发电技术2025，Vol.46Issue(3)：496-507,12.DOI:10.12096/j.2096-4528.pgt.24074
基于人工智能的直流微电网大信号稳定性评估方法研究
Research on Large-Signal Stability Assessment Methods of DC Microgrids Based on Artificial Intelligence
摘要
Abstract
[Objectives]DC microgrids are prone to the issue of large-signal stability due to the low inertia and constant power load characteristics.Traditional model-based methods involve complex calculations and are difficult to solve.To address these issues,this study investigates intelligent analysis methods for large-signal stability of DC microgrids.[Methods]Common artificial intelligence(AI)classifiers are selected to analyze the stability of DC microgrids.A comparative analysis is conducted on three types of common AI technologies(covering six methods)-deep learning,support vector machine,and decision trees-for large-signal stability assessment in a specific DC microgrid case study.[Results]Comparative analysis based on specific examples shows that in the large-signal stability assessment of DC microgrids,long short-term memory(LSTM)networks outperform other methods in terms of overall performance(accuracy,real-time capability,and adaptability).[Conclusions]The LSTM network classifier shows high compatibility with the state-space equations of DC microgrids,making it more suitable than traditional machine learning classifiers for large-signal stability analysis of DC microgrids.Meanwhile,ensuring the performance of the classifier requires appropriate selection of parameter values.关键词
直流微电网/分布式能源/可再生能源/储能/人工智能(AI)/机器学习/深度学习/长短期记忆网络Key words
DC microgrids/distributed energy resources/renewable energy/energy storage/artificial intelligence(AI)/machine learning/deep learning/long short-term memory network分类
能源与动力引用本文复制引用
刘宿城,栾李,李龙,洪涛,刘晓东..基于人工智能的直流微电网大信号稳定性评估方法研究[J].发电技术,2025,46(3):496-507,12.基金项目
国家自然科学基金面上项目(52277169).Project Supported by National Natural Science Foundation of China(52277169). （52277169）
