ICIEA 2026 Special Session
SS14: Technical Challenges and Solutions on Implementing Advanced Control Systems: Energy Systems and Electrical Drives Applications
Organized by:
Organizer 1: Jackson J. Justo
Affiliation: ITMO University, Russia; University of Dar es Salaam, Tanzania
Organizer 2: Galina Demidova
Affiliation: ITMO University, Russia; Hangzhou Dianzi University, China
Implementing advanced control systems in energy systems and electrical drive applications faces several critical challenges. Accurate instrumentation is essential as sensor errors and equipment failures can degrade control performance. Control algorithms rely on precise system models, but nonlinearities and uncertainties complicate adaptive and predictive controls. Integrating heterogeneous technologies, especially intermittent renewable energy sources, adds complexity requiring hierarchical control strategies. Real-time data management to handle vast sensor outputs is crucial for fault detection and optimization but demands robust computational resources. Ensuring robustness and reliability in the face of disturbances and faults entails designing adaptive, fault-tolerant controls. Practical concerns include maintaining system operation without frequent shutdowns and requiring skilled personnel for ongoing tuning and diagnostics. Additionally, high upfront costs and scalability issues can hinder large-scale adoption of advanced control scheme. Overcoming these challenges requires interdisciplinary approaches combining control theory, system engineering, data analytics, and practical implementation strategies to achieve efficient, reliable, and sustainable energy systems with optimized electrical drives. Implementation of advanced control systems in energy systems and electrical drives faces several technical challenges. One significant challenge lies in instrumentation and measurement. These advanced systems require accurate and reliable sensors and actuators; however, issues such as sensor noise, miscalibration, measurement resolution limits, and equipment failures can adversely affect control performance. Effective detection and compensation for these measurement problems are crucial to maintain system stability and reliability.
Relevant Topics for the Session are:
Another major challenge is related to the accuracy and limitations of models and control algorithms. Advanced control solutions, including Model Predictive Control (MPC), depend heavily on reliable dynamic models of the process. Uncertainties, nonlinearities, and changes in operating conditions can degrade model accuracy, complicating controller design and tuning. Nonlinear and adaptive controllers needed for complex processes require specialized development to manage system disturbances and dynamic behavior.
System integration complexity is also a critical issue. Energy systems often involve heterogeneous technologies, including renewable energy sources with variable outputs and interconnected electrical drives. Integrating these into a cohesive control framework requires advanced hierarchical control architectures and coordination strategies to handle intermittent power supplies and diverse control requirements.
Handling and processing large volumes of real-time data from sensors, smart meters, and communication networks present additional challenges. The control system must efficiently manage this data to enable fault detection, real-time optimization, and decision-making, which requires robust data management and computational capabilities.
Robustness and reliability are essential features for these control systems. They must maintain stable operation and performance despite disturbances, load variations, and faults. Designing adaptive and fault-tolerant control strategies to ensure safe and reliable operation under dynamic and uncertain conditions is complex.
Practical implementation and maintenance also pose challenges. Frequent system shutdowns or operator interventions diminish the benefits of advanced controls. Continuous tuning, fault diagnosis, and maintenance require skilled personnel and reliable tools to sustain optimal system performance over time.
Finally, economic and scalability considerations affect the deployment of advanced control systems in energy contexts. The high initial investment costs and the complexity involved in scaling these solutions across large, distributed energy infrastructures can be barriers to widespread adoption.
Together, these challenges require multidisciplinary efforts combining control theory, system engineering, instrumentation expertise, and practical operational strategies to successfully implement advanced control applications in energy systems and electrical drives.