OPTIMAL DISPATCH OF CONTROLLABLE RESOURCES IN DISTRIBUTION NETWORK SUPPORTED BY CLOUD LOAD LIBRARY

Bao Yu; Xia Xiangwu; Gao Jiuguo; Lu Yang; Wang Mengyao

doi:10.19912/j.0254-0096.tynxb.2023-1545

PDF(2079 KB)

Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (1) : 557-566. DOI: 10.19912/j.0254-0096.tynxb.2023-1545

OPTIMAL DISPATCH OF CONTROLLABLE RESOURCES IN DISTRIBUTION NETWORK SUPPORTED BY CLOUD LOAD LIBRARY

Bao Yu¹, Xia Xiangwu¹, Gao Jiuguo², Lu Yang², Wang Mengyao¹

Author information +

History +

Abstract

A controllable resource optimization dispatching framework for low-voltage distribution network supported by cloud load library is proposed. First,use a data-driven method to mine the causal relationship between transformer load,user load and optimal dispatch model parameters,and build a cloud load library with parameter identification function; secondly,identify the optimal dispatch model parameters of the target distribution network with the support of the load library,establish an optimal scheduling model. Then,the model is solved to obtain the operating alignment of the controllable resource cluster in the target distribution network,and is sent to the edge management and control unit to regulate the operation of the equipment. Finally,tests are conducted in an actual low-voltage distribution network to prove the effectiveness and practicability of the proposed framework.

Key words

scheduling algorithms / optimization / data analytics / low-voltage distribution network / cloud-edge collaboration

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Bao Yu, Xia Xiangwu, Gao Jiuguo, Lu Yang, Wang Mengyao. OPTIMAL DISPATCH OF CONTROLLABLE RESOURCES IN DISTRIBUTION NETWORK SUPPORTED BY CLOUD LOAD LIBRARY[J]. Acta Energiae Solaris Sinica. 2025, 46(1): 557-566 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1545

