Parameter identification in load models is a critical factor for power system computation,
simulation, and prediction, as well as stability and reliability analysis. Conventional point …

Background. Due to the high maintenance costs, it is critical to make full use of operating
rooms (ORs). Operative duration is an important factor that guides research on surgery …

Over the past decades, ther have been an increased number of the Internet of Things (IoT)
sensor deployment in electrical distribution networks. This paper proposes a statistical …

Short-term load forecasting is a critical element of power systems energy management
systems. In recent years, probabilistic load forecasting (PLF) has gained increased attention …

This report presents the detailed steps of establishing the composite load model in the
power system. The derivations of estimation the ZIP model and IM model parameters are …

Harnessing the heterogeneous datasets would improve system observability. While the
current metering infrastructure in distribution network has been utilized for the operational …

传统光伏发电功率预测存在因气象因素特征提取不综合不精确而导致预测精度不高的问题.
为了充分挖掘气象因素对光伏出力的影响, 并有效利用深度学习技术在非线性拟合方面的优势 …

Traditional load analysis is facing challenges with the new electricity usage patterns due to
demand response as well as increasing deployment of distributed generations, including …

文章基于图机器学习提出了一种面向分布式光伏电站的深度时空特征提取预测模型. 首先,
针对临近区域的光伏电站进行图建模, 使用长短期记忆(long short-term memory, LSTM) …

针对微网中敏感负荷对频率和电压幅值要求较高这一情况, 笔者提出了一种下垂系数随反正切
函数变化的下垂控制策略. 把反正切函数的两种特性应用于微源的下垂控制 …