Modern power networks face escalating load demands, leading to severe transmission line congestion, exacerbated active power losses, and degraded voltage stability. While Flexible AC Transmission Systems (FACTS) provide a robust mechanism for dynamically controlling power flow and relieving grid bottlenecks, their prohibitive capital costs mandate precise, mathematically optimised sizing and siting. Traditional optimisation techniques frequently falter in accuracy and convergence speed due to the highly non-linear and nonconvex nature of the Optimal Power Flow (OPF) problem. To address this gap, this paper proposes a computationally rigorous grid decongestion strategy employing the Differential Evolution (DE) algorithm. Implemented via matrix mathematics in a custom MATLAB environment, the proposed methodology solves the complex OPF equations for the standard IEEE 30-bus test system. The algorithm systematically determines the optimal location and parameter sizing of FACTS devices with the dual objective of minimising total active power loss and significantly enhancing the system-wide voltage profile. By comparing the unoptimized base case against the DEoptimized framework, this study mathematically validates the technical efficiency and financial viability of algorithmic FACTS integration, offering a highly scalable blueprint for cost-effective modern grid management.

Ritesh Nirmalkar, Satya Prakash Makhija,"A Comprehensive Review of Differential Evolution Strategies for Optimal FACTS Allocation and Grid Decongestion" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(5): Page(647-655) September - October 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.