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Dynamic Economic Dispatch (DED) is a highly complex nonlinear optimization problem with practical constraints. The aim of DED is to optimize dynamically the active power of generating units over operating time considering practical constraints such as valve point effect, prohibited zones, ramp rate limits and total power losses. In order to overcome the drawback of the two standard metaheuristics such as Firefly Algorithm (FA) and Time Varying Acceleration based Particle Swarm Optimization (PSOTVAC), a hybrid method called FAPSOTVAC is proposed to improve the solution of DED. The main idea introduced towards combining FA and PSOTVAC is to create a flexible equilibrium between exploration and exploitation during search process. The robustness of the proposed hybrid method is validated on many practical power systems (10 and 30 units) to minimize the total fuel cost considering all practical constraints. The results found prove the efficiency of the proposed FAPSOTVAC in terms of solution quality and convergence characteristics.

Application of a Novel Modified Hybrid Algorithm for Solving Dynamic Economic Dispatch Problem with Practical Constraints