Digital Modeling, Operation and Control of Sustainable Energy Systems

Dear Colleagues,

The ongoing energy revolution is driving a comprehensive evolution in power system architectures, with the large-scale integration of renewable energy sources (RESs) accelerating the development of sustainable integrated energy systems. While this transformation enhances the overall cleanliness of energy systems, it also introduces multidimensional technical challenges: system-level modeling complexities, stability boundaries reshaped by reduced inertia, and exponentially increasing coordination difficulties in optimizing source–grid–load–storage systems due to the integration of massive heterogeneous distributed resources. As a critical enabler, energy storage has demonstrated unique value in mitigating the volatility of RESs, enhancing grid flexibility, and promoting renewable energy utilization. However, for these highly nonlinear and self-coupled systems, developing a systematic framework that spans "modeling–optimization–control–planning" remains a challenge requiring urgent attention.

Notably, paradigm shifts in digital technologies are opening new pathways to address these challenges. In the realm of modeling, emerging digital modeling techniques enable cross-scale mapping from device-level parameter identification to system-level dynamic forecasting. On the control side, artificial intelligence (AI)-driven methodological innovations are reshaping traditional paradigms, with real-time autonomous decision-making systems based on deep reinforcement learning significantly improving the dispatch responsiveness of wind–solar–storage hybrid systems. At the implementation level, cloud–edge–end collaborative computing platforms provide the computational foundation for plug-and-play control of millions of distributed resources. Recent breakthroughs in data-driven predictive optimization algorithms, distributed autonomous control frameworks, and hybrid enhanced decision models in renewable energy and integrated energy systems mark the transition of this field into a new era of deep “physical-information” integration.

To advance the field of sustainable energy systems under the dual contexts of energy and digital transformation, we invite you to contribute high-quality innovative research to this Special Issue, focusing on the “modeling–control–operation” technology chain for renewable and integrated energy systems enabled by next-generation AI technologies. Key topics of interest include, but are not limited to, the following: the multi-scale hybrid modeling of sustainable energy systems; outage monitoring; event detection and the resilient operation of power systems; smart optimization and scheduling for low-carbon energy systems; multi-energy complementary technologies for urban, campus, and rural integrated energy systems; intelligent planning methods for modern power systems in the context of low-carbon transitions; applications of AI in forecasting and analysis of low-carbon energy systems; autonomous restoration control under extreme events; stability analysis and control of electronic power-dominated systems; and autonomous energy management algorithms.

By fostering dialogue across multiple disciplines, this Special Issue aims to promote the organic integration of methodological innovation and practical application, ultimately enhancing the operational efficiency and global reliability of sustainable energy systems.

Dr. Yi Yu
Dr. Rongni Yang
Dr. Yingping Cao
Dr. Kuan Zhang
Dr. Hong Tan
Guest Editors

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