基于小信号稳定性的直流微电网多控制器参数全局优化方法

doi:10.12204/j.issn.1000-7229.2023.06.012

摘要/Abstract

摘要：

直流微电网中存在多个控制器,而不同控制器参数的组合对系统的整体稳定性影响也存在差异。为提升系统稳定性,提出了一种基于小信号稳定性的直流微电网多控制器参数全局优化方法。首先,推导了系统的小信号模型,对系统进行特征值分析和参与因子分析,确定了PI参数、下垂系数、虚拟惯性系数等关键控制参数的稳定域;其次,建立了包含系统主导极点实部、阻尼比和储能最大输出功率的目标函数,并采用正交实验法获得样本数据,利用综合赋权法对多目标进行赋权;然后,采用结合灰狼优化的改进粒子群算法对系统的关键参数进行优化,结果表明参数优化后的系统特征值更加远离虚轴,阻尼比增大,储能最大输出功率增加,系统稳定性得到了提升;最后,通过仿真验证了所提方法的有效性和优越性。

关键词: 直流微电网, 控制器参数优化, 综合赋权法, 改进粒子群算法, 稳定性分析

Abstract:

DC microgrid systems have multiple controllers, and the combination of different controller parameters has different effects on the stability of the entire system. To improve system stability, a multi-controller parameter global optimization method based on small-signal stability is proposed. First, the small-signal model of the system is deduced, and eigenvalue and participation factor analyses of the system are performed to determine the stability domain of key control parameters such as PI parameters, droop coefficients, and virtual inertia coefficients. The objective function, including the maximum real part of the eigenvalue, damping ratio, and maximum output power of the energy storage, is established. The sample data are obtained by using an orthogonal experiment, and the multi-objective is weighted by using a comprehensive weighting method. The key parameters of the system are then optimized using improved particle swarm optimization based on the grey wolf algorithm, thereby yielding the optimization results. The results show that the eigenvalues of the system after parameter optimization are farther away from the imaginary axis, the damping ratio increases, and the maximum output power of the energy storage increases, which improves system stability. Finally, the effectiveness and superiority of the proposed method are verified by building a model on the MATLAB Simulink simulation platform.

Key words: DC microgrid, optimization of controller parameters, comprehensive weighting method, improved particle swarm algorithm, stability analysis

中图分类号:

TM73

朱晓荣, 冯天娇. 基于小信号稳定性的直流微电网多控制器参数全局优化方法[J]. 电力建设, 2023, 44(6): 112-125.

ZHU Xiaorong, FENG Tianjiao. Global Optimization Method for Multi-controller Parameters of DC Microgrids Based on Small-Signal Stability[J]. ELECTRIC POWER CONSTRUCTION, 2023, 44(6): 112-125.

图/表 32

图1 直流微电网系统结构

Fig.1 Structure of DC microgrid

图2 简化的直流微电网模型结构

Fig.2 Structure of simplified DC microgrid model

图3 虚拟惯性控制结构框图

Fig.3 Structure diagram of virtual inertia control block

图4 恒功率负荷控制策略

Fig.4 Control strategy of constant power load

图5 直流线路结构

Fig.5 Structure of DC transmission line

图6 系统的特征值

Fig.6 Characteristic root of system

图7 储能比例积分系数的稳定域

Fig.7 Stability region of proportional integral coefficients of energy storage unit

图8 虚拟惯性系数的稳定域

Fig.8 Stability region of virtual inertial coefficients of energy storage unit

图9 储能下垂系数的稳定域

Fig.9 Stability region for droop coefficients of energy storage unit

图10 输出最大功率时下垂系数的稳定域

Fig.10 Stability region of droop coefficients at maximum output power

图11 恒功率负荷比例积分的稳定域

Fig.11 Stability region of proportional integral coefficients of constant power load

表1 控制器参数取值范围

Table 1 The value range of the controller parameters

表2 指标对比程度含义

Table 2 Indicator comparison degree meaning

表3 判断矩阵

Table 3 Judgment matrix

表4 AHP法权重系数

Table 4 Weight of each index obtained by AHP

表5 CRITIC法权重系数

Table 5 Weight of each index obtained by CRITIC

表6 AHP-CRITIC法权重系数

Table 6 Weights of each index obtained by AHP-CRITIC

图12 不同粒子群算法的优化结果

Fig.12 Optimization results of different particle swarm algorithm

表7 控制器参数优化结果

Table 7 Optimization results of controller parameters

表8 优化前后系统性能指标对比

Table 8 Comparison of system performance indicators

表9 采用传统目标函数的控制器参数优化结果

Table 9 Optimization results of controller parameters for traditional objective functions

