Chaos Moth Flame Algorithm for Multi-Objective Dynamic Economic Dispatch Integrating with Plug-In Electric Vehicles

Dynamic economic dispatch (DED) plays an important role in the operation and control of power systems. The integration DED with space time makes it a complex challenging problem optimal decision making. By connecting plug-in electric vehicles (PEVs) to grid (V2G), fluctuations can be mitigated, benefits balancing peaks filling valleys realized. However, complexity has increased emergence penetration vehicles. This paper proposes model that takes into account day-ahead, hourly-based scheduling systems impact PEVs. To solve model, improved chaos moth flame optimization algorithm (CMFO) is introduced. faster convergence rate better global capabilities due incorporation chaotic mapping. feasibility proposed CMFO validated through numerical experiments on benchmark functions various generation units different sizes. results demonstrate superiority compared other commonly used swarm intelligence algorithms.