Results 241 to 250 of about 128,623 (299)

AI-enhanced multi-timescale optimization strategy for virtual power plants: Advancing losad forecasting and dynamic demand response integration. [PDF]

PLoS One
Xu G, Yang G, Bao J, Feng H, Zhang F, Zheng H.   +5 more
europepmc   +1 more source

Electrolyte Design Strategies for Static Shuttle‐Free and Long‐Life Aqueous Zinc‐Iodine Batteries

Advanced Functional Materials, EarlyView.
This review systematically summarizes recent advances in electrolyte design for static aqueous Zn‐I2 batteries, highlighting solvation regulation and interfacial engineering strategies to control reaction kinetics, suppress iodine shuttling, enhance energy density, and stabilize multi‐electron iodine redox chemistry for durable, high‐performance energy
Qianqin Zhou, Fan Zhang, Ting Liao, Ziqi Sun   +3 more
wiley   +1 more source

Machine Learning Assisted Hybrid Cuckoo Search for Predictive Optimization in Renewable Energy Systems. [PDF]

F1000Res
Dalaf N, Abbas IT.
europepmc   +1 more source

Optimization based load forecasting and demand management in smart building microgrids with Greylag Goose and Bi level graph models. [PDF]

Sci Rep
Ahamed BS, Dhanya D, Sivaramkrishnan M, Srinivas TA, Hadi AA, Khan S, Khan WA.   +6 more
europepmc   +1 more source

Mamba ECIS for power marketing customer behavior forecasting using multimodal deep learning. [PDF]

Sci Rep
Pang W, Wang X, Li K.
europepmc   +1 more source

EdgeGuard-AI: Zero-Trust and Load-Aware Federated Scheduling for Secure and Low-Latency IoT Edge Networks. [PDF]

Sensors (Basel)
Alanazi AG, Alanazi HA.
europepmc   +1 more source

Design of a hybrid learning model for establishing consistency in smart grid environment. [PDF]

Sci Rep
Mahendran S, Gomathy B.
europepmc   +1 more source

Enhancing peak demand forecasting with adaptive FastICA-transformer and entropy-based model customization. [PDF]

Sci Rep
Saeed F, Aldera S, Alkhatib M.
europepmc   +1 more source

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An ADMM-LSTM framework for short-term load forecasting

Neural Networks, 2023
Accurate short-term load forecasting (STLF) is crucial for maintaining reliable and efficient operations within power systems. With the continuous increase in volume and variety of energy data provided by renewables, electric vehicles and other sources, long short-term memory (LSTM) has emerged as an attractive approach for STLF due to its ...
Shuo Liu, Zhengmin Kong, Tao Huang 0008, Yang Du 0005, Wei Xiang 0001   +4 more
openaire   +4 more sources