Hierarchical and Partitioned Optimal Control of Distribution Networks Considering the Coordination Between Energy Storage and Distributed Generation Systems

doi:10.11930/j.issn.1004-9649.202001081

Abstract

Abstract: The current distribution network is facing the challenge of large-scale distributed generation and diverse forms of energy storage being integrated into the distribution network, which has brought extreme complexity to the optimal management and control of distribution system. Inspired by the idea of layered optimization and partition coordination, a layered optimization system for distribution networks with regional autonomy and coordination among regions was proposed to achieve the purpose of system optimization after the integration of large-scale distributed generation into the bulk power grid. At the optimal dispatch layer, the dynamic mathematical model is established with the power exchange between each regions and the main power grid as the objective function. Then through the optimization coordinated by each regions, the large-scale distributed energy resources are connected to the grid smoothly and hourly schedules of the inter-region power exchange are obtained. At the control layer within the region, considering the discrepancies between the regulation capabilities of each distributed energy source, the dispatch order from upper layer is revised based on fuzzy control logic in combination with the energy storage system. Additionally the 5min ultra short term dispatch order is also issued for each region. At the unit control layer, real-time control is implemented based on PWM converter. Finally, the correctness and validity of the proposed strategy are verified by virtue of case studies with simulated calculations.

Key words: distribution system, distributed energy storage, distributed generation, hierarchical partitioning, optimized control

ZHANG Ying, KOU Lingfeng, JI Yu, YU Hui, HU Zhuandi, SUN Zhen’ao. Hierarchical and Partitioned Optimal Control of Distribution Networks Considering the Coordination Between Energy Storage and Distributed Generation Systems[J]. Electric Power, 2021, 54(2): 104-112.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202001081

