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LI Jie, WANG J, LIANG WWenteng, et al. Load model construction and parameter identification method of inverter-interfaced distributed generator [J]. Southern energy construction, 2024, 11(6): 164-173. DOI: 10.16516/j.ceec.2024.6.17
Citation: LI Jie, WANG J, LIANG WWenteng, et al. Load model construction and parameter identification method of inverter-interfaced distributed generator [J]. Southern energy construction, 2024, 11(6): 164-173. DOI: 10.16516/j.ceec.2024.6.17
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Load Model Construction and Parameter Identification Method of Inverter-Interfaced Distributed Generator

  • 1.

    State Grid Jiangsu Electric Power Co., LTD., Nanjing 210008, Jiangsu, China

  • 2.

    NARI Technology Co., LTD., Nanjing 211106, Jiangsu, China

  • 3.

    Nanjing University of Posts and Telecommunications, Nanjing 210023, Jiangsu, China

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  • Received Date: December 11, 2023
  • Revised Date: March 12, 2024
  • Available Online: September 09, 2024
    Abstract
  •   Introduction  Distributed generation (DG) has a significant impact on the operational characteristics of the load side of the power grid. However, current research focuses mainly on analyzing and modeling the characteristics of a single type of distributed generation, and there is limited research on general models that can uniformly describe DGs with certain similarities.
      Method  This article constructed an inverter-interfaced distributed generator (IIDG) model and employed a novel optimization algorithm. Firstly, based on the analysis of the characteristics and common features of IIDG, a comprehensive load model containing IIDG was constructed; According to the unified model, analytical calculations were performed to derive the state differential equation of the IIDG system and the output equation of the system model. To calculate the state and response of the system at each moment through continuous iteration and switch function updates, a formula for calculating the initial value of the system's state was provided. Combined with the sample data, the unified model identification process was given. Finally, the white shark optimizer (WSO) algorithm was employed to identify the parameters of the model; considering the voltage drop disturbance, the system model was sampled and analyzed.
      Result  The simulation results show that the proposed unified model can better reflect the IIDG characteristics in the case of different levels of voltage drop.
      Conclusion  The modeling error and parameter identification results show that the proposed unified model has good self-describing ability and parameter stability.
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    • References (25)
  • [1]
    李颖峰, 史腾肖, 库城银, 等. 分布式电源接入对配电网网络损耗的影响研究 [J]. 电工技术, 2022(14): 160-163. DOI: 10.19768/j.cnki.dgjs.2022.14.049.

    LI Y F, SHI T X, KU C Y, et al. Research on the influence of distributed power access on distribution network loss [J]. Electric engineering, 2022(14): 160-163. DOI: 10.19768/j.cnki.dgjs.2022.14.049.
    [2]
    肖峻, 王传奇. 配电网分布式发电渗透率极限值定义与计算方法 [J]. 电网技术, 2024, 48(1): 352-360. DOI: 10.13335/j.1000-3673.pst.2022.1977.

    XIAO J, WANG C Q. Definition and calculation method of DG penetration limit values of distribution network [J]. Power system technology, 2024, 48(1): 352-360. DOI: 10.13335/j.1000-3673.pst.2022.1977.
    [3]
    韩平平, 张楠, 潘薇, 等. 配电网状态估计可观性研究综述 [J]. 电力系统及其自动化学报, 2022, 34(4): 11-21. DOI: 10.19635/j.cnki.csu-epsa.000787.

    HAN P P, ZHANG N, PAN W, et al. Review of research on observability of distribution network state estimation [J]. Proceedings of the CSU-EPSA, 2022, 34(4): 11-21. DOI: 10.19635/j.cnki.csu-epsa.000787.
    [4]
    王吉利, 贺仁睦, 马进. 配网侧接入电源对负荷建模的影响 [J]. 电力系统自动化, 2007, 31(20): 22-26, 40. DOI: 10.3321/j.issn:1000-1026.2007.20.005.

    WANG J L, HE R M, MA J. Impact of connecting power sources on load modeling in a distribution network [J]. Automation of electric power systems, 2007, 31(20): 22-26, 40. DOI: 10.3321/j.issn:1000-1026.2007.20.005.
    [5]
    毛万成, 李勇, 彭衍建, 等. 光伏/微型燃气轮机混合微电网协调控制策略 [J]. 电力系统及其自动化学报, 2018, 30(4): 22-29. DOI: 10.3969/j.issn.1003-8930.2018.04.004.

