Model Predictive Control-Based Approach for Microgrids

Dear Colleagues,

In recent years, the scientific literature on microgrids has focused on finding solutions for their decarbonization, making a strong and significant contribution to the broader topic of decarbonizing large-scale energy networks. Further advances in the field of microgrids are highly desirable, particularly in light of recent developments at the 28th United Nations Conference on Climate Change (COP28). During this event, the agreements among political decision makers did not provide the necessary momentum to achieve the objectives set by the Paris Agreement within the deadline.

While the commitment of political decision makers and the allocation of appropriate funds are crucial for the large-scale implementation of decarbonization policies in the energy sector, it is equally important that the maturity of potentially adoptable solutions is already high when such policies are finally being implemented. In this context, this Special Issue, titled "Model Predictive Control-Based Approach for Microgrids", aims to compile the state of the art in scientific research on this topic.

The optimization of energy microgrids through model-based predictive control (MPC) schemes enables the reconciliation of different operational objectives while respecting the constraints imposed by the considered scenarios. Importantly, the iterative nature of MPC and the use of a future time horizon for optimization allows for the implementation of robust control/resource management policies for microgrids that can withstand uncertainties in the system, such as energy generation from renewable sources, among other factors.

Topics of interest for this Special Issue include, but are not limited to, the following:

• Centralized, decentralized, distributed, and hybrid approaches;
• Integrated approaches (MPC in combination with data-driven techniques, such as, and not restricted to, RL);
• Deterministic and stochastic settings;
• Single, multiple, and microgrid aggregation;
• Single and multilevel control architectures;
• AC, DC, and hybrid microgrid;
• Renewable integration and decarbonization;
• Smart microgrid and smart grid modeling, simulations, and operations;
• Smart sector integration (e.g., green transport systems) and/or strictly related topics (e.g., energy communities);
• Reliability, resiliency, robustness, and stability;
• Cybersecurity, cyberthreat mitigation, cyberattack countermeasures.

Dr. Valerio Mariani
Prof. Dr. Giorgio Graditi
Dr. Maria Valenti
Prof. Dr. Luigi Glielmo
Guest Editors

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• smart/microgrid optimization
• modeling
• simulation
• model predictive control
• renewable integration
• smart sector integration
• market participation
• ancillary services
• cybersecurity