Effective Development and Management Strategy for Distributed Smart Grids Based on Collective Intelligence

doi:10.11930/j.issn.1004-9649.202312024

Abstract

Abstract:

To overcome the challenge of accurately investing in the construction strategies of distributed smart grids under different resource endowments, an efficient development and management strategy for distributed smart grids based on collective intelligence was proposed. Firstly, relying on development planning data of massive distributed smart grids, the optimal index set for the development of distributed smart grids was constructed from three aspects of operation, planning, and development by using Ward agglomerative hierarchical clustering. Secondly, the corresponding probability distribution function was fitted according to the type of each index, and the index threshold interval was determined to achieve the objective scoring of each index. Then, the precise investment evaluation system for the development of distributed smart grids based on collective intelligence was constructed, and the horizontal and vertical difference degree of indexes was used to drive the re-weighting of collective intelligence, so as to achieve the rational evaluation of distributed smart grid construction strategy. Finally, the closed-loop feedback was formed by calculating the input-to-output ratio of the development planning, and efficient development and management of distributed smart grids was achieved. The rationality of the proposed system was verified by analyzing the development planning data of 10 000 groups in a province.

Key words: collective intelligence, distributed smart grids, development and management strategy, data drive, evaluation system

Zongchao YU, Ming WEN, Xianghua LI, Xintao XIE, Hongming YANG. Effective Development and Management Strategy for Distributed Smart Grids Based on Collective Intelligence[J]. Electric Power, 2024, 57(10): 57-68.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202312024