    MAO W C, LI Y, PENG Y J, et al. Coordination control strategy for PV/micro-turbine hybrid micro-grid [J]. Proceedings of the CSU-EPSA, 2018, 30(4): 22-29. DOI: 10.3969/j.issn.1003-8930.2018.04.004.
    [6]
    刘君, 穆世霞, 李岩松, 等. 微电网中微型燃气轮机发电系统整体建模与仿真 [J]. 电力系统自动化, 2010, 34(7): 85-89.

    LIU J, MU S X, LI Y S, et al. Overall modeling and simulation of microturbine generation systems in microgrids [J]. Automation of electric power systems, 2010, 34(7): 85-89.
    [7]
    GHOLAMI A, AMERI M, ZANDI M, et al. A fast and precise double-diode model for predicting photovoltaic panel electrical behavior in variable environmental conditions [J]. International journal of ambient energy, 2023, 44(1): 1298-1315. DOI: 10.1080/01430750.2023.2173290.
    [8]
    屈星, 李欣然, 盛义发, 等. 面向广义负荷的光伏发电系统等效建模研究 [J]. 电网技术, 2020, 44(6): 2143-2150. DOI: 10.13335/j.1000-3673.pst.2019.1498.

    QU X, LI X R, SHENG Y F, et al. Research on equivalent modeling of PV generation system for generalized load [J]. Power system technology, 2020, 44(6): 2143-2150. DOI: 10.13335/j.1000-3673.pst.2019.1498.
    [9]
    王善立, 龙军. 含分布式储能的光伏发电系统建模与仿真 [J]. 电源技术, 2016, 40(10): 1973-1975, 2047. DOI: 10.3969/j.issn.1002-087X.2016.10.021.

    WANG S L, LONG J. Modeling and simulation of a PV system with DESS [J]. Chinese journal of power sources, 2016, 40(10): 1973-1975, 2047. DOI: 10.3969/j.issn.1002-087X.2016.10.021.
    [10]
    马腾, 付常亮, 祝得治, 等. 固体氧化物燃料电池电堆电特性的建模 [J]. 电源技术, 2011, 35(11): 1364-1367. DOI: 10.3969/j.issn.1002-087X.2011.11.010.

    MA T, FU C L, ZHU D Z, et al. Modeling of electrical characteristics of a SOFC stack [J]. Chinese journal of power sources, 2011, 35(11): 1364-1367. DOI: 10.3969/j.issn.1002-087X.2011.11.010.
    [11]
    YU R J, GUO H, CHEN H, et al. Influence of different parameters on PEM fuel cell output power: a three-dimensional simulation using agglomerate model [J]. Energy conversion and management, 2023, 280: 116845. DOI: 10.1016/j.enconman.2023.116845.
    [12]
    王玲, 李欣然, 马亚辉, 等. 燃料电池发电系统的机电动态模型 [J]. 中国电机工程学报, 2011, 31(22): 40-47. DOI: 10.13334/j.0258-8013.pcsee.2011.22.001.

    WANG L, LI X R, MA Y H, et al. Dynamic model of fuel cell power generating system [J]. Proceedings of the CSEE, 2011, 31(22): 40-47. DOI: 10.13334/j.0258-8013.pcsee.2011.22.001.
    [13]
    刘普仁, 李奇, 孟翔, 等. 基于多向差分进化算法的氢燃料电池市域动车组运行协同优化 [J]. 中国电机工程学报, 2024, 44(3): 1007-1019. DOI: 10.13334/j.0258-8013.pcsee.221627.

    LIU P R, LI Q, MENG X, et al. Collaborative optimization of hydrogen fuel cell urban emu operation based on multi-directional differential evolution algorithm [J]. Proceedings of the CSEE, 2024, 44(3): 1007-1019. DOI: 10.13334/j.0258-8013.pcsee.221627.
    [14]
    汪海姗, 王冰, 张秋桥, 等. 独立直流微电网中多组燃料电池分布式协同控制 [J]. 电气自动化, 2021, 43(2): 44-46. DOI: 10.3969/j.issn.1000-3886.2021.02.016.

