Application of meta-heuristic methods in economic load dispatch solving considering uncertainties

The economic load dispatch (ELD) is one of the most complex optimization problems of electrical power system. Classically, it is to identify the optimal combination of generation level of all power generating units in order tominimize the total fuel cost while satisfying the loads and losses in power transmission system. Economic load dispatch (ELD) is an importantoptimization task in power system. It is the process of allocating generation among the committed units such that the constraints imposed are satisfied andthe energy requirements are minimized. In view of the sharply increasing nature of cost of fossil fuel, energy management has gained lot of significancenowadays. A lot of research works have been carried out on this problem using several optimization techniques including classical, linear, quadratic, and nonlinear programming methods. The objective function of the ELDproblem being of highly nonlinear and non-convex nature, the classical optimization methods cannot guarantee convergence to the global optimal solution. Some soft computing techniques like Firefly Algorithm (FA), Biography Based Optimization (BBO), Particle Swarm Optimization (PSO), etc. are now being applied to find even better solution to the ELD problem. In this paper met heuristic is discussed and it is applied to solve the non-convexEconomic Load Dispatch (ELD) problem for the minimization of fuel cost. the Firefly Algorithm (FA), Biography Based Optimization (BBO), Particle Swarm Optimization (PSO) solves economic load dispatch (ELD) power system problem of six generator system with different constraints, such as power balance, prohibited operating zones, ramp-rate limits, bus voltage constraints and line flow limits. A general formulation of this algorithm is presented together with an analytical mathematical modeling to solve this problem by equivalent objective function. The results are compared with those obtained by alternative techniques proposed by the literature in order to showthat it is capable of yielding good optimal solutions with proper selection of control parameters.

کلیدواژه ها:

Biogeography Based Optimization ، Cost Function ، Constraints ، Economic Load Dispatch ، Firefly Algorithm ، Particle Swarm Optimization