https://www.electricpower.com.cn/EN/Y2024/V57/I10/57

Figures/Tables 11

References 25

1	新华社. 习近平主持召开中央财经委员会第十一次会议[EB/OL]. (2022-04-26) [2023-11-20]. https://www.gov.cn/xinwen/2022-04/26/content_5687372.htm.
2	南方电网技术情报中心. 专题研究-分布式智能电网基本内涵与主要物理形态[EB/OL]. (2022-08-12) [2023-11-20]. https://mp.weixin.qq.com/s/gIbAvjDrBWy NVVZW0LaqBA.
3	王成山, 王瑞, 于浩, 等. 配网形态演变下的协调规划问题与挑战[J]. 中国电机工程学报, 2020, 40 (8): 2385- 2396.
	WANG Chengshan, WANG Rui, YU Hao, et al. Challenges on coordinated planning of smart distribution networks driven by source-network-load evolution[J]. Proceedings of CSEE., 2020, 40 (8): 2385- 2396.
4	黄志鹏, 李黄强, 舒征宇, 等. 基于配电自动化故障管理的配电网扩展规划方法[J]. 智慧电力, 2022, 50 (4): 66- 72.
	HUANG Zhipeng, LI Huangqiang, SHU Zhengyu, et al. Expansion planning method of distribution system based on distribution automation fault Management[J]. Smart Power, 2022, 50 (4): 66- 72.
5	姜拓, 方必武, 陈亦平, 等. 基于多参数规划的主配网协同优化运行方法[J]. 南方电网技术, 2023, 17 (9): 10- 19.
	JIANG Tuo, FANG Biwu, CHEN Yiping, et al. Coordinative optimal operation method of transmission and distribution networks based on multi-parametric programming[J]. Southern Power System Technology, 2023, 17 (9): 10- 19.
6	程宝玉. 电力大数据在配网规划中的应用研究[D]. 北京: 华北电力大学, 2017.
	CHENG Baoyu. Application of electricity large data on distribution network planning [D]. Beijing: North China Electric Power University, 2017.
7	黄国楠. 配网规划分析与辅助决策支持系统的研究[D]. 北京: 华北电力大学, 2015.
	HUANG Guonan. Research on analysis and assistant decision support system for distribution network planning [D]. Beijing: North China Electric Power University, 2015.
8	LI Fangxing, BROADWATER R P. Software framework concepts for power distribution system analysis[J]. IEEE Transactions on Power Systems, 2004, 19, 948- 956. DOI
9	高崇, 赵懿祺, 唐俊熙, 等. 以解决现状电网问题为导向的配网自动规划方法研究[J]. 电力系统保护与控制, 2018, 46 (15): 85- 92.
	GAO Chong, ZHAO Yiqi, TANG Junxi, et al. Research on an innovative problem-oriented automatic distribution net-work planning method[J]. Power System Protection and Control, 2018, 46 (15): 85- 92.
10	张稳, 盛万兴, 杜松怀, 等. 基于海量数据的配网运行分析系统架构与技术实现[J]. 电力系统自动化, 2020, 44 (3): 147- 155.
	ZHANG Wen, SHENG Wanxing, DU Songhuai, et al. Architecture and technology implementation of massive data based distribution network operation analysis system[J]. Automation of Electric Power system, 2020, 44 (3): 147- 155.
11	王文彬, 伍小生, 朱傲, 等. 基于层次分析法的配网“低电压”智能规划与综合治理评估技术研究及应用[J]. 电工技术学报, 2018, 33 (S2): 596- 607.
	WANG Wenbin, WU Xiaosheng, ZHU Ao, et al. Research and application of low-voltage intelligent planning and comprehensive treatment evaluation technology for distribution network based on analytic hierarchy process[J]. Transactions of China Electrotechnical Society, 2018, 33 (S2): 596- 607.
12	荆朝霞, 曾丽. 基于改进层次分析法的配网中压改造项目迫切度分析[J]. 电力系统自动化, 2011, 35 (4): 92- 95, 99.
	JING Zhaoxia, ZENG Li. Analysis on urgency degrees of distribution network reconstruction scheme based on advanced AHP[J]. Automation of Electric Power system, 2011, 35 (4): 92- 95, 99.
13	尹晓敏, 王华莹, 丁吉, 等. 基于最大离差与系数熵的配网规划评估方法[J]. 电力工程技术, 2019, 38 (3): 51- 59.
	YIN Xiaomin, WANG Huaying, DING Ji, et al. Evaluation method of distribution grid planning based on maximum deviation and coefficient entropy[J]. Electric Power Engineering Technology, 2019, 38 (3): 51- 59.
14	李滨, 刘铸峰, 黄柳军, 等. 县级电网线损管理综合对标评价[J]. 电网技术, 2016, 40 (12): 3871- 3880.
