The field of power system research is moving towards the development of more efficient and sustainable energy systems. Recent studies have focused on optimizing energy storage configuration, demand flexibility, and power grid control. The use of machine learning and artificial intelligence techniques is becoming increasingly prevalent, with applications in power system security assessment, fault detection, and load forecasting. Researchers are also exploring new approaches to power grid operation, including the use of diffusion models and reinforcement learning. Notably, the 'Leveraging Multi-Task Learning for Multi-Label Power System Security Assessment' paper introduces a novel approach to power system security assessment using multi-task learning, while the 'Deep Reinforcement Learning for Power Grid Multi-Stage Cascading Failure Mitigation' paper develops a simulation environment to mitigate multi-stage cascading failures. Overall, the field is advancing towards more efficient, sustainable, and resilient power systems.
Advances in Power System Optimization and Control
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Economic Analysis and Optimization of Energy Storage Configuration for Park Power Systems Based on Random Forest and Genetic Algorithm
On the Potential of Electrified Supply Chains to Provide Long Duration Demand Flexibility
Shortlisting Protection Configurations for HVDC Grids and Electrical Energy Hubs
Leveraging Multi-Task Learning for Multi-Label Power System Security Assessment
Benchmarking Traditional Machine Learning and Deep Learning Models for Fault Detection in Power Transformers
Development of Reduced Feeder and Load Models Using Practical Topological and Loading Data
Diffusion-assisted Model Predictive Control Optimization for Power System Real-Time Operation
Deep Reinforcement Learning for Power Grid Multi-Stage Cascading Failure Mitigation
Equilibrio de carga para transformadores de distribuci\'on el\'ectrica mejorando la calidad de servicio en fin de l\'inea
Measuring Flexibility through Reduction Potential
Offline Reinforcement Learning for Microgrid Voltage Regulation
Improving Power Systems Controllability via Edge Centrality Measures