Comparison of Different Heuristic Algorithms in a Centralized Implementation of a Distributed Power Flow Control System

Today, congestion management on higher voltage levels is almost exclusively done preventively. However, integrating curative measures which utilize flexible power and innovative control equipment such as Impedance Controllers (ICs) can leverage significant benefits for grid operation. To ensure these curative measures take effect in due time, they should be activated by an automated system. In this work, a centralized replica of a distributed Multi-Agent System (MAS) is developed as a kind of simplified digital twin. The MAS uses heuristic search algorithms based on dc sensitivity analysis to eliminate grid congestion. By centrally replicating the underlying control algorithms, control interventions of the distributed system can be predicted. Also, testing and troubleshooting of new Heuristic Control Algorithms (HCAs) is facilitated by the centralized version. This way, in addition to the existing HCA, alternative heuristics are developed, implemented and tested in this centralized version. The proposed heuristics focus on the differences in the calculation of IC sensitivities and their accuracies for overload control. Besides, they make a broader range of choices of Flexible Power Units (FPUs) available to solve overloads in the grid, making the algorithm more efficient. Furthermore, the control heuristics are validated with Optimal Power Flow (OPF) approaches. For the validation of the system, the IEEE 39 New England Test-Bus system is used in Matlab MATPOWER.