This paper proposes a safe reinforcement learning algorithm for generation bidding
decisions and unit maintenance scheduling in a competitive electricity market environment …

Effective bidding on multiple electricity products under uncertainty would allow a more
profitable market participation for hybrid power plants with variable energy resources and …

This paper presents a novel safe reinforcement learning algorithm for strategic bidding of
Virtual Power Plants (VPPs) in day-ahead electricity markets. The proposed algorithm …

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 …

The wind power forecasting error restricts the benefit of the wind farm in the electricity
market. Considering the cooperation of wind power bidding and energy storage system …

Bi-level optimization and reinforcement learning (RL) constitute the state-of-the-art
frameworks for modeling strategic bidding decisions in deregulated electricity markets …

In this paper, a day-ahead electricity market bidding problem with multiple strategic
generation company (GEN-CO) bidders is studied. The problem is formulated as a Markov …

In this paper, we address the problem of jointly determining the energy bid submitted to the
wholesale electricity market (WEM) and the energy price charged in the retailed electricity …

Recently, various renewable energy sources and large-scale batteries have been integrated
into power grids, and renewable energy bidding and battery control become critical …

The life cycle of wind turbines depends on the operation and maintenance policies adopted.
With the critical components of wind turbines being equipped with condition monitoring and …