Innovative Strategies for Power System Control: Optimizing Renewable Energy Integration for Enhanced Energy Sustainability
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".
Deadline for manuscript submissions: 30 November 2025 | Viewed by 163
Special Issue Editors
2. INESC Coimbra—Institute for Systems Engineering and Computers at Coimbra, Coimbra, Portugal
Interests: power systems analysis and simulation; power system reliability; power generation expansion planning; sustainability; distributed generation; renewable energy; electricity markets
Special Issues, Collections and Topics in MDPI journals
Interests: power systems reliability and planning; operating reserves of power systems; power flow; fuzzy power flow; transmission network adequacy evaluation; uncertainties at power systems modeling power quality
Special Issues, Collections and Topics in MDPI journals
2. INESC Coimbra—Institute for Systems Engineering and Computers at Coimbra, Coimbra, Portugal
Interests: dynamic voltage stability; influence of a wind farm in the dynamic voltage stability of a power network; wind turbines; power quality; renewable energy systems; distributed generation; electrical installations
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In order to achieve energy sustainability, the integration of renewable energy sources is vital; however, their variability and intermittency present significant challenges. Decentralized systems, including distributed energy resources (DERs), are reshaping traditional power grids into smart and resilient networks. Energy storage systems, demand-side management, and flexible load balancing also play a critical role in this paradigm. By aligning energy generation with consumption patterns, these strategies mitigate the mismatch between supply and demand, ensuring the sustainable and reliable delivery of power. Hybrid solutions that combine multiple renewable sources with large-scale energy storage provide enhanced energy resilience and reduce carbon emissions. Innovative policies and advanced technologies, such as smart grids and sophisticated control systems, are critical to sustainably meeting the growing demand for electricity. The application of innovative strategies that can control the power system is essential to addressing these issues. Real-time analytics, predictive models, and adaptive control systems enable operators to anticipate fluctuations and dynamically adjust grid operations. By adopting these strategies, the energy sector can effectively transition to a low-carbon future, ensuring a secure and reliable energy supply while overcoming the challenges posed by the integration of renewable energy.
This Special Issue aims to address all aspects of science and technology related to innovative strategies for power system control and the optimization of renewable energy integration. The scope of this Special Issue includes, but is not limited to, the following topics:
- Advanced control strategies for renewable integration;
- Renewable generation forecasting;
- Hybrid energy storage systems;
- Coordinating energy storage systems with variable renewable sources;
- Scheduling and charging optimization for EVs in smart grids;
- Advanced optimization algorithms for renewable dispatch;
- Incentive models for demand response and energy storage deployment;
- Algorithms for optimal renewable energy dispatch and grid operation;
- Dynamic grid reconfiguration strategies;
- The optimization of grid capacity to accommodate high renewable penetration;
- Convert surplus renewable electricity into hydrogen or methane for use in other sectors;
- Policy and economic incentives;
- Case studies and implementation frameworks.
Dr. Adelino J. C. Pereira
Dr. Eduardo Miguel Mendonça Gouveia
Dr. Rita Manuela Monteiro Pereira
Guest Editors
Manuscript Submission Information
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Keywords
- advanced control strategies
- renewable generation forecasting
- energy storage
- renewable sources
- smart grids
- optimization algorithms
- energy dispatch
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