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【目的】随着全球能源结构转型和可再生能源的广泛应用，具有清洁、可再生特性的光伏发电系统在电力系统中的占比日益加大，但其对电网稳定性的影响也逐渐变大。为降低光伏发电系统输出功率的波动性对电网稳定性的影响，【方法】本文提出了一种基于智能算法优化与虚拟同步发电机(virtual synchronous generator,VSG)技术的光储三相并网系统优化方法。通过深入分析VSG控制原理和储能系统控制参数(比例增益Kp和积分增益Ki)对系统电压、电流、频率方面的影响，构建了光储三相并网系统整体模型，并采用非支配排序遗传算法(nondominated sorting genetic algorithm-Ⅱ,NSGA-Ⅱ)对直流电压方差、交流频率方差进行多目标优化。优化结果通过优劣解距离法(technique for order preference by similarity to an ideal solution,TOPSIS)进行综合评价，通过和传统PI控制进行对比，验证了优化参数配置的有效性。【结果】研究表明，经过TOPSIS优化后的VSG控制系统在稳定频率和电压偏差方面的数值分别为50 Hz和-0.064%，明显优于PI控制的50.2 Hz和0.354%。基于VSG控制的系统在电压畸变率、负序电压不平衡度方面也表现优异，其中电压正弦波畸变率仅为0.12%，远低于PI控制的3.78%，负序电压不平衡度为0.002%，显著低于PI控制的0.023%。并网电压的质量显著改善，证明了NSGA-Ⅱ优化的VSG控制模型在提高系统稳定性和电能质量方面的有效性。【结论】本研究为光储并网系统的优化设计提供了新的思路和方法，为可再生能源并网技术的发展提供了有力支持，有助于推动未来能源管理系统向更高效、更可靠的方向发展。
Abstract：[Objective] With the transformation of the global energy structure and the wide application of renewable energy, photovoltaic power generation system has become one of the important energy sources because of its clean and renewable characteristics. However, the fluctuation of output power from photovoltaic power generation systems poses a challenge to the stability of the power grid. In order to solve the problem of power grid stability caused by the output power fluctuation of photovoltaic power generation system. [Methods] In this paper, an optimization method of optical storage three-phase grid-connected system based on intelligent algorithm optimization and virtual synchronous generator( VSG) technology is proposed. Through in-depth analysis of VSG control principle and the influence of energy storage system control parameters( proportional gain Kp and integral gain Ki) on system voltage, current and frequency, this study constructs the overall model of the three-phase grid-connected system, and uses nondominated sorting genetic algorithm-Ⅱ( NSGA-Ⅱ) to optimize the DC voltage variance and AC frequency variance. The optimization results are comprehensively evaluated by the technique for order preference by similarity to an ideal solution( TOPSIS) method. By comparing with the traditional PI control, the effectiveness of the optimized parameter configuration is verified. [Results] The performance of the VSG control system optimized by TOPSIS in terms of stable frequency and voltage deviation is 50 Hz and-0.064%, respectively, which is significantly better than 50.2 Hz and 0.354% of PI control. The system based on VSG control also performs well in terms of voltage distortion rate and negative sequence voltage imbalance. The voltage sine wave distortion rate is only 0.12%, which is much lower than 3.78% of PI control, and the negative sequence voltage imbalance is 0.002%, which is significantly lower than 0.023% of PI control. The quality of gridconnected voltage is significantly improved, which proves the effectiveness of NSGA-Ⅱ optimized VSG control model in improving system stability and power quality. [Conclusion] This study provides new insights and methodologies for the optimal design of PV energy storage grid-connected systems, offering robust support for the development of renewable energy grid integration technology and facilitating the evolution of future energy management systems towards greater efficiency and reliability.
[1]马晓磊,李永光,段鹏飞,等.光伏发电参与电网供电功率稳定性调节技术研究[J].电网与清洁能源,2023,39(11):105-110.MA Xiaolei, LI Yongguang, DUAN Pengfei, et al. Research on the technology of photovoltaic power generation participating in power supply stability regulation of power grids[J]. Power System and Clean Energy, 2023, 39(11):105-110.
