Skip to content
Log in
Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Similar papers

Open access Sep 2026

Deep Learning-Based Optimal Power Flow Algorithm with Grid Topology-Variation Perception

With the increasing penetration of renewable energy resources and the continuous diversification of power system operating conditions, data-driven methods are becoming an important means for real-time optimal power flow (OPF) decision-making in power system planning and operation because of their capability to process...

Zhen-Cheng Liang, Shan-Yu Liang, Li Xiong et al. · 0 citations
Open access Sep 2026

Hybrid LSTM–XGBoost Prediction of Power System Dynamic States Under Renewable Integration

With the increasing penetration of renewable energy and inverter-based resources, power systems exhibit stronger uncertainty and nonlinear dynamic characteristics, which increases the need for accurate short-term prediction of dynamic states. This study proposes a hybrid prediction method combining Long Short-Term Memo...

Shu-Jia Guo, Yi-Fan Tong, Xin Tong et al. · 0 citations
Open access Aug 2026

A Dual-Track Feature-Enhanced Physics-Informed Model for Accurate Wind Power Forecasting with Physical Consistency

A hybrid FCM-WGM-BiLSTM-Transformer (FW-BTP) framework integrating Fuzzy C-Means clustering, Weighted Grey Model (WGM) trend extraction, and a coupled BiLSTM-Transformer module is proposed, supporting refined scheduling in modern power systems.

Yihua Shu, Ren-Lin Pei, Yan-Xin Liu · 0 citations
Sep 2026

Optimized design and implementation of a power grid load forecasting model for renewable energy integration scenarios

Given the challenges associated with renewables-based power grids, such as greater volatility, greater non-stationarity, and traditional forecasting techniques failing to sufficiently adjust to adaptive changes, this paper studies the design and implementation of an adaptive power grid load forecasting model suitable t...

Qiang Fan, Qiang Liu, Jian Qiu et al. · 0 citations
#reinforcement learning Oct 2026

Pre-control scheme generation for extreme-weather power imbalance risk using multi-resource frequency regulation and deep reinforcement learning

To address the power imbalance risk between renewable energy output and load demand under extreme weather conditions, this paper proposes a pre-control scheme generation method based on the integration of multiple frequency regulation resources and deep reinforcement learning. First, mechanism models for wind power and...

Ze-Xin Mu, Yuan-Ting Hu, Hong-Yu Chen et al. · 0 citations
Open access Aug 2026

CoFFormer: A Collaborative Frequency-Domain-Enhanced Network for Sustainable Wind Power Forecasting Under Non-Stationary Conditions

Accurate wind power forecasting is essential for renewable-energy accommodation, low-carbon dispatch, and the sustainable operation of modern power systems. However, wind power series exhibit pronounced non-stationarity, strong volatility, and multi-scale evolution, making long-term trends and short-term disturbances d...

Yuan-Yuan Liu, Zhi-Guo Xiao, Yu-Jing Guo et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.