Conventional microgrids face a number of challenges due to intermittency of renewable
energy resources and the lack of any effective energy management system. Thus, there is a …

In this paper, the application and future vision of Artificial Intelligence (AI)-based techniques
in microgrids are presented from a cyber-security perspective of physical devices and …

In this study, an intelligent and data-driven hierarchical energy management approach
considering the optimal participation of renewable energy resources (RER), energy storage …

Reverse power flow, defined as the continuous flow of electricity in a direction opposite to
the normal direction of the power flow in a grid, typically occurs in microgrids when the …

Given the significant challenges posed by the vast and diverse data in energy management,
this study introduces a two-stage approach: optimal energy management system (OEMS) …

High-impact and low-probability extreme events have occurred more frequently than before
because of rapid climate change, which can seriously damage distribution systems …

With the increase of energy demand and the continuous development of renewable energy
technology, active distribution networks have become increasingly important. However, the …

Modern grids are facing a reduction of system inertia and primary frequency regulation
capability due to the high penetration of distributed energy resources. In this paper, a …

This paper presents a Reinforcement Learning (RL) approach to a price-based Demand
Response (DR) program. The proposed framework manages a dynamic pricing scheme …

In the context of the expanding diversity of energy demands, an increasing number of
heterogeneous Multi-energy Microgrids (MEMGs) are engaging in the collaborative …