Heuristic Kalman Algorithm applied to the Dynamic AC Transmission Network Expansion Planning

Abstract

The transmission network is an essential part of the power system for delivering generated power to load centers, primarily through an interconnected system of transmission lines. Significant investment is required for network expansion to maintain system reliability and address congestion issues. Transmission Network Expansion Planning (TNEP) is thus essential and involves complex and large-scale mathematical and computational challenges. This research introduces a Memetic Heuristic Kalman Algorithm (HKA) combined with the Variable Neighborhood Search (VNS) meta-heuristic to solve static and dynamic TNEP. This approach is based on the AC model of the transmission network, integrating reactive power compensation planning to enhance the system's performance. Tests were conducted on the 6-bus Garver test system, demonstrating the algorithm's effectiveness in addressing the nonlinear nature of AC networks and underscoring the importance of advanced optimization techniques.