## 3 Artificial Intelligence (AI) Techniques in Power Systems
### Evolutionary Methods
#### 3.4.2 Metaheuristic Optimization Technique
\begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Metaheuristic Algorithm** & **Role in Stability** & **Role in Protection** & **Role in Control** & **Other Roles** \\ \hline Particle Swarm Optimization (PSO) & Optimizing stability control strategies, tuning stability parameters & Designing optimal protection schemes, fault diagnosis & Optimizing control parameters, load flow optimization & Renewable energy scheduling, grid optimization \\ \hline Artificial Bee Colony (ABC) & Enhancing stability through optimized control actions, tuning system parameters & Fault detection and classification, adaptive protection schemes & Real-time control optimization, voltage control & Energy management, resource allocation \\ \hline Genetic Algorithms (GAs) & Optimization of stability control strategies, tuning of control parameters & Designing optimal protection settings, fault diagnosis & Solving complex control optimization problems, load flow optimization & Renewable energy scheduling, grid optimization \\ \hline Ant Colony Optimization (ACO) & Enhancing system stability by finding optimal paths for power flow flow & Fault detection, designing robust protection schemes & Control parameter optimization, dynamic load balancing & Network optimization, resource scheduling \\ \hline Differential Evolution (DE) & Stability optimization through parameter tuning, dynamic stability analysis & Designing adaptive protection schemes, fault classification & Control strategy optimization, real-time system adjustments & Demand forecasting, renewable energy integration \\ \hline Simulated Annealing (SA) & Stability enhancement by optimizing control actions, mitigating stability issues & Optimizing protection settings, fault detection & Control parameter tuning, load flow optimization & Preventive maintenance, energy management \\ \hline Harmony Search (HS) & Stability control optimization, tuning system parameters & Fault diagnosis, designing adaptive protection schemes & Real-time control optimization, voltage, and frequency control & Resource allocation, demand response management \\ \hline Firefly Algorithm (FA) & Stability enhancement through optimized control strategies, parameter tuning & Fault detection, adaptive protection schemes & Control optimization, load flow management & Smart grid operations, energy storage management \\ \hline Bat Algorithm (BA) & Optimizing stability control parameters, enhancing dynamic stability & Fault classification, designing robust protection schemes & Real-time control adjustments, optimizing control actions & Renewable energy management, asset optimization \\ \hline Cuckoo Search (CS) & Stability optimization, enhancing system resilience & Designing optimal protection settings, fault detection & Control parameter tuning, dynamic load balancing & Energy management, predictive maintenance \\ \hline Grey Wolf Optimizer (GWO) & Stability control optimization, enhancing system stability & Fault detection and classification, adaptive protection settings & Control strategy optimization, voltage, and frequency regulation & Resource scheduling, demand forecasting \\ \hline Whale Optimization Algorithm (WOA) & Stability enhancement through parameter optimization, dynamic stability analysis & Fault diagnosis, designing adaptive protection schemes & Real-time control optimization, load flow management & Smart grid operations, energy storage management \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Roles and applications of metaheuristic algorithms in power system stability, control, protection, and other aspects [60; 61; 62; 63; 64; 65; 66; 67].