Current power distribution system faces challenges that originate from aging infrastructure, DER integration, and frequent natural disasters.

This thesis provides a comprehensive overview of all major reinforcement learning algorithms and a review of all areas of home energy management systems.

The energy management of a cyber physical system is a difficult task because of the complexity of hardware architectures and the use of OS. In addition, these systems are deployed in changing environments where their energy harvesting ...

In this work, HVAC setpoints are the control variables developed on top of a Direct Digital Control (DDC) system.

This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics.

As a field, reinforcement learning has progressed tremendously in the past decade. The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning.

The book shows how the operation of renewable-energy microgrids can be facilitated by the use of model predictive control (MPC).

... based system ( KBS ) or ES . An ES can emulate human problem solving by representing the expertise in its knowledge ... learning has received attention from the Al community from the beginning . Nowadays machine learning is widely ...

It addresses current proposed local market models and lessons from their limited practical implementation. The work discusses relevant decision and informatics tools considered important in the implementation of local electricity markets.