IEEE

Assessing Grid Penalized Reinforcement Learning for Renewable Energy Management of Power-to-X Integrated With Intermediate Storage

Abstract: This research explores the deep reinforcement learning (DRL) based planning strategies of power-to-X (PtX) systems under uncertainties of renewable and price through a detailed case study ...
IEEE

A Cost-Effective and Eco-Friendly Micro-Grid by Employing a Model-Free Multi-Agent Reinforcement Learning Strategy for Power Management

Abstract: This paper proposes the employment of reinforcement learning based strategies to tackle the complexities of micro-grid (MG) power management. The envisioned MG comprises combined cooling, ...