Optimal Placement of Phasor Measurement Units in Power Systems Using Genetic Algorithms

With the increasing integration of intermittent renewable energy sources into power grids, managing voltage conditions and load flows becomes more challenging due to their rapid production changes. Phasor Measurement Units (PMUs) offer real-time insight into grid parameters with microsecond precision, enabling effective regulation of dynamic processes. However, installing PMUs at every node is impractical and costly. This paper proposes a genetic algorithm-based approach to optimize the number and placement of PMUs in diverse grid topologies. The algorithm balances the objectives of maximizing observability reliability and minimizing PMU placements. The genetic algorithm efficiently solves large-scale bus systems by formulating the problem as a nonlinear optimization task, enhancing voltage stability prediction and system observability. The effectiveness of the method is demonstrated on the IEEE 39-bus, highlighting its ability to determine the minimal PMU number and distribution while maintaining network observability.