	LI Bin, LIU Zhufeng, HUANG Liujun, et al. Comprehensive evaluation benchmark study on line loss management of county power grids[J]. Power System Technology, 2016, 40 (12): 3871- 3880.
15	李滨, 严康, 罗发, 等. 最优标杆在市级电网企业线损精益管理中的综合应用[J]. 电力系统自动化, 2018, 42 (23): 184- 192.
	LI Bin, YAN Kang, LUO Fa, et al. Comprehensive application of optimal benchmarking in line loss lean management of city-level power grid enterprises[J]. Automation of Electric Power system, 2018, 42 (23): 184- 192.
16	付学谦, 陈皓勇. 基于加权秩和比法的电能质量综合评估[J]. 电力自动化设备, 2015, 35 (1): 128- 132.
	FU Xueqian, CHENG Haoyong. Comprehensive power quality evaluation based on weighted rank sum ration method[J]. Electric Power Automation Equipment, 2015, 35 (1): 128- 132.
17	孙惠娟, 刘君, 彭春华. 基于分类概率综合多场景分析的分布式电源多目标规划[J]. 电力自动化设备, 2018, 38 (12): 39- 45.
	SUN Huijuan, LIU Jun, PENG Chunhua. Multi-objective DG planning based on classified probability integration multi-scenario analysis[J]. Electric Power Automation Equipment, 2018, 38 (12): 39- 45.
18	DAI Anna, ZHAO Zhifeng, LI Rongpeng, et al. Evaluation mechanism of collective intelligence for heterogeneous agents group[J]. IEEE Access, 2020, 8, 28385- 28394. DOI
19	刘映尚, 陶文伟, 周凯等. 基于变权物元可拓模型的二次设备状态综合评价[J]. 电力系统保护与控制, 2017, 45 (8): 80- 85.
	LIU Yingshang, TAO Wenwei, ZHOU Kai, et al. Comprehensive evaluation on secondary equipment condition based on matter-element extension model with variable weight[J]. Power System Protection and Control, 2017, 45 (8): 80- 85.
20	潘艳, 张祥成, 张文朝, 等. 通道型电磁环网解环量化评估方法分析[J]. 电力系统自动化, 2017, 41 (20): 157- 162.
	PAN Yan, ZHANG Xiangcheng, ZHANG Wenchao, et al. Analysis on quantitative evaluation methods of open-loop for channel-type electromagnetic loop network[J]. Automation of Electric Power system, 2017, 41 (20): 157- 162.
21	宋人杰, 刘瑞英, 刘耀伟, 等. 基于层次灰关联分析的变压器状态评估关键指标体系构建及应用[J]. 高电压技术, 2018, 44 (8): 2509- 2515.
	SONG Renjie, LIU Ruiying. LIU Yaowei, et al. Key indicator system establishment and application for transformer condition assessment based on hierarchy grey relation analysis[J]. High Voltage Engineering, 2018, 44 (8): 2509- 2515.
22	张稳, 盛万兴, 刘科研, 等. 高渗透率分布式电源按节点关键性接入配电网的运行风险评估[J]. 高电压技术, 2021, 47 (3): 937- 947.
	ZHANG Wen, SHENG Wanxing, LIU Keyan, et al. Operation risk assessment of high penetration distributed generation connected to distribution network according to node criticality[J]. High Voltage Engineering, 2021, 47 (3): 937- 947.
23	徐斌, 马骏, 陈青等. 基于改进AHP-TOPSIS法的经济开发区配电网综合评价指标体系和投资策略研究[J]. 电力系统保护与控制, 2019, 47 (22): 35- 44.
	XU Bin, MA Jun, CHEN Qing, et al. Research on comprehensive evaluation index system and investment strategy of economic development zone distribution network based on improved AHP-TOPSIS method[J]. Power System Protection and Control, 2019, 47 (22): 35- 44.
24	苏浩益, 李如琦. 智能电网条件下的多目标输电网规划[J]. 中国电机工程学报, 2012, 32 (34): 30- 35, 6.
	SU Haoyi, LI Ruqi. A novel method for multi-objective transmission network planning under smart grid condition[J]. Proceedings of the CSEE, 2012, 32 (34): 30- 35, 6.
25	程砚秋, 徐占东. 基于泰尔指数修正的ELECTRE III小企业信用评价模型[J]. 中国管理科学, 2019, 27 (10): 22- 33.
	CHENG Yanqiu, XU Zhandong. Credit risk evaluation of small enterprises based on revised ELECTRE III by theil index[J]. Chinese Journal of Management Science, 2019, 27 (10): 22- 33.

