| 丁 晓,郑文明,岳 立,刘啸瑜,许一川,张峰毓.基于改进教与学优化的光伏阵列模型参数辨识研究[J].电力需求侧管理,2022,24(1):14-20 |
| 基于改进教与学优化的光伏阵列模型参数辨识研究 |
| Research on parameter identification of photovoltaic array model based on improved teaching and learning optimization |
| 投稿时间：2021-10-24 修订日期：2021-11-17 |
| DOI：10. 3969 / j. issn. 1009-1831. 2022. 01. 004 |
| 中文关键词: 光伏电站 参数辨识 教与学优化算法 Tent混沌映射 |
| 英文关键词: PV plant parameter identification teaching and learning-based optimization algorithm Tent chaotic map |
| 基金项目:国家电网有限公司科技项目（5400-202018202A-0-0-00）；国网江苏省电力有限公司常州供电分公司科技项目（B710D0208XLI） |
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| 中文摘要: |
| 光伏发电系统中阵列模型及其参数辨识的准确性对光伏电站故障诊断、发电功率预测以及并网运行的稳定性评估具有重要意义。在单二极管模型基础上建立了光伏阵列数学模型，并提出一种基于Tent混沌映射的改进教与学优化算法对模型参数进行辨识，通过实测数据和参数辨识后的仿真结果进行对比，验证了该模型的准确性、求解快速性以及稳定性，为下阶段综合能源系统建模奠定模型基础。 |
| 英文摘要: |
| The accuracy of model and parameter identification in photovoltaic（PV）power generation system is of great significance for PV plant fault diagnosis, power prediction and stability evaluation of grid-connected operation. Based on single diode model, the mathematical model of PV array is established. An improved teaching and learning - based optimization algorithm based on the Tent chaotic maps is used to identify the model parameters.The measured data are compared with the simulation results of parameter identification. The accuracy, solving speed ability and stability of model are verified. The proposed model lay the foundation of modeling integrated energy system in the further research. |
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