https://www.electricpower.com.cn/EN/Y2021/V54/I2/104

References

[1] 孙丽敬, 盛万兴, 吴鸣, 等. 基于模糊C均值聚类的分布式电源集群并网逆变器输出功率置信区间估计方法[J]. 电网技术, 2019, 43(5): 1495-1503
SUN Lijing, SHENG Wanxing, WU Ming, et al. Estimation method of DG clusters grid-connected inverter’s output power confidence interval based on fuzzy C-means algorithm[J]. Power System Technology, 2019, 43(5): 1495-1503
[2] 张明霞, 闫涛, 来小康, 等. 电网新功能形态下储能技术的发展愿景和技术路径[J]. 电网技术, 2018, 42(5): 1370-1377
ZHANG Mingxia, YAN Tao, LAI Xiaokang, et al. Technology vision and route of energy storage under new power grid function configuration[J]. Power System Technology, 2018, 42(5): 1370-1377
[3] 王成山, 武震, 李鹏. 分布式电能存储技术的应用前景与挑战[J]. 电力系统自动化, 2014, 38(16): 1-8, 73
WANG Chengshan, WU Zhen, LI Peng. Prospects and challenges of distributed electricity storage technology[J]. Automation of Electric Power Systems, 2014, 38(16): 1-8, 73
[4] 叶季蕾, 薛金花, 王伟, 等. 储能技术在电力系统中的应用现状与前景[J]. 中国电力, 2014, 47(3): 1-5
YE Jilei, XUE Jinhua, WANG Wei, et al. Application of energy storage technology and its prospect in power system[J]. Electric Power, 2014, 47(3): 1-5
[5] 张江林, 庄慧敏, 刘俊勇, 等. 分布式储能系统参与调压的主动配电网两段式电压协调控制策略[J]. 电力自动化设备, 2019, 39(5): 15-21, 29
ZHANG Jianglin, ZHUANG Huimin, LIU Junyong, et al. Two-stage coordinated voltage control scheme of active distribution network with voltage support of distributed energy storage system[J]. Electric Power Automation Equipment, 2019, 39(5): 15-21, 29
[6] 吴鸣, 熊雄, 季宇, 等. 微网群技术综述[J]. 储能科学与技术, 2019, 8(4): 621-628
WU Ming, XIONG Xiong, JI Yu, et al. Overview on multi-microgrid technologies[J]. Energy Storage Science and Technology, 2019, 8(4): 621-628
[7] 王成山, 武震, 李鹏. 微电网关键技术研究[J]. 电工技术学报, 2014, 29(2): 1-12
WANG Chengshan, WU Zheng, LI Peng. Research on key technologies of microgrid[J]. Transactions of China Electrotechnical Society, 2014, 29(2): 1-12
[8] 肖传亮, 赵波, 周金辉, 等. 配电网中基于网络分区的高比例分布式光伏集群电压控制[J]. 电力系统自动化, 2017, 41(21): 147-155
XIAO Chuanliang, ZHAO Bo, ZHOU Jinhui, et al. Network partition based cluster voltage control of high-penetration distributed photovoltaic systems in distribution networks[J]. Automation of Electric Power Systems, 2017, 41(21): 147-155
[9] 陆凌芝, 耿光飞, 季玉琦, 等. 基于电气距离矩阵特征根分析的主动配电网电压控制分区方法[J]. 电力建设, 2018, 39(1): 83-89
LU Lingzhi, GENG Guangfei, JI Yuqi, et al. Voltage control partitioning method for active distribution network based on electrical distance matrix eigenvalue analysis[J]. Electric Power Construction, 2018, 39(1): 83-89
[10] 张孟琛, 牛益国, 宣文华. 含 DG配电网分层分区协同故障定位隔离技术[J]. 电力系统保护与控制, 2019, 47(23): 115-121
ZHANG Mengchen, NIU Yiguo, XUAN Wenhua. Hierarchical zoning collaborative fault location and isolation technology for distribution networks containing DG[J]. Power System Protection and Control, 2019, 47(23): 115-121
[11] 黄海. 新能源并网下微电网台区线损与无功多目标优化[J]. 电测与仪表, 2019, 45(3): 56-63
HUANG Hai. Multi-objective optimization of line loss and reactive power in microgrid area considering renewable energy integration[J]. Electrical Measurement and Instrumentation, 2019, 45(3): 56-63
[12] 滕云, 孙鹏, 罗桓桓, 等. 计及电热混合储能的多微源微网自治优化运行模型[J]. 中国电机工程学报, 2019, 39(18): 5316-5324, 5578
TENG Yun, SUN Peng, LUO Huanhuan, et al. Autonomous optimization operation model for multi-source microgrid considering electrothermal hybrid energy storage[J]. Proceedings of the CSEE, 2019, 39(18): 5316-5324, 5578
[13] 林顺富, 刘持涛, 李东东, 等. 考虑电能交互的冷热电区域多微网系统双层多场景协同优化配置[J]. 中国电机工程学报, 2019-12-13, 网络预印.
LIN Shunfu, LIU Chitao, LI Dongdong, et al. Bi-level multiple scenarios collaborative optimization configuration of CCHP regional multi-microgrid system considering power interaction among microgrids[J]. Proceedings of the CSEE, 2019-12-13.
[14] 吴攀, 黄文焘, 邰能灵, 等. 基于功率互济的柔性互联多微网孤岛运行多层协调控制策略[J]. 高电压技术, 2019, 45(10): 3101-3111
WU Pan, HUANG Wentao, TAI Nengling, et al. Multi-layer coordinated control strategy for islanded flexible interconnected multiple microgrids based on mutual power support[J]. High Voltage Engineering, 2019, 45(10): 3101-3111
[15] 张宏, 陈钊, 黄蓉, 等. 风电-光伏-光热联合发电系统地模糊多目标优化模型[J], 电源学报, 2019-06-14.
ZHANG Hong, CHEN Zhao, HUANG Rong, et al. Fuzzy multi-objective optimization about wind power-photovoltaic power concentrating solar power hybrid power generation system[J]. Journal of Power Supply, 2019-06-14.
[16] 晋宏杨, 孙宏斌, 郭庆来, 等. 含大规模储热的光热电站-风电联合系统多日自调度方法[J]. 电力系统自动化, 2016, 40(11): 17-23
JIN Hongyang, SUN Hongbin, GUO Qinglai, et al. Multi-day self-scheduling method for combined system of CSP plants and wind power with large-scale thermal energy storage contained[J]. Automation of Electric Power Systems, 2016, 40(11): 17-23
[17] 杨俊安, 庄镇泉. 量子遗传算法研究现状[J]. 计算机科学, 2003, 30(11): 13-15
YANG Junan, ZHUANG Zhenquan. Actuality of research on quantum genetic algorithm[J]. Computer Science, 2003, 30(11): 13-15
[18] 修晓青, 唐巍, 李建林, 等. 基于层次分析法的储能配置综合评估技术[J]. 电力系统自动化, 2018, 42(11): 72-78
XIU Xiaoqing, TANG Wei, LI Jianlin, et al. Comprehensive evaluation technology of energy storage configuration based on analytic hierarchy process[J]. Automation of Electric Power Systems, 2018, 42(11): 72-78
[19] 孙振新, 刘汉强, 赵喆, 等. 储能经济性研究[J]. 中国电机工程学报, 2013, 33(增刊1): 54-58
SUN Zhenxin, LIU Hanqiang, ZHAO Zhe, et al. Research on economical efficiency of energy storage[J]. Proceedings of the CSEE, 2013, 33(S1): 54-58
[20] 严干贵, 刘嘉, 崔杨, 等. 利用储能提高风电调度入网规模的经济性评价[J]. 中国电机工程学报, 2013, 33(22): 45-52, 9
YAN Gangui, LIU Jia, CUI Yang, et al. Economic evaluation on improving wind power scheduling scale by using energy storage systems[J]. Proceedings of the CSEE, 2013, 33(22): 45-52, 9