Metaheuristic Algorithm for Smart Grids Problems: A Brief Review

The modern Smart Grid fueled by extensive renewable energy, electric vehicles (EVs), and complex bidirectional power flows has rendered conventional optimization techniques obsolete. This pivotal study delivers an essential, systematic review establishing metaheuristic algorithms as the indispensable technology for mastering this operational complexity. The research methodically dissects the application of metaheuristics across eight critical domains, including Unit Commitment (UC), Distributed Energy Resource (DER) management, Optimal Power Flow (OPF), and EV/V2G coordination. By synthesizing prior investigations, the paper demonstrates that these advanced techniques consistently yield near-optimal, computationally viable solutions. The real-world impact is transformative: substantial cost savings, minimized power losses, effective peak load reduction, and dramatically improved voltage stability. Crucially, the work champions hybrid methodologies as the strategic tool to reconcile exploration and exploitation in solving the mixed-variable, multi-objective challenges inherent to power systems. Ultimately, this document validates metaheuristic optimization as the core enabling factor for a reliable, efficient, and sustainable Smart Grid. It serves as a vital strategy guide for researchers and practitioners, charting the roadmap for future directions, including real-time implementation and integration with Artificial Intelligence (AI).