维度	台区指标	线路指标
运行层	配变出口低电压频次（YX1）	主线路跳闸频次(YX1)
	配变过载频次（YX2）	分支线路跳闸频次(YX2)
	配变重载频次（YX3）	线路过载频次(YX3)
	配变停电投诉频次（YX4）	线路重载频次(YX4)
	低电压投诉频次（YX5）	停电投诉频次(YX5)
	配变缺陷隐患程度（YX6）	线路缺陷隐患程度(YX6)
		故障自愈成功率(YX7)
		线路线损率(YX8)
规划层	配变供电半径（WJ1）	线路供电半径(WJ1)
	配变高损耗率（WJ2）	线路联络情况(WJ2)
	台区两相供电（WJ3）	线路分段化(WJ3)
	台区线损率（WJ4）	线路绝缘化率(WJ4)
		线路电缆光纤覆盖率(WJ5)
发展层	配变运行年限（FZ1）	线路运行年限(FZ1)
	配变可开放容量（FZ2）	线路自动化覆盖率(FZ2)
	配变户均容量（FZ3）	线路可开放容量(FZ3)
	负荷发展需求率（FZ4）	负荷发展需求(FZ4)
		分布式资源渗透率(FZ5)

维度	台区指标	线路指标
运行层	配变出口低电压频次（YX1）	主线路跳闸频次(YX1)
	配变过载频次（YX2）	分支线路跳闸频次(YX2)
	配变重载频次（YX3）	线路过载频次(YX3)
	配变停电投诉频次（YX4）	线路重载频次(YX4)
	低电压投诉频次（YX5）	停电投诉频次(YX5)
	配变缺陷隐患程度（YX6）	线路缺陷隐患程度(YX6)
		故障自愈成功率(YX7)
		线路线损率(YX8)
规划层	配变供电半径（WJ1）	线路供电半径(WJ1)
	配变高损耗率（WJ2）	线路联络情况(WJ2)
	台区两相供电（WJ3）	线路分段化(WJ3)
	台区线损率（WJ4）	线路绝缘化率(WJ4)
		线路电缆光纤覆盖率(WJ5)
发展层	配变运行年限（FZ1）	线路运行年限(FZ1)
	配变可开放容量（FZ2）	线路自动化覆盖率(FZ2)
	配变户均容量（FZ3）	线路可开放容量(FZ3)
	负荷发展需求率（FZ4）	负荷发展需求(FZ4)
		分布式资源渗透率(FZ5)

线路类指标				台区类指标
编号	$ {N^ - } $	$ {N^ + } $	函数	编号	$ {N^ - } $	$ {N^ + } $	函数
YX1	0	3	③	YX1	1	5	③
YX2	1	9	③	YX2	0	5	③
YX3	0	3	②	YX3	1	9	②
YX4	0	5	①	YX4	0	5	①
YX5	0	4	①	YX5	0	3	①
YX6	10	90	②	YX6	10	90	②
WJ1	3 km	15 km	③	WJ1	100 m	1400 m	③
WJ2	0	1	①	WJ2	0	1	①
WJ3	1	3	②	WJ3	0	1	①
WJ4	10	90	①	WJ4	10	90	②
FZ1	10	35	③	FZ1	10	35	③
FZ2	0	1	①	FZ2	0	1	①
FZ3	0	1	①	FZ3	0.6	1.8	③
FZ4	0	1	①	FZ4	0	1	①

线路类指标				台区类指标
编号	$ {N^ - } $	$ {N^ + } $	函数	编号	$ {N^ - } $	$ {N^ + } $	函数
YX1	0	3	③	YX1	1	5	③
YX2	1	9	③	YX2	0	5	③
YX3	0	3	②	YX3	1	9	②
YX4	0	5	①	YX4	0	5	①
YX5	0	4	①	YX5	0	3	①
YX6	10	90	②	YX6	10	90	②
WJ1	3 km	15 km	③	WJ1	100 m	1400 m	③
WJ2	0	1	①	WJ2	0	1	①
WJ3	1	3	②	WJ3	0	1	①
WJ4	10	90	①	WJ4	10	90	②
FZ1	10	35	③	FZ1	10	35	③
FZ2	0	1	①	FZ2	0	1	①
FZ3	0	1	①	FZ3	0.6	1.8	③
FZ4	0	1	①	FZ4	0	1	①

编号	初始分数	增加分数	最终分数	投入经费/万元	产出比
#1	46.7	20.9	67.6	5.90	47.46
#2	56.1	16.9	73.0	5.67	41.48
#3	58.8	24.9	83.7	6.34	69.67
#4	45.6	18.7	64.3	8.56	40.49
#5	59.9	23.7	83.6	10.98	66.22