柴电混合无人系统功率调配控制策略

doi:10.12382/bgxb.2025.0500

摘要/Abstract

摘要：

针对柴电混合能源无人系统中逆变器与柴油发电机组并联运行时的功率分配问题，提出了一种改进的逆变器恒功率控制方法，其有功和无功功率指令分别由频率偏差和频率下垂系数、电压偏差和电压下垂系数计算得到。所提方法将柴油发电机频率和电压的动态变化直接引入逆变器控制，通过对下垂系数的合理选取，实现了逆变器与发电机并联运行时的功率均分，解决了混合能源无人系统逆变器恒功率控制模式下与柴发机组并联运行时，突加、突卸负载可能导致的发电机过载或逆功率问题。通过仿真和物理实验验证了该控制方法的有效性和可行性。

关键词: 柴电混合能源, 无人系统, 逆变器, 恒功率控制, 功率调配

Abstract:

To solve the problem of power distribution in unmanned diesel-electrical power system，this paper proposes an improved constant power control strategy of inverter.The active power control command of the strategy is obtained by calculating the frequency deviation and droop coefficient，and its reactive power control command is obtained by calculating the voltage deviation and droop coefficient.The control strategy can be used to directly introduce the dynamic changes in the frequency and voltage of diesel-engine generator into the inverter control，equally distribute the power to the inverter and diesel-engine generator when operating in parallel by properly setting the droop coefficients，and deal with the generator overload or reverse power caused by sudden loading or unloading in unmanned systems.Simulation and experiment verify that the proposed control strategy is feasible and effective.

Key words: diesel-electrical system, unmanned system, inverter, constant power control, power distribution

张雪妍, 姜远志, 肖晗, 陈雅仕, 崔德瑞. 柴电混合无人系统功率调配控制策略[J]. 兵工学报, 2025, 46(S1): 250500-.

ZHANG Xueyan, JIANG Yuanzhi, XIAO Han, CHEN Yashi, CUI Derui. Power Distribution Control Strategy of Diesel-electrical Unmanned Systems[J]. Acta Armamentarii, 2025, 46(S1): 250500-.

图/表 19

图1 独立电力系统结构

Fig.1 Structural diagram of the isolated power system

图2 逆变器拓扑结构

Fig.2 Topological structure of inverter

图3 逆变器恒功率控制框图

Fig.3 Constant-power control block diagram of inverter

图4 柴油发电机组控制框图

Fig.4 Control block diagram of diesel generator

图5 发电机下垂特性曲线

Fig.5 Generator droop characteristic curves

图6 逆变器下垂特性曲线

Fig.6 Inverter droop characteristic curves

图7 逆变器改进恒功率控制框图

Fig.7 Block diagram of improved constant-power control

图8 线路阻抗补偿环节

Fig.8 Line impedance compensation link

图9 仿真模型结构图

Fig.9 Structure diagram of simulation model

表1 仿真模型参数

Table 1 Parameters of simulation model

参数	数值
逆变器额定容量S_invN/（kV·A）	1250
发电机额定容量S_gN/（kV·A）	937.5
直流母线额定电压U_dcN/V	700
交流母线额定线电压U_N/V	390
逆变器输出滤波电感L_m/mH	70
滤波电感等效串联电阻R_m/mΩ	0.15
逆变器输出滤波电容C_f/μF	1000
滤波电容等效串联电阻R_c/mΩ	20

表2 控制参数

Table 2 Control parameters

参数	数值
逆变器有功PI控制器比例系数K_pp	0.1
逆变器有功PI控制器积分系数K_ip	30
逆变器无功PI控制器比例系数K_pq	0.5
逆变器无功PI控制器积分系数K_iq	20
发电机电压PI控制器比例系数K_pv	60
发电机电压PI控制器积分系数K_iv	200
发电机转速PI控制器比例系数K_pn	80
发电机转速PI控制器积分系数K_in	100
发电机有功—频率下垂系数m_p	0.03
发电机无功—电压下垂系数n_q	0.03
柴油机等效惯性时间常数T_D/s	0.1
限幅环节上限P_max（Q_max）	1.1
限幅环节下限P_min（Q_min）	0

