Real-Time Scheduling of High-Penetrated Renewable Power Systems: An Expert Knowledge and Reinforcement Learning Hybrid Approach

S Du, T Ding, Y **ao, J Wan, J Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Modern power systems are undergoing a low-carbon and sustainable transition. The
increasing penetration of renewable energy sources (RESs) poses significant challenges to …

Eco-environmental dispatch of power system with high penetration wind farms considering demand/source side uncertainties

A Heydari, R Ebrahimi, M Ghanbari - Electric Power Systems Research, 2024 - Elsevier
In this paper, a stochastic economic-emission dispatch (EE-D) of a power system with wind
farms and flexible loads is proposed. The EE-D is defined as a stochastic multi-objective …

Blockchain-based decentralized power dispatching model for power grids integrated with renewable energy and flexible load

L Xu, D Yu, J Zhou, C ** - Processes, 2023 - mdpi.com
To cope with the energy crisis and environmental pollution, the future development of the
power system has to change towards a clean, low-carbon, flexible, and diversified direction …

[HTML][HTML] Feasibility-guaranteed machine learning unit commitment: Fuzzy Optimization approaches

B Venkatesh, MIA Shekeew, J Ma - Applied Energy, 2025 - Elsevier
The unit commitment (UC) problem is solved several times daily in a limited amount of time
and is commonly formulated using mixed-integer linear programs (MILP). However, solution …

A reinforcement learning based Lagrangian relaxation algorithm for multi-energy allocation problem in steel enterprise

M Chang, S Zhao, L Tang, J Liu, Y Zhang - Computers & Chemical …, 2025 - Elsevier
The integrated iron and steel enterprises are typically characterized by the presence of
multiple energy media that are highly coupled, frequent start-stop cycles of energy …

[HTML][HTML] Component modeling and updating method of integrated energy systems based on knowledge distillation

X Lin, W Zhong, X Lin, Y Zhou, L Jiang, L Du-Ikonen… - Energy and AI, 2024 - Elsevier
Amid the backdrop of carbon neutrality, traditional energy production is transitioning towards
integrated energy systems (IES), where model-based scheduling is key in scenarios with …

A two-stage SCUC model for distribution networks considering uncertainty and demand response

F Wang, L Gan, P Zhang - Heliyon, 2023 - cell.com
Demand response (DR) is one of the most effective and economical methods for power
operators to improve network reliability in face of uncertainty and emergencies. In this paper …

Robust Dynamic Economic Dispatch in Smart Grids Using an Intelligent Learning Technology

J Qin, H Liu, H Meng, W Gu, Q Xu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Dynamic economic dispatch is crucial for implementing real-time and efficient power
management, aiming to minimize the total cost of management over a specified period …

Redispatch Model for Real-Time Operation with High Solar-Wind Penetration and Its Adaptation to the Ancillary Services Market

K Balzer, D Watts - Applied System Innovation, 2024 - mdpi.com
Modern electrical power systems integrate renewable generation, with solar generation
being one of the pioneers worldwide. In Latin America, the greatest potential and …

A Deep Reinforcement Learning-Based Method for Signal Duration Control at Intersections with Asymmetric Traffic Flows

G Songhao - International Journal of High Speed Electronics and …, 2024 - World Scientific
At the intersection with asymmetric traffic flow, a single neural network or other control
methods cannot make a choice in time to ensure that the intersection with a large traffic flow …