表10 采用传统目标函数优化后的系统性能指标

Table 10 System performance indicators for traditional objective functions

图13 不同目标函数的参数优化仿真结果

Fig.13 Parameter optimization simulation results for different objective functions

表11 不同赋权方法的控制器参数优化结果

Table 11 Optimization results of controller parameters for different weighting methods

表12 不同赋权方法优化后系统性能指标对比

Table 12 System performance indicators for different weighting methods

图14 不同赋权方法的参数优化仿真结果

Fig.14 Simulation results of parameter optimization with different weighting methods

表A1 直流微电网系统参数

Table A1 DC microgrid system parameters

表A2 特征值分析结果

Table A2 Eigenvalue analysis results

图A1 参与因子分析结果

Fig.A1 System participation factor analysis

表A3 正交试验因素水平取值

Table A3 The value of the factor level of the orthogonal test

图A2 控制器参数优化流程

Fig.A2 Flow chart of controller parameter optimization

表A4 正交试验结果

Table A4 Orthogonal experiment results

参考文献 31

[1]	李霞林, 郭力, 王成山, 等. 直流微电网关键技术研究综述[J]. 中国电机工程学报, 2016, 36(1): 2-17.
	LI Xialin, GUO Li, WANG Chengshan, et al. Key technologies of DC microgrids: an overview[J]. Proceedings of the CSEE, 2016, 36(1): 2-17.
[2]	王子鹏, 郑丽君, 吕世轩. 考虑多储能系统功率分配的独立直流微电网协调控制策略[J]. 电力建设, 2021, 42(4): 89-96. doi: 10.12204/j.issn.1000-7229.2021.04.010
	WANG Zipeng, ZHENG Lijun, LÜ Shixuan. Coordinated control for islanded DC microgrid considering power sharing of multiple energy storages[J]. Electric Power Construction, 2021, 42(4): 89-96. doi: 10.12204/j.issn.1000-7229.2021.04.010
[3]	朱晓荣, 候顺达, 李铮. 基于模型预测控制的直流微电网电压动态响应优化[J]. 电网技术, 2020, 44(6): 2187-2195.
	ZHU Xiaorong, HOU Shunda, LI Zheng. Voltage dynamic response optimization of DC microgrid based on model predictive control[J]. Power System Technology, 2020, 44(6): 2187-2195.
[4]	陈景文, 周媛, 李晓飞, 等. 光储直流微网混合储能控制策略研究[J]. 智慧电力, 2022, 50(1): 14-20, 87.
	CHEN Jingwen, ZHOU Yuan, LI Xiaofei, et al. Hybrid energy storage control strategy of optical storage DC microgrid[J]. Smart Power, 2022, 50(1): 14-20, 87.
[5]	季宇, 王东旭, 吴红斌, 等. 提高直流微电网稳定性的有源阻尼方法[J]. 电工技术学报, 2018, 33(2): 370-379.
	JI Yu, WANG Dongxu, WU Hongbin, et al. The active damping method for improving the stability of DC microgrid[J]. Transactions of China Electrotechnical Society, 2018, 33(2): 370-379.
[6]	吴卫民, 何远彬, 耿攀, 等. 直流微网研究中的关键技术[J]. 电工技术学报, 2012, 27(1): 98-106, 113.
	WU Weimin, HE Yuanbin, GENG Pan, et al. Key technologies for DC micro-grids[J]. Transactions of China Electrotechnical Society, 2012, 27(1): 98-106, 113.
[7]	张小莲, 汪麒, 张仰飞, 等. 基于双电压环补偿的直流微网下垂控制[J]. 电力建设, 2021, 42(3): 72-80. doi: 10.12204/j.issn.1000-7229.2021.03.009
	ZHANG Xiaolian, WANG Qi, ZHANG Yangfei, et al. DC-microgrid droop control based on double voltage compensation[J]. Electric Power Construction, 2021, 42(3): 72-80. doi: 10.12204/j.issn.1000-7229.2021.03.009
[8]	曾浩, 赵恩盛, 周思宇, 等. 基于电流一致性的直流微网自适应下垂控制[J]. 电力系统保护与控制, 2022, 50(12): 11-21.
	ZENG Hao, ZHAO Ensheng, ZHOU Siyu, et al. Adaptive droop control of a DC microgrid based on current consistency[J]. Power System Protection and Control, 2022, 50(12): 11-21.
[9]	彭克, 陈佳佳, 徐丙垠, 等. 柔性直流配电系统稳定性及其控制关键问题[J]. 电力系统自动化, 2019, 43(23): 90-98, 115.
