Optimizing Control Strategies for Multi-Microgrid and Power Distribution Systems

Dear Colleagues,

The global energy landscape is shifting due to the push for decarbonization and the integration of distributed renewable energy sources (DERs) like solar and wind power. At the same time, new electrical loads such as electric vehicle (EV) charging stations, hydrogen production facilities and energy-intensive data centers are changing demand patterns and complicating power distribution. This has led to the rise in multi-microgrid (MMG) systems, aiming to create more resilient and efficient local energy networks.

However, the intermittency of renewables and the variable power demands of new loads challenge system stability, especially in maintaining voltage and frequency regulation. Extreme weather events and natural disasters further threaten interconnected grids, increasing the risk of cascading failures.

To address these challenges, decentralized control strategies are crucial. These strategies enable microgrids to operate autonomously while working together to ensure system stability. The use of artificial intelligence (AI), data-driven methods and hybrid model-based approaches offers a promising solution, helping with predictive energy management and proactive disaster control.

This Special Issue aims to explore intelligent control architectures that improve the autonomy, resilience and efficiency of MMG systems and power distribution systems. It invites research on decentralized AI-enhanced control strategies to optimize the operation of interconnected grids with high renewable penetration and new loads. Topics of interest include simulation modeling of multi-subnet microgrids, AI-based energy management, optimal dispatch, stability analysis, proactive disaster control and cybersecurity for cyber–physical systems.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:

• Simulation modeling of multi-subnet microgrid systems;
• AI-based energy management;
• optimal dispatch for multi-microgrid operation;
• data-driven and model-based cooperative control;
• frequency and voltage stability analysis;
• stability control for multi-subnet microgrid systems;
• proactive disaster-prevention control;
• cyber–physical system security.

Dr. Jie Zhao
Dr. Li Wang
Guest Editors

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