[2]石荣亮，张兴，徐海珍，等.基于自适应模式切换的虚拟同步发电机功率控制策略[J].电工技术学报，2017,32(12):127-137.SHI Rongliang, ZHANG Xing, XU Haizhen, et al. The active and reactive power control of virtual synchronous generator based on adaptive mode switching[J]. Transactions of China Electrotechnical Society, 2017, 32(12):127-137.
[3]XU Y Y, NIAN H, WANG Y M, et al. Impedance modeling and stability analysis of VSG controlled grid-connected converters with cascaded inner control loop[J]. Energies, 2020, 13(19):5114-5114.
[4]陈阳，赵晋斌，朱弘，等.基于PQ控制的电压控制型逆变器研究[J].电力电子技术，2016,50(1):28-29.CHEN Yang, ZHAO Jinbin, ZHU Hong, et al. A PQ control strategy of voltage-controlled inverter[J]. Power Electronics, 2016,50(1):28-29.
[5]卢红文,袁旭峰,张腊华.柔性接入微电网的改进VF控制策略[J].电力科学与工程,2022,38(2):1-8.LU Hongwen, YUAN Xufeng, ZHANG Lahua. Improved VF control strategy for flexible access to microgrid[J]. Electric Power Science and Engineering, 2022, 38(2):1-8.
[6]查雨欣,林健,王悦,等.基于广义下垂控制的光伏发电系统的惯量特性分析[J].智慧电力,2021,49(2):54-59+68.ZHA Yuxin, LIN Jian, WANG Yue, et al. Analysis of inertia characteristics of photovoltaic power generation system based on generalized droop control[J]. New Energy, 2021, 49(2):54-59+68.
[7]ZHANG M R, DU Z C, WAN S B. Research on droop control strategy and parameters selection of microgrids[J]. Diangong Jishuo Xuebao/Transactions of China Electrotechnical Society, 2014, 29(2):136-144.
[8]JOAN R, ALVARO L, FREDE B, et al. Control of power converters in AC microgrids[J]. IEEE Transactions on Power Electronics,2012, 27(11):4734-4749.
[9]韩爱,林俊宏,张宇,等.风光储直流微电网的改进下垂控制研究[J].能源环境保护,2023,37(6):111-118.HAN Ai, LIN Junhong, ZHANG Yu, et al. An improved droop control method for wind-PV-storage DC microgrids[J]. Energy Environmental Protection, 2023, 37(6):111-118.
[10]张常友,朱作滨.基于储能协调的光储微网VSG控制策略研究[J].电气工程学报,2023,18(1):228-234.ZHANG Changyou, ZHU Zuobin. Research on VSG control strategy of optical storage microgrid based on energy storage coordination[J]. Journal of Electrical Engineering, 2023, 18(1):228-234.
[11]陶银正,蒲道杰,毛福斌.虚拟同步发电机技术及其在光储微电网中的应用[J].电气技术,2016(11):36-40.TAO Yinzheng, PU Daojie, MAO Fubin. Virtual synchronous generator technology and its application in PV-Storage micro-grid[J]. Electrical Engineering, 2016(11):36-40.
[12]薛家祥,胡炫,张祥颖.基于改进参数自适应VSG的逆变器并联控制研究[J].电测与仪表，2023(3):1-12.XUE Jiaxiang, Hu Xuan, ZHANG Xiangying. Research of inverter parallel control based on improved parameter adaptive VSG[J].Electrical Measurement&Instrumentation, 2023(3):1-12.
[13]贾杰,任伟.基于VSG技术的微电网虚拟惯性控制策略[J].微型电脑应用,2023,39(9):219-221.JIA Jie, REN Wei. Virtual inertial control strategy of microgrid based on VSG technology[J]. Microcomputer Applications, 2023,39(9):219-221.
[14]XIA Y, CHEN Y, WANG Y, et al. A virtual synchronous generator control strategy based on transient damping compensation and virtual inertia adaptation[J]. Applied Sciences,2025, 15(2):728.