	PENG Ke, CHEN Jiajia, XU Bingyin, et al. Key issues of stability and control in flexible DC distribution system[J]. Automation of Electric Power Systems, 2019, 43(23): 90-98, 115.
[10]	张宇涵, 杜贵平, 雷雁雄, 等. 直流微网混合储能系统控制策略现状及展望[J]. 电力系统保护与控制, 2021, 49(3): 177-187.
	ZHANG Yuhan, DU Guiping, LEI Yanxiong, et al. Current status and prospects of control strategy for a DC micro grid hybrid energy storage system[J]. Power System Protection and Control, 2021, 49(3): 177-187.
[11]	郑凯元, 杜文娟, 王海风. 动态单元间交互作用对直流微电网稳定性影响的分析[J]. 中国电机工程学报, 2021, 41(23): 7963-7980.
	ZHENG Kaiyuan, DU Wenjuan, WANG Haifeng. Analysis on the stability of DC microgrid affected by interactions among dynamic components[J]. Proceedings of the CSEE, 2021, 41(23): 7963-7980.
[12]	郭力, 冯怿彬, 李霞林, 等. 直流微电网稳定性分析及阻尼控制方法研究[J]. 中国电机工程学报, 2016, 36(4): 927-936.
	GUO Li, FENG Yibin, LI Xialin, et al. Stability analysis and research of active damping method for DC microgrids[J]. Proceedings of the CSEE, 2016, 36(4): 927-936.
[13]	张辉, 杨甲甲, 支娜, 等. 基于无源阻尼的直流微电网稳定性分析[J]. 高电压技术, 2017, 43(9): 3100-3109.
	ZHANG Hui, YANG Jiajia, ZHI Na, et al. Stability analysis of DC microgrid based on the passive damping method[J]. High Voltage Engineering, 2017, 43(9): 3100-3109.
[14]	朱晓荣, 谢志云, 荆树志. 直流微电网虚拟惯性控制及其稳定性分析[J]. 电网技术, 2017, 41(12): 3884-3893.
	ZHU Xiaorong, XIE Zhiyun, JING Shuzhi. Virtual inertia control and stability analysis of DC micro-grid[J]. Power System Technology, 2017, 41(12): 3884-3893.
[15]	朱晓荣, 孟欣欣. 直流微电网的稳定性分析及有源阻尼控制研究[J]. 高电压技术, 2020, 46(5): 1670-1681.
	ZHU Xiaorong, MENG Xinxin. Stability analysis and research of active damping control method for DC microgrids[J]. High Voltage Engineering, 2020, 46(5): 1670-1681.
[16]	曾国辉, 廖鸿飞, 赵晋斌, 等. 直流微网双向DC/DC变换器虚拟惯量和阻尼系数自适应控制策略[J]. 电力系统保护与控制, 2022, 50(6): 65-73.
	ZENG Guohui, LIAO Hongfei, ZHAO Jinbin, et al. A self-adaptive control strategy of virtual inertia and a damping coefficient for bidirectional DC-DC converters in a DC microgrid[J]. Power System Protection and Control, 2022, 50(6): 65-73.
[17]	尹聪琦, 谢小荣, 刘辉, 等. 柔性直流输电系统振荡现象分析与控制方法综述[J]. 电网技术, 2018, 42(4): 1117-1123.
	YIN Congqi, XIE Xiaorong, LIU Hui, et al. Analysis and control of the oscillation phenomenon in VSC-HVDC transmission system[J]. Power System Technology, 2018, 42(4): 1117-1123.
[18]	崔鹏, 郭春义, 蒋雯, 等. 基于二次型指标和蒙特卡洛方法的含STATCOM的LCC-HVDC系统的控制参数优化[J]. 中国电机工程学报, 2020, 40(12): 3858-3867.
	CUI Peng, GUO Chunyi, JIANG Wen, et al. Optimization of control parameters of LCC-HVDC system with STATCOM based on Lyapunov stability and Monte Carlo algorithm[J]. Proceedings of the CSEE, 2020, 40(12): 3858-3867.
[19]	吴琦, 邓卫, 谭建鑫, 等. 基于下垂控制的多端直流系统稳定性分析[J]. 电工技术学报, 2021, 36(S2): 507-516.
	WU Qi, DENG Wei, TAN Jianxin, et al. Stability analysis of multi-terminal DC system based on droop control[J]. Transactions of China Electrotechnical Society, 2021, 36(S2): 507-516.
[20]	朱晓荣, 李铮, 孟凡奇. 基于不同网架结构的直流微电网稳定性分析[J]. 电工技术学报, 2021, 36(1): 166-178.
	ZHU Xiaorong, LI Zheng, MENG Fanqi. Stability analysis of DC microgrid based on different grid structures[J]. Transactions of China Electrotechnical Society, 2021, 36(1): 166-178.
[21]	朱晓荣, 李铮. 多换流器直流微电网稳定性分析[J]. 电网技术, 2021, 45(4): 1400-1410.