References

[1] 王秀丽, 闫璐, 刘豹, 等. 基于合作-非合作博弈的光储荷网协同运行策略[J]. 太阳能学报, 2023, 44(5): 128-138.
WANG X L, YAN L, LIU B, et al.Cooperative operational strategies of photovoltaic, energy storage, load and power grid based on cooperative and non-cooperative game[J]. Acta energiae solaris sinica, 2023, 44(5): 128-138.
[2] 帅挽澜, 朱自伟, 李雪萌, 等. 考虑风电消纳的综合能源系统“源-网-荷-储” 协同优化运行[J]. 电力系统保护与控制, 2021, 49(19): 18-26.
SHUAI W L, ZHU Z W, LI X M, et al.“Source-network-load-storage” coordinated optimization operation for an integrated energy system considering wind power consumption[J]. Power system protection and control, 2021, 49(19): 18-26.
[3] 刘豫亳, 谢丽蓉, 彭维, 等. 计及弃风消纳的储电-蓄热协同优化控制研究[J]. 太阳能学报, 2023, 44(4): 276-282.
LIU Y B, XIE L R, PENG W, et al.Research on cooperative optimal control of electricity storage and heat storage considering abandoned wind consumption[J]. Acta energiae solaris sinica, 2023, 44(4): 276-282.
[4] XU B, ZHANG G Y, LI K, et al.Reactive power optimization of a distribution network with high-penetration of wind and solar renewable energy and electric vehicles[J]. Protection and control of modern power systems, 2022, 7(4): 1-13.
[5] 张思, 杨晓雷, 阙凌燕, 等. 高比例光伏发电对浙江电网电力平衡的影响及应对策略[J]. 浙江电力, 2022, 41(11): 9-16.
ZHANG S, YANG X L, QUE L Y, et al.The impact of high-proportion photovoltaic power generation on the power balance of Zhejiang power grid and its countermeasures[J]. Zhejiang electric power, 2022, 41(11): 9-16.
[6] 张勇军, 羿应棋, 李立浧, 等. 双碳目标驱动的新型低压配电系统技术展望[J]. 电力系统自动化, 2022, 46(22): 1-12.
ZHANG Y J, YI Y Q, LI L C, et al.Prospect of new low-voltage distribution system technology driven by carbon emission peak and carbon neutrality targets[J]. Automation of electric power systems, 2022, 46(22): 1-12.
[7] 舒印彪, 张智刚, 郭剑波, 等. 新能源消纳关键因素分析及解决措施研究[J]. 中国电机工程学报, 2017, 37(1): 1-9.
SHU Y B, ZHANG Z G, GUO J B, et al.Study on key factors and solution of renewable energy accommodation[J]. Proceedings of the CSEE, 2017, 37(1): 1-9.
[8] 杨京渝, 罗隆福, 阳同光, 等. 计及谷时段风电消纳的储能系统平抑风电功率波动控制策略[J]. 电力系统保护与控制, 2023, 51(10): 131-141.
YANG J Y, LUO L F, YANG T G, et al.Smoothing wind power fluctuation control strategy for an energy storage system considering wind power consumption in the valley period[J]. Power system protection and control, 2023, 51(10): 131-141.
[9] 吴润基, 王冬骁, 谢昌鸿, 等. 空调负荷参与配电网电压管理的分布式控制方法[J]. 电力系统自动化, 2021, 45(6): 215-222.
WU R J, WANG D X, XIE C H, et al.Distributed control method for air-conditioning load participating in voltage management of distribution network[J]. Automation of electric power systems, 2021, 45(6): 215-222.
[10] 车伟, 陈洁, 胡亚杰, 等. 光伏快速充电站配电变压器端电能质量综合控制研究[J]. 电力系统保护与控制, 2022, 50(21): 128-137.
CHE W, CHEN J, HU Y J, et al.Comprehensive control of power quality at the distribution transformer end of a photovoltaic fast charging station[J]. Power system protection and control, 2022, 50(21): 128-137.
[11] 王力成, 杨宇, 杨晓东, 等. 考虑非完美通讯的高光伏渗透率配电网实时电压协同控制[J]. 中国电机工程学报, 2022, 42(11): 4027-4040.
WANG L C, YANG Y, YANG X D, et al.Real-time voltage cooperative control in distribution networks with high photovoltaic penetration considering imperfect communication[J]. Proceedings of the CSEE, 2022, 42(11): 4027-4040.
[12] 王鹏, 林佳颖, 宁昕, 等. 配电网全景信息感知架构设计[J]. 高电压技术, 2021, 47(7): 2293-2302.
WANG P, LIN J Y, NING X, et al.Architecture of power distribution network measurement system[J]. High voltage engineering, 2021, 47(7): 2293-2302.
[13] 李翔宇, 赵冬梅. 分散架构下多虚拟电厂分布式协同优化调度[J]. 电工技术学报, 2023, 38(7): 1852-1863.
LI X Y, ZHAO D M.Distributed coordinated optimal scheduling of multiple virtual power plants based on decentralized control structure[J]. Transactions of China Electrotechnical Society, 2023, 38(7): 1852-1863.
[14] 杨秀, 李安, 孙改平, 等. 基于改进GMM-CNN-GRU混合的非侵入式负荷监测方法研究[J]. 电力系统保护与控制, 2022, 50(14): 65-75.
YANG X, LI A, SUN G P, et al.Non-invasive load monitoring based on an improved GMM-CNN-GRU combination[J]. Power system protection and control, 2022, 50(14): 65-75.
[15] 潘旭, 王金丽, 赵晓龙, 等. 智能配电网多维数据质量评价方法[J]. 中国电机工程学报, 2018, 38(5): 1375-1384.
PAN X, WANG J L, ZHAO X L, et al.Multi dimensional data quality evaluation method for intelligent distribution network[J]. Proceedings of the CSEE, 2018, 38(5): 1375-1384.
[16] 李想, 王鹏, 刘洋, 等. 考虑类别不平衡的海量负荷用电模式辨识方法[J]. 中国电机工程学报, 2020, 40(1): 128-137.
LI X, WANG P, LIU Y, et al.Massive load pattern identification method considering class imbalance[J]. Proceedings of the CSEE, 2020, 40(1): 128-137.
[17] ZHAO J L, ZHANG Z Q, YU H, et al.Cloud-edge collaboration-based local voltage control for DGs with privacy preservation[J]. IEEE transactions on industrial informatics, 2023, 19(1): 98-108.
[18] 刘家瑞, 杨国田, 杨锡运. 基于深度卷积自编码器的风电机组故障预警方法研究[J]. 太阳能学报, 2022, 43(11): 215-223.
LIU J R, YANG G T, YANG X Y.Research on wind turbine fault warning method based on deep convolution auto-encoder[J]. Acta energiae solaris sinica, 2022, 43(11): 215-223.
[19] VICHI M, CAVICCHIA C, GROENEN P J F. Hierarchical means clustering[J]. Journal of classification, 2022, 39(3): 553-577.
[20] 刘健, 赵磐, 张志华, 等. 放弃全局最优去寻找满意解: 精英优化法[J]. 供用电, 2022, 39(6): 2-5, 1.
LIU J, ZHAO P, ZHANG Z H, et al.An elitist searching approach to find the satisfied solutions[J]. Distribution & utilization, 2022, 39(6): 2-5, 1.
[21] 谭海旺, 杨启亮, 邢建春, 等. 基于XGBoost-LSTM组合模型的光伏发电功率预测[J]. 太阳能学报, 2022, 43(8): 75-81.
TAN H W, YANG Q L, XING J C, et al.Photovoltaic power prediction based on combined XGBoost-LSTM model[J]. Acta energiae solaris sinica, 2022, 43(8): 75-81.
[22] LIN S F, LI F X, TIAN E W, et al.Clustering load profiles for demand response applications[J]. IEEE transactions on smart grid, 2019, 10(2): 1599-1607.
[23] 杨珺, 侯俊浩, 刘亚威, 等. 分布式协同控制方法及在电力系统中的应用综述[J]. 电工技术学报, 2021, 36(19): 4035-4049.
YANG J, HOU J H, LIU Y W, et al.Distributed cooperative control method and application in power system[J]. Transactions of China Electrotechnical Society, 2021, 36(19): 4035-4049.
[24] 郭亦宗, 冯斌, 岳铂雄, 等. 负荷聚合商模式下考虑需求响应的超短期负荷预测[J]. 电力系统自动化, 2021, 45(1): 79-87.
GUO Y Z, FENG B, YUE B X, et al.Ultra-short-term load forecasting considering demand response in load aggregator mode[J]. Automation of electric power systems, 2021, 45(1): 79-87.