    WANG H S, WANG B, ZHANG Q Q, et al. Distributed cooperative control of multi-group fuel cells in independent DC micro-grids [J]. Electrical automation, 2021, 43(2): 44-46. DOI: 10.3969/j.issn.1000-3886.2021.02.016.
    [15]
    何雄峰, 李先允, 谈益珲, 等. 微型燃气轮机发电系统LVRT特性分析研究 [J]. 电气技术, 2016, 17(6): 18-24. DOI: 10.3969/j.issn.1673-3800.2016.06.005.

    HE X F, LI X Y, TAN Y H, et al. Performance analysis and research on microturbine generation system with LVRT [J]. Electrical engineering, 2016, 17(6): 18-24. DOI: 10.3969/j.issn.1673-3800.2016.06.005.
    [16]
    马亚辉. 含分布式电源的综合负荷建模方法研究 [D]. 长沙: 湖南大学, 2013.

    MA Y H. Studies on composite load modeling of distribution network considering distributed generation [D]. Changsha: Hunan University, 2013.
    [17]
    任晓红, 万红, 俞啸, 等. 基于Park变换的三电平逆变器开路故障诊断 [J]. 工矿自动化, 2020, 46(5): 82-86, 93. DOI: 10.13272/j.issn.1671-251x.17523.

    REN X H, WAN H, YU X, et al. Open-circuit fault diagnosis of three-level inverter based on Park transformation [J]. Industry and mine automation, 2020, 46(5): 82-86, 93. DOI: 10.13272/j.issn.1671-251x.17523.
    [18]
    冯茜, 李擎, 全威, 等. 多目标粒子群优化算法研究综述 [J]. 工程科学学报, 2021, 43(6): 745-753. DOI: 10.13374/j.issn2095-9389.2020.10.31.001.

    FENG Q, LI Q, QUAN W, et al. Overview of multiobjective particle swarm optimization algorithm [J]. Chinese journal of engineering, 2021, 43(6): 745-753. DOI: 10.13374/j.issn2095-9389.2020.10.31.001.
    [19]
    GOLDBERG D E. Genetic algorithms in search, optimization, and machine learning [M]. Reading: Addison-Wesley Pub. Co., 1989.
    [20]
    GREWAL M S, ANDREWS A P. Kalman filtering: theory and practice using MATLAB® (3rd ed. ) [M]. Hoboken: Wiley-IEEE Press, 2008.
    [21]
    GUO P, ZHU L. Ant colony optimization for continuous domains [C]//2012 8th International Conference on Natural Computation, Chongqing, China, May 29-31, 2012. Chongqing: IEEE, 2012: 758-762. DOI: 10.1109/ICNC.2012.6234538.
    [22]
    BRAIK M, HAMMOURI A, ATWAN J, et al. White shark optimizer: a novel bio-inspired meta-heuristic algorithm for global optimization problems [J]. Knowledge-based systems, 2022, 243: 108457. DOI: 10.1016/j.knosys.2022.108457.
    [23]
    FATHY A, YOUSRI D, ALHARBI A G, et al. A new hybrid white shark and whale optimization approach for estimating the Li-ion battery model parameters [J]. Sustainability, 2023, 15(7): 5667. DOI: 10.3390/su15075667.
    [24]
    李小明, 董智, 高明, 等. 基于粒子群算法的中低压配电网网格化规划模型 [J]. 电气自动化, 2023, 45(2): 58-60. DOI: 10.3969/j.issn.1000-3886.2023.02.018.

    LI X M, DONG Z, GAO M, et al. Grid planning model of medium and low voltage distribution network based on particle swarm algorithm [J]. Electrical automation, 2023, 45(2): 58-60. DOI: 10.3969/j.issn.1000-3886.2023.02.018.
    [25]
    谢涛, 张春炯, 徐永健. 基于历史梯度平均方差缩减的协同参数更新方法 [J]. 电子与信息学报, 2021, 43(4): 956-964. DOI: 10.11999/JEIT200061.

    XIE T, ZHANG C J, XU Y J. Collaborative parameter update based on average variance reduction of historical gradients [J]. Journal of electronics & information technology, 2021, 43(4): 956-964. DOI: 10.11999/JEIT200061.
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    Corresponding author: ZHOU Xia, zhouxia@njupt.edu.cn
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      Nanjing University of Posts and Telecommunications, Nanjing 210023, Jiangsu, China

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