图10 工况一突加负载的仿真结果

Fig.10 Simulation results of sudden loading of Case 1

图11 工况一突卸负载的仿真结果

Fig.11 Simulation results of sudden unloading of Case 1

图12 全工况负载变化的仿真结果

Fig.12 Simulation results of load change under all conditions

图13 突加负载添加线路阻抗补偿前仿真结果

Fig.13 Simulation results of sudden loading without line impedance compensation

图14 突加负载添加线路阻抗补偿后仿真结果

Fig.14 Simulation results of sudden loading with line impedance compensation

图15 实验系统实物图

Fig.15 Experimental system

图16 突加负载的实验结果

Fig.16 Experimental results of sudden loading

图17 突卸负载的实验结果

Fig.17 Experimental results of sudden unloading

参考文献 20

[1]	GAO. Uncrewed maritime systems-navy should improve its approach to maximize early investments:GAO-22-104567[R]. Washington DC, US: United States Government Accountability Office, 2022.
[2]	王亮, 陈建华, 李烨. 一种基于深度学习的无人艇海上目标识别技术[J]. 兵工学报, 2022, 43(增刊2):13-19.
	WANG L, CHEN J H, LI Y. A target identification technique for unmanned surface vessel based on deep learning[J]. Acta Armamentarii, 2022, 43 (S2):13-19. (in Chinese) doi: 10.12382/bgxb.2022.B021
[3]	O’ROURKE. Navy large unmanned surface and undersea vehicles:R45757[R]. Washington DC,WA, USA: Congressional Research Service, 2022.
[4]	李丹, 于邵祯, 杨华东. 国外水面无人艇环境感知技术前沿进展[J]. 兵工学报, 2024, 45 (增刊2):97-104.
	LI D, YU S J, YANG H D. Progress on environmental perception technology of foreign unmanned surface vehicles[J]. Acta Armamentarii, 2024, 45 (S2):97-104. (in Chinese) doi: 10.12382/bgxb.2024.0860
[5]	王东, 纪锋, 艾胜, 等. 无人船综合电力技术应用与发展分析[J]. 中国舰船研究, 2022, 17 (5):257-267.
	WANG D, JI F, AI S, et al. Analysis of the application and development of integrated electric power technology for unmanned ships[J]. Chinese Journal of Ship Research, 2022, 17 (5):257-267. (in Chinese)
[6]	曹红梅, 胡光兰, 李晓东. 国外无人潜航器能源技术发展现状与趋势研究[J]. 数字海洋与水下攻防, 2022, 5 (4):361-368.
	CAO H M, HU G L, LI X D. Research on the development status and trend of foreign unmanned underwater vehicle energy technology[J]. Digital Ovean & Underwater Warfare, 2022, 5(4):361-368. (in Chinese)
[7]	PAN P C, SUN Y W, YUAN C Q, et al. Research progress on ship power systems integrated with new energy sources:a review[J]. Renewable and Sustainable Energy Reviews, 2021, 14(4):111-118.
[8]	HU J, SHAN Y, CHENG K W, et al. Overview of power converter control in microgrids—challenges,advances,and future trends[J]. IEEE Transactions on Power Electronics, 2022, 37(8):9907-9922.
[9]	曾松林. 直驱风力发电网侧逆变器的双模式运行控制及平滑切换[D]. 秦皇岛: 燕山大学, 2023.
	ZENG S L. Dual-mode operation control and smooth switching of direct-drive wind power grid-side inverter[D]. Qinhuangdao: Yanshan University, 2023. (in Chinese)
[10]	PENG X T, YAO W, YAN C, et al, “Two-stage variable proportion coefficient based frequency support of grid-connected DFIG-WTs[J]. IEEE Transactions on Power Systems, 2020, 35(2):962-974.
[11]	ASHOURI-ZADEH A, TOULABI M, An adaptive virtual inertia controller for DFIG considering nonlinear aerodynamic efficiency[J] IEEE Transactions on Sustainable Energy, 2021, 12(2):1060-1067.
[12]	李世春, 苏凌杰, 张志刚. 基于改进粒子群算法的风电场虚拟惯量优化分配方法[J]. 智慧电力, 2023, 51(8):8-14.
	LI S C, SU L J, ZHANG Z G, et al. Virtual inertia optimization allocation method for wind farm based on improved particle swarm optimization[J]. Smart Power, 2023, 51(8):8-14. (in Chinese)
[3]	王同森, 程雪坤. 计及转速限值的双馈风机变下垂系数控制策略[J]. 电力系统保护与控制, 2021, 49(9):29-36.
	WANG T S, CHENG X K. Variable droop coefficient control strategy for doubly fed fans considering speed limits[J]. Power System Protection and Control, 2021, 49(9):29-36. (in Chinese)
[14]	张小莲, 孙啊传, 陈冲, 等. 风电场参与电网一次调频的功率分配策略[J]. 电气工程学报, 2025, 20 (1):309-316.
	ZHANG X L, SUN A C, CHEN C, et al. Power allocation strategy for wind farms participating in grid primary frequency modulation[J]. Journal of electrical engineering, 2025, 20 (1):309-316. (in Chinese)
[15]	SUN M, MIN Y, CHEN L, et al. Optimal auxiliary frequency control of wind turbine generators and coordination with synchronous generators[J]. CSEE Journal of Power and Energy Systems, 2021, 7(1): 78-85.
[16]	王祺, 余鹏, 郭建伟, 等. 风机参与系统一次调频虚拟惯量优化控制[J]. 中国电机工程学报, 2025, 45(16):6368-6379.
	WANG Q, YU P, GUO J W, et al. Virtual inertia optimization control of the system’s primary frequency modulation with wind turbine participation[J]. Proceedings of the CSEE, 2025, 45(16):6368-6379.
[17]	张祥宇, 朱永健, 付媛. 基于系统惯量需求的风储协同快速频率响应技术[J]. 中国电机工程学报, 2023, 43(14):5415-5429.
	ZHANG X Y, ZHU Y J, FU Y. Wind storage collaborative fast frequency response technology based on system inertia demand[J]. Proceedings of the CSEE, 2023, 43(14):5415-5429. (in Chinese)
[18]	祁星强, 高迪驹, 吴国栋. 面向船舶微网的虚拟同步发电机并联运行功率分配控制策略[J]. 上海海事大学学报, 2025, 46(1):120-127.
	QI X Q, GAO D J, WU G D. Power distribution control strategy for parallel operation of virtual synchronous generators for ship microgrids[J]. Journal of Shanghai Maritime University, 2025, 46(1):120-127. (in Chinese)
[19]	郝晓光, 马瑞, 李剑锋, 等. 考虑负荷变化的VSG并网模型预测有功补偿控制方法[J]. 电力系统及其自动化学报, 2024, 36 (10):135-142.
	HAO X G, MA R, LI J F, et al. Predictive active power compensation control method for VSG grid-connected model considering load variation[J]. Proceedings of the CSU-EPSA, 2024, 36 (10):135-142. (in Chinese)
[20]	CHENG H J, LI C, GHIAS A M Y M, et al. Dynamic coupling mechanism analysis between voltage and frequency in virtual synchronous generator system[J]. IEEE Transactions on Power Systems, 2024, 39(1):2365-2368.