Virtual power plants (VPPs) have become an important technological means for large-scale
distributed energy resources to participate in the operation of power systems and electricity …

The increasing penetration of renewable generations, along with the deregulation and
marketization of power industry, promotes the transformation of energy market operation …

Market agents with renewable resources face amplified uncertainty when forecasting energy
production to securely place bids in electricity markets. To deal with uncertainties, stochastic …

The bidding behaviors of the energy storage systems (ESS) are complicated due to time
coupling and market coupling limited by their capacity states. The existing research is mainly …

This paper studies the risk management of a battery bidding in both day-ahead and intraday
markets arising from the uncertain nature of electricity prices. To this end, a coherent risk …

The transition to renewable production and smart grids is driving a massive investment to
battery storages, and reinforcement learning (RL) has recently emerged as a potentially …

Growth in the penetration of renewable energy sources makes supply more uncertain and
leads to an increase in the system imbalance. This trend, together with the single imbalance …

Deep reinforcement learning (DRL) algorithms have successfully solved many challenging
problems in various power system control scenarios. However, their decision-making …

Driven by the global decarbonization effort, the rapid integration of renewable energy into
the conventional electricity grid presents new challenges and opportunities for the battery …

Modeling electricity markets realistically plays a crucial role for understanding complex
emerging market dynamics and guiding policy making. In systems with a high share of …