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Firefly optimization is a population based technique in which the attractiveness of a firefly is determined by its attractiveness which is then encoded as the objective function of the optimization problems. Firefly algorithm is one of the newest meta-heuristic algorithms based on the mating or flashing behavior of fireflies. Economic load dispatch of generation allocates power generation to match load demand at minimal possible cost without violating power units and system constraints. This paper presents application of firefly optimization technique (FFOT) for solving convex economic load dispatch of generation. The economic load dispatch problem was formulated to minimize the total fuel cost for the heat optimal combination of thermal generators without violating any of the system constraints using quadratic fuel cost model of Sapele, Delta, Afam and Egbin power stations as case studies. The equality and inequality constraints used on the system were the power balance equation and the transmission line constraints respectively. Firefly optimization technique was then developed using appropriate control parameters for a faster convergence of the technique. The optimization technique was tested and validated on the IEEE 30-bus system and Nigerian 24-bus system. The results obtained from the IEEE 30-bus system were compared to published results obtained via Differential Evolution (DE), Ant Colony Optimization (ACO) and Genetic Algorithm (GA). The comparison confirms the superiority, fast convergence and proficiency of the algorithm.

Application of Firefly Optimization Technique for Solving Convex Economic Load Dispatch of Generation On Nigerian 330 kV, 24-Bus Grid System