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 …
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 …
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 …
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
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 …
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 …
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
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 …
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 …
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
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 …
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 …
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 …
methods cannot make a choice in time to ensure that the intersection with a large traffic flow …