[15]杨萍,陈卓,罗婷,等.基于VSG的光伏发电与混合储能的控制方法[J].电网与清洁能源,2023,39(2):83-91+113.YANG Ping, CHEN Zhuo, LUO Ting, et al. A control method of photovoltaic power generation and hybrid energy storage based on VSG[J]. Power System and Clean Energy, 2023, 39(2):83-91+113.
[16]张赟宁,周小萌.并网逆变器分数阶虚拟惯性的虚拟同步发电机控制技术[J].控制与决策,2021,36(2):463-468.ZHANG Yunning, ZHOU Xiaomeng. Virtual synchronous generator control technology with fractional virtual inertia for grid-connected inverters[J]. Control and Decision, 2021, 36(2):463-468.
[17]陈来军,王任,郑天文,等.基于参数自适应调节的虚拟同步发电机暂态响应优化控制[J].中国电机工程学报,2016,36(21):5724-5731+6014.CHEN Laijun, WANG Ren, ZHENG Tianwen, et al. Optimal control of transient response of virtual synchronous generator based on adaptive parameter adjustment[J]. Proceedings of the CSEE, 2016, 36(21):5724-5731+6014.
[18]禹红，夏向阳，彭梦妮，等.基于虚拟同步电机技术的混合储能平抑微网频率波动策略研究[J].电力系统保护与控制,2018,46(22):47-54.YU Hong,XIA Xiangyang,PENG Mengni,et al. Research on strategy of micro-grid frequency control in hybrid energy storage system based on virtual synchronous generator technology[J].Power System Protection and Control, 2018, 46(22):47-54.
[19]WATSON J D, LESTAS I. Frequency and voltage regulation in hybrid AC/DC networks[J]. IEEE Transactions on Control Systems Technology, 2021, 29(5):1839-1849.
[20]SHI H X, SUN K, HOU X C, et al. Equilibrium mechanism between dc voltage and ac frequency for AC-DC interlinking converters[J]. iEnergy, 2022, 1(3):279-284.
[21]MENG J H, WU X L, YE T R, et al. Output voltage response improvement and ripple reduction control for input-parallel output-parallel high-power DC supply[J]. IEEE Transactions on Power Electronics, 2023, 38(9):11102-11112.
[22]LIM S, BANDYOPADHYAY S, PERREAULT D J. Highfrequency isolated AC-DC converter with stacked architecture[C].2017 IEEE Applied Power Electronics Conference and Exposition(APEC), Tampa, FL, USA, 2017, 1789-1796.
[23]AYALEW B E, MOURSI M S E, El-Saadany E F. Enhanced DC voltage and frequency regulation for high voltage AC/DC power grid[J]. IEEE Transactions on Power Systems, 2024, 39(2):3374-3388.
[24]KJAER S B, BLAABJERG F. Design optimization of a single phase inverter for photovoltaic applications[C]. IEEE 34th Annual Conference on Power Electronics Specialist, 2003. PESC'03,Acapulco, Mexico, 2003(3)1183-1190.
[25]KREIN P T, BALOG R S. Cost-effective hundred-year life for single-phase inverters and rectifiers in solar and led lighting applications based on minimum capacitance requirements and a ripple power port[C]. 2009 Twenty-Fourth Annual IEEE Applied Power Electronics Conference and Exposition, Washington, DC,USA, 2009, 620-625.
[26]曹远征,张雷.风电场储能系统的多目标优化调度策略[J].科学技术与工程,2023,23(20):8677-8685.CAO Yuanzheng, ZHANG Lei. Multi-objective optimal scheduling of energy storage system in wind farms[J]. Science Technology and Engineering, 2023, 23(20):8677-8685.
基本信息:
DOI：10.19944/j.eptep.1674-8069.2025.05.016
中图分类号:TM615;TP18
引用信息:
[1]魏振,任杰,李仪佳,等.基于非支配排序遗传算法的虚拟同步光储并网系统动态特性解析与多目标协同控制[J].电力科技与环保,2025,41(05):852-864.DOI:10.19944/j.eptep.1674-8069.2025.05.016.
基金信息:
国网山东省电力公司科技项目（520602230006）