Design and Optimization of Instability Mitigation for AC–DC Feeder Systems With Constant Power Loads Using Artificial Intelligence Techniques

Most electrical power system loads are actively controlled power electronics converters behaving as constant power loads. These loads resemble a small-signal negative impedance that can directly degrade the system stability margin and performance. The active damping approach is widely used for instability mitigation. However, if the mitigation is applied at the load side, it can affect the load performance. Therefore, this article presents a new design method for instability mitigation by the artificial intelligence method called the adaptive tabu search algorithm. After applying the proposed design method, the power system can maintain stable operation until achieving the rated power. Moreover, the load performance is better when the proposed design technique is applied compared to that from the conventional design. Good agreement among theoretical, simulation, and experimental results is also achieved.