The field of power distribution system restoration and energy management is moving towards more innovative and advanced solutions. Researchers are focusing on developing situationally aware and data-driven approaches to improve the efficiency and resilience of power distribution systems. The integration of renewable energy sources, energy storage systems, and smart grid technologies is becoming increasingly important. Notably, the use of machine learning and optimization techniques is being explored to enhance the performance of power distribution systems and energy management strategies. Some noteworthy papers in this area include: The paper on situationally aware rolling horizon multi-tier load restoration, which proposes a novel framework for load restoration in power distribution systems. The paper on data-driven stochastic distribution system hardening, which presents a Bayesian online learning approach to enhance the resilience of distribution systems. The paper on power distribution system blackstart restoration using renewable energy, which surveys the latest technological advances for blackstart restoration using renewable energy sources.
Advancements in Power Distribution System Restoration and Energy Management
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Situationally Aware Rolling Horizon Multi-Tier Load Restoration Considering Behind-The-Meter DER
Data-Driven Stochastic Distribution System Hardening Based on Bayesian Online Learning
Power Distribution System Blackstart Restoration Using Renewable Energy
Real-Time Peer-to-Peer Energy Trading for Multi-Microgrids: Improved Double Auction Mechanism and Prediction-Free Online Trading Approach
Incomplete Air Mixing Reduces the Efficiency of Commercial Buildings Behaving as Virtual Batteries
Efficient MPC-Based Energy Management System for Secure and Cost-Effective Microgrid Operations
Optimising Battery Energy Storage System Trading via Energy Market Operator Price Forecast
Cyber Resilience of Three-phase Unbalanced Distribution System Restoration under Sparse Adversarial Attack on Load Forecasting
Enhancing Data Center Low-Voltage Ride-Through
Cooperative Flexibility Exchange: Fair and Comfort-Aware Decentralized Resource Allocation
A Diffusion-based Generative Machine Learning Paradigm for Contingency Screening
Power Reserve Capacity from Virtual Power Plants with Reliability and Cost Guarantees
Model Predictive Control-Guided Reinforcement Learning for Implicit Balancing
Multi-Loop Design of Virtual Synchronous Machine Control for DFIG-Based Wind Farms
Mitigating Increase-Decrease Gaming with Alternative Connection Agreements: A Defender-Attacker-Defender Game