Resilient power systems urgently need real-time evaluation of their operational states. By
mining the characteristics of the grid operational data and mapping them to the operational …

以深度学习, 强化学习和迁移学习等高级机器学习为代表的新一代人工智能技术在处理海量数据
, 挖掘复杂非线性映射等方面具有更强的优势, 使其在电力系统稳定评估与决策中的应用逐渐 …

Microgrids are small-scale energy system that supplies power to homes, businesses, and
industries. Microgrids can be considered as a trending technology in energy fields due to …

One of the main reasons that affecting the stability of power systems is low frequency
oscillation (LFO). The existence of noise influences the accuracy of LFO mode identification …

A complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)
thresholding denoising method optimized by nonlocal means (NLM) algorithm is proposed …

采用离散傅里叶变换(DFT) 检测含有频率相近的谐波与间谐波的电网信号时,
信号的非同步采样会引起频谱泄露和混叠现象, 严重影响了检测精度. 针对以上问题 …

Recently, several high-frequency oscillation (HFO) events have occurred, and have
introduced a serious threat to power system stability. It is significant to estimate HFO …

The real-time identification of low-frequency electromechanical oscillations within interconn-
ected power systems is of significant interest due to its vital role in assessing the system's …

The paper presents research on mode identification of broad-band oscillation in
interconnected power system. A data-driven mode identification (DDMI) method for broad …

Today, Smart Grids (SGs), as the goal of the next-generation power grid system, span
extremely wide aspects from power generation to end-user utilities. In smart grids, Energy …