Step 1: Know the methods
- Newton-Raphson: fast convergence, but complex and suitable for large systems.
- Gauss-Seidel: easy to implement, less memory, slower convergence but ideal for small/medium systems.
Step 2: Use case for Gauss-Seidel
Gauss-Seidel works well for radial or weakly meshed networks, typical of distribution systems.
Step 3: Eliminate other options
- Decoupled and Newton-Raphson are better for large systems.
- Backward/Forward Sweep is best for radial distribution but not general.
Hence, Option (2) is correct.