	ZHU Xiaorong, LI Zheng. Stability analysis of multi converter DC microgrid[J]. Power System Technology, 2021, 45(4): 1400-1410.
[22]	孟建辉, 邹培根, 王毅, 等. 基于灵活虚拟惯性控制的直流微网小信号建模及参数分析[J]. 电工技术学报, 2019, 34(12): 2615-2626.
	MENG Jianhui, ZOU Peigen, WANG Yi, et al. Small-signal modeling and parameter analysis of the DC microgrid based on flexible virtual inertia control[J]. Transactions of China Electrotechnical Society, 2019, 34(12): 2615-2626.
[23]	刘其辉, 洪晨威, 田若菡, 等. 基于正交优选粒子群多机参数优化的风电SSO抑制方法[J]. 电网技术, 2021, 45(12): 4660-4671.
	LIU Qihui, HONG Chenwei, TIAN Ruohan, et al. Parameter optimization of multi-DFIGs for SSO mitigation based on orthogonal design and particle swarm optimization[J]. Power System Technology, 2021, 45(12): 4660-4671.
[24]	孙峰洲, 马骏超, 朱洁, 等. 直流配电网下垂参数小干扰稳定优化调控方法[J]. 电力系统自动化, 2018, 42(3): 48-55.
	SUN Fengzhou, MA Junchao, ZHU Jie, et al. Optimized dispatching and control method of droop parameters with assurance of small-signal stability in DC distribution network[J]. Automation of Electric Power Systems, 2018, 42(3): 48-55.
[25]	WANG H, HUANG W T, YU M D, et al. The interaction mechanism and parameters optimization of multiple DC filters for second-order harmonics in DC microgrids[C]// 2021 3rd International Conference on Smart Power & Internet Energy Systems (SPIES). IEEE, 2021: 259-264.
[26]	叶运铭, 汪娟娟, 陈威, 等. 基于小干扰动态模型的LCC-HVDC系统控制器参数优化方法[J]. 南方电网技术, 2021, 15(4): 1-9.
	YE Yunming, WANG Juanjuan, CHEN Wei, et al. Controller parameters optimization method for LCC-HVDC system based on small-interference dynamic model[J]. Southern Power System Technology, 2021, 15(4): 1-9.
[27]	郑安然, 郭春义, 殷子寒, 等. 提高弱交流系统下混合多端直流输电系统小干扰稳定性的控制参数优化调节方法[J]. 电工技术学报, 2020, 35(6): 1336-1345.
	ZHENG Anran, GUO Chunyi, YIN Zihan, et al. Optimal adjustment method of control parameters for improving small-signal stability of hybrid multi-terminal HVDC system under weak AC condition[J]. Transactions of China Electrotechnical Society, 2020, 35(6): 1336-1345.
[28]	黄伟煌, 李明, 郭铸, 等. 基于小干扰稳定性的多端混合高压直流输电系统控制参数分析与优化方法[J]. 电网技术, 2020, 44(8): 2941-2949.
	HUANG Weihuang, LI Ming, GUO Zhu, et al. Control parameter analysis and optimization method of multi-terminal hybrid HVDC transmission system based on small signal stability[J]. Power System Technology, 2020, 44(8): 2941-2949.
[29]	熊连松, 刘小康, 卓放, 等. 光伏发电系统的小信号建模及其控制器参数的全局优化设计方法[J]. 电网技术, 2014, 38(5): 1234-1241.
	XIONG Liansong, LIU Xiaokang, ZHUO Fang, et al. Small-signal modeling of photovoltaic power generation system and global optimal design for its controller parameters[J]. Power System Technology, 2014, 38(5): 1234-1241.
[30]	邹培根, 孟建辉, 王毅, 等. 一种直流微电网的灵活虚拟惯性控制策略[J]. 电力建设, 2018, 39(6): 56-62. doi: 10.3969/j.issn.1000-7229.2018.06.008
	ZOU Peigen, MENG Jianhui, WANG Yi, et al. A flexible virtual inertia control strategy for DC microgrid[J]. Electric Power Construction, 2018, 39(6): 56-62. doi: 10.3969/j.issn.1000-7229.2018.06.008
[31]	李真, 王帆, 王冉珺. 一种结合灰狼算法的粒子群优化算法[J]. 计算机测量与控制, 2021, 29(10): 217-222.
	LI Zhen, WANG Fan, WANG Ranjun. An improved particle swarm optimization algorithm[J]. Computer Measurement & Control, 2021, 29(10): 217-222.