Results 161 to 170 of about 899,657 (289)

Optimizing Electric Vehicle Charging Scheduling With Deep Q Networks and Long Short‐Term Memory‐Based Electricity and Battery State of Charge Prediction

open access: yesEnergy Science &Engineering, EarlyView.
Schematic diagram showing the proposed approach for EV charging/discharging. ABSTRACT The number of electric vehicles (EVs) on the road is rising as a result of recent advancements in EV technology, and EVs are important to the smart grid economy. Demand response schemes involving electric vehicles have the potential to dramatically reduce the cost of ...
F. Zonuntluanga   +6 more
wiley   +1 more source

Intelligent Control Framework of District Heating Systems Considering Waste Heat Utilization in Data Centers

open access: yesEnergy Science &Engineering, EarlyView.
A deep reinforcement learning–based control architecture is proposed to coordinate heat pumps, thermal storage, renewable energy, and demand response in data center waste heat recovery systems. The agent learns optimal control actions from system states and reward feedback to achieve electrical–thermal co‐optimization under realistic operational ...
Rendong Shen   +5 more
wiley   +1 more source

A Rapid Post‐Disaster Restoration Method for Networked Microgrids Based on Adaptive Quantum Particle Swarm Optimization

open access: yesEnergy Science &Engineering, EarlyView.
To enhance the power restoration speed of networked microgrids (NMGs) after extreme natural disasters and reduce the power outage of the system, this paper proposes a rapid post‐disaster restoration method for NMGs based co‐optimization of fault repair and load restoration.
Yunfan Zhang   +3 more
wiley   +1 more source

Markov Sets.

open access: yesMATHEMATICA SCANDINAVICA, 1969
openaire   +3 more sources

Spatio‐Temporal Dual‐Encoder Transformer for Short‐Term Regional Wind Power Forecasting

open access: yesEnergy Science &Engineering, EarlyView.
ST‐DualFormer separates temporal and spatial encoding to model complex dependencies in regional wind power forecasting. The fused dual‐stream representation enables accurate short‐term regional forecasts from multi‐farm meteorological and historical power data. The method achieved 5.25% nMAE and 7.53% nRMSE for three‐day‐ahead forecasting on real‐world
Jianfeng Che   +4 more
wiley   +1 more source

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