Intelligent Coordinated Control and Optimization of Distributed Systems and Energy Resources

As the global energy landscape continues to transform, the integration of distributed systems and energy resources - such as intermittent energy resources, small-to-large scale nuclear energy systems, energy storage, fuel cells, controllable loads (such as high-temperature electrolysis), electric vehicles, amongst others - has become a pivotal driver in advancing grid security, resilience, and operational intelligence. This Research Topic seeks to address the pressing technical and conceptual challenges that accompany the widespread deployment of these resources in both utility-scale grids and microgrid applications.

To accommodate the accelerating uptake of intermittent energy systems, power systems must adapt to increasing complexity and variability. The intelligent coordination of decentralized assets, each responding to real-time conditions and multi-scale market signals, calls for the development of robust simulation frameworks and innovative control strategies. We invite contributions that advance the understanding of how distributed systems and energy resources can be modelled, optimised, and controlled under diverse grid configurations and operating scenarios, leveraging both classical techniques and emerging technologies such as artificial intelligence (AI) and machine learning (ML).

Topics of interest include, but are not limited to:
• Sophisticated Frameworks for Simulation and Analysis - Novel approaches and tools for accurately modelling distributed systems behaviour and interactions within heterogeneous grid environments, from microgrids to large grid-scale systems.
• Algorithms for Power Flow Optimization - Novel optimization methods which maximise efficiency and reliability, enabling real-time operational decisions across hundreds of thousands of distributed systems and energy resources.
• Demand response strategies: Novel controls that enables for coordinated control of large loads for demand response participation. Such loads can include high temperature electrolysis systems, data centres, and large HVAC systems.
• Advanced Control and Smart Inverter Design - Strategies for leveraging smart inverters, autonomous agents, and adaptive control mechanisms to maintain voltage stability, ensure seamless DER integration, and facilitate participation in electricity markets.
• AI-Driven Prediction and Management - Applications of AI/ML to forecast energy generation and consumption, orchestrate multi-agent coordination, and support dynamic adaptation to grid events and uncertainties.
• Cyber-Physical Integration and Security - Empirical and theoretical studies examining how the interdependence between digital infrastructures and physical energy systems can be harnessed to improve interoperability, resilience, and cyber-physical security.

We welcome the submission of original research articles and reviews focusing on the above topics and others related to the intelligent control and optimisation of distributed energy resources and generation systems. Of particular interest are contributions showcasing the deployment of distributed optimization frameworks capable of adapting to dynamic grid conditions in real time, as well as research exploring the impacts of system-level coordination between diverse systems—such as nuclear power plants, electric vehicles, High temperature electrolysis, fuel cell, EVs, energy storage, and others—within smart grid markets.

By collecting and disseminating innovative research, this Topic aims to chart a path toward flexible, efficient, and resilient grids capable of enhancing energy security.