for a load aggregator with direct thermostat control capabilities[J]. IEEE Transactions on Smart Grid, 2018, 9 (3): 2327- 2336. |
7 | 朱怡莹, 周荣生, 罗龙波. 考虑需求响应与光伏不确定性的电力系统经济调度[J]. 太阳能学报, 2023, 44 (1): 62- 68. |
ZHU Yiying, ZHOU Rongsheng, LUO Longbo. Economic dispatch of power system considering demand response and PV uncertainty[J]. Acta Energiae Solaris Sinica, 2023, 44 (1): 62- 68. | |
8 |
PENG C, ZOU J X, LIAN L, et al. An optimal dispatching strategy for V2G aggregator participating in supplementary frequency regulation considering EV driving demand and aggregator’s benefits[J]. Applied Energy, 2017, 190, 591- 599.
DOI |
9 | 李婧, 徐胜蓝, 万灿, 等. 基于自适应k-means++算法的电力负荷特性分析[J]. 南方电网技术, 2019, 13 (2): 13- 19. |
LI Jing, XU Shenglan, WAN Can, et al. Electricity load characteristics analysis based on adaptive k-means ++ algorithm[J]. Southern Power System Technology, 2019, 13 (2): 13- 19. | |
10 | 孙毅, 毛烨华, 李泽坤, 等. 面向电力大数据的用户负荷特性和可调节潜力综合聚类方法[J]. 中国电机工程学报, 2021, 41 (18): 6259- 6270. |
SUN Yi, MAO Yehua, LI Zekun, et al. Comprehensive clustering method of user load characteristics and adjustable potential for electric power big data[J]. Proceedings of the CSEE, 2021, 41 (18): 6259- 6270. | |
11 | 李晨希, 史佳琪, 刘念, 等. 基于复杂网络的电力用户群体演化分析模型[J]. 中国电机工程学报, 2022, 42 (16): 5835- 5847. |
LI Chenxi, SHI Jiaqi, LIU Nian, et al. Analysis model of power user group evolution based on complex network[J]. Proceedings of the CSEE, 2022, 42 (16): 5835- 5847. | |
12 | 刘春阳, 李康平, 纪陵, 等. 基于聚类-估计联动的需求响应集群基线负荷估计方法[J]. 电力系统自动化, 2023, 47 (2): 79- 87. |
LIU Chunyang, LI Kangping, JI Ling, et al. Clustering-estimation linkage based estimation method for aggregated baseline loads of demand response[J]. Automation of Electric Power Systems, 2023, 47 (2): 79- 87. | |
13 |
ALIZADEH M, SCAGLIONE A, APPLEBAUM A, et al. Reduced-order load models for large populations of flexible appliances[J]. IEEE Transactions on Power Systems, 2015, 30 (4): 1758- 1774.
DOI |
14 | 黄昌达, 赵鑫. 基于凝聚层次聚类的电力用户服务方法[J]. 电力需求侧管理, 2023, 25 (2): 112- 116. |
HUANG Changda, ZHAO Xin. Power user service method based on agglomerative hierarchical clustering[J]. Power Demand Side Management, 2023, 25 (2): 112- 116. | |
15 | 孙玉芹, 王松雷, 黄冬梅, 等. 考虑簇间重叠关系的负荷曲线多重聚类集成算法[J]. 电网技术, 2022, 46 (5): 1982- 1989. |
SUN Yuqin, WANG Songlei, HUANG Dongmei, et al. Multi-cluster integration algorithm of load curve considering overlapping relationship between clusters[J]. Power System Technology, 2022, 46 (5): 1982- 1989. | |
16 | 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- 4443. |
YAN Qiang, LI Yang, FAN Youjie, et al. Regression analysis of residents' electricity consumption behavior based on weighted voting integrated clustering[J]. Power System Technology, 2021, 45 (11): 4435- 4443. | |
17 | 张洁, 夏飞, 袁博, 等. 基于特征优选策略的居民用电行为聚类方法[J]. 电力系统自动化, 2022, 46 (6): 153- 159. |
ZHANG Jie, XIA Fei, YUAN Bo, et al. Clustering method for residential electricity consumption behavior based on feature optimization strategy[J]. Automation of Electric Power Systems, 2022, 46 (6): 153- 159. | |
18 |
李明轩, 齐步洋, 贺大玮. 工业园区需求响应资源聚合优化配置方法[J]. 电网技术, 2022, 46 (9): 3543- 3549.
DOI |
LI Mingxuan, QI Buyang, HE Dawei. Optimal allocation method of demand response resource aggregation in industrial park[J]. Power System Technology, 2022, 46 (9): 3543- 3549.
DOI |
|
19 |
PAPADASKALOPOULOS D, STRBAC G. Nonlinear and randomized pricing for distributed management of flexible loads[J]. IEEE Transactions on Smart Grid, 2016, 7 (2): 1137- 1146.
DOI |
20 |
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- 708.
