Virtual Power Plant

Virtual power plants (VPPs) aggregate geographically dispersed renewable energy sources and other distributed energy resources (DERs) to participate in energy markets and enhance grid stability. Current research emphasizes developing advanced control and optimization strategies, often employing machine learning techniques like deep reinforcement learning and distributed optimization algorithms, to efficiently manage the inherent uncertainties and complexities of VPP operations, including real-time energy dispatch and strategic bidding. This focus on improved forecasting, robust control, and fair resource allocation is driven by the need for efficient integration of renewable energy and the increasing importance of VPPs in modern power systems. The resulting advancements have significant implications for grid modernization, market efficiency, and the broader transition to sustainable energy.

Papers

October 27, 2023

Machine Learning Infused Distributed Optimization for Coordinating Virtual Power Plant Assets
Meiyi Li, Javad Mohammadi
Optimization Purpose Renewable Energy Multi Agent Coordination Distributed Optimization Virtual Power Plant

September 15, 2023

A Stochastic Online Forecast-and-Optimize Framework for Real-Time Energy Dispatch in Virtual Power Plants under Uncertainty
Wei Jiang, Zhongkai Yi, Li Wang, Hanwei Zhang, Jihai Zhang, Fangquan Lin, Cheng Yang
High Uncertainty Anticipation Stochastic Optimization Deep Learning Based Building Energy Online Stochastic Virtual Power Plant Energy Dispatch

July 11, 2023

Safe Reinforcement Learning for Strategic Bidding of Virtual Power Plants in Day-Ahead Markets
Ognjen Stanojev, Lesia Mitridati, Riccardo de Nardis di Prata, Gabriela Hug
Safe Reinforcement Learning Deep Deterministic Policy Gradient Day Ahead Safe Reinforcement Learning Algorithm Bidding Strategy Intraday Market Virtual Power Plant

May 28, 2023

Predictability and Fairness in Load Aggregation with Deadband
F. V. Difonzo, M. Roubalik, J. Marecek
Procedural Fairness Nonlinear Dynamic Predictability Problem Band Selection Loss Design Virtual Power Plant

January 30, 2023

Learning passive policies with virtual energy tanks in robotics
Riccardo Zanella, Gianluca Palli, Stefano Stramigioli, Federico Califano
Reinforcement Learning Robotics Domain Constrained Robot Passivity Based Implicit Policy Virtual Power Plant

April 1, 2022

Synthetic Photovoltaic and Wind Power Forecasting Data
Stephan Vogt, Jens Schreiber, Bernhard Sick
Consumption Forecasting Wind Power Forecasting Solar Cell Virtual Power Plant Synthetic Power