DOI |
YANG Xiu, FU Guangnu, LIU Fang, et al. Study on evaluation and control strategy of air conditioning load aggregation response potential considering multiple factors[J]. Power System Technology, 2022, 46 (2): 699- 708.
DOI |
|
21 |
XU Z W, CALLAWAY D S, HU Z C, et al. Hierarchical coordination of heterogeneous flexible loads[J]. IEEE Transactions on Power Systems, 2016, 31 (6): 4206- 4216.
DOI |
22 |
赵冬梅, 宋原, 王云龙, 等. 考虑柔性负荷响应不确定性的多时间尺度协调调度模型[J]. 电力系统自动化, 2019, 43 (22): 21- 30.
DOI |
ZHAO Dongmei, SONG Yuan, WANG Yunlong, et al. Coordinated scheduling model with multiple time scales considering response uncertainty of flexible load[J]. Automation of Electric Power Systems, 2019, 43 (22): 21- 30.
DOI |
|
23 |
潘建辉, 张宁, 雍培, 等. 面向海量灵活性资源的两阶段分布式协同调度方法[J]. 电力系统自动化, 2023, 47 (15): 67- 79.
DOI |
PAN Jianhui, ZHANG Ning, YONG Pei, et al. Two-stage distributed collaborative dispatching method for massive flexible resources[J]. Automation of Electric Power Systems, 2023, 47 (15): 67- 79.
DOI |
|
24 | TULABING R S, MITCHELL B C, COVIC G A, et al. Localized demand control of flexible devices for peak load management[J]. IEEE Transactions on Smart Grid, 2022, 14 (1): 217- 227. |
25 | 刘向向, 张森林, 朱思乔, 等. 基于灰靶理论和谱聚类的虚拟电厂多形态柔性资源聚合模型[J]. 中国电力, 2023, 56 (11): 104- 112. |
LIU Xiangxiang, ZHANG Senlin, ZHU Siqiao, et al. Multi-form flexible resource aggregation model for virtual power plant based on grey target theory and spectral clustering[J]. Electric Power, 2023, 56 (11): 104- 112. |
[1] | REN Peng, ZHAO Zhigang, GAO Hongchao, WEN Wu, JIANG Yingyi. Weak Connection Regulation Technology for Source-Storage-Load Collaborative Microgrids Based on Direct Power Control [J]. Electric Power, 2025, 58(4): 13-20. |
[2] | Junfeng QIAO, Aihua ZHOU, Lin PENG, Yiqing WANG, Xiaofeng SHEN, Sen PAN, Pei YANG, Chenhong HUANG. An Evaluation Method for Distribution Network Operation Based on Multi-source Data Deep Fusion [J]. Electric Power, 2024, 57(6): 193-203. |
[3] | Yuefen GAO, Chengbo YUN, Fanpeng KONG, Xuesong WANG. Optimization of Integrated Energy System Coupled with Power-to-Gas and Carbon Capture and Storage Equipment under Demand Response Incentive [J]. Electric Power, 2024, 57(4): 32-41. |
[4] | LIN Yuhuan, HAO Fangzhou, LI Baixin, HUANG Bo. Method for Identifying Abnormal Data in Distribution Network Operation [J]. Electric Power, 2023, 56(9): 134-139. |
[5] | ZHU Pengcheng, LIU Zhaoyu, SUN Ke, XU Jie, HU Pengfei, JIANG Daozhuo. Optimal Scheduling of Honeycomb Distribution Network Based on BADMM [J]. Electric Power, 2023, 56(6): 90-100. |
[6] | ZHANG Li, LIU Qinglei, ZHANG Hongwei. Home Load Optimization Scheduling Strategy Based on Improved Binary Particle Swarm Optimization Algorithm [J]. Electric Power, 2023, 56(5): 118-128. |
[7] | ZHAO Jun, ZHANG Min, ZHANG Shifeng, YANG Qi. Optimization Strategy of Multi-microgrid Cooperative Operation Considering Carbon Trading and Renewable Energy Uncertainties [J]. Electric Power, 2023, 56(5): 62-71. |
[8] | Zhaojun JIANG, Yue XIANG, Zhukui TAN, Yongtao GUO, Yang WANG, Ke ZHOU. Optimal Allocation of Energy Storage Capacity in High Proportion Clean Energy Parks Considering Demand Response [J]. Electric Power, 2023, 56(12): 147-155, 163. |
[9] | ZHANG Yan, QIAO Songbo, XU Qifeng, YU Jing. Analysis of Distributed Green Power Transaction Optimization Based on Nash Bargaining Theory [J]. Electric Power, 2022, 55(12): 168-178. |
[10] | AI Xin, XU Limin, LIU Huichuan, WANG Xueying, LIU Hongyang, LI Yizheng. Demand Side Load Source Duality Modeling Method for Active Demand Response [J]. Electric Power, 2021, 54(6): 183-190. |
[11] | LING Chanhui, ZHENG Changbao, HU Cungang, RUI Tao. Real-Time Economic Optimization Method for Microgrid Considering Energy Storage Charge and Discharge Benefits [J]. Electric Power, 2019, 52(6): 111-120. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||