الفهرس 
mportance of Economic Dispatch
Unconstrained Optimization ApproachesOnly 14 pages are availabe for public view
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Abstract
The Economic Dispatch (ED) optimization is one of the fundamentals to assure reliability and security of power systems. The objective of ED is to dispatch the load among units in an economic way, at the same time operational, physical constraints are satisfied. In today’s world, environmental concerns arise as a result of the emission produced from fossil- fueled generators, which changes the classical ED problem to a multi-objective Economic Emission Dispatch (EED) problem.
This thesis addresses the optimization of the EED problem for thermal power plants subjected to the power balance equality constraint and generator operating limits. For more practical representation of the systems, the transmission losses are taken into consideration, in addition to valve loading effect.
Much research recently has been pertained to EED problem. Traditional techniques show good capability of solving the economic emission dispatch problem, but they fail to achieve satisfactory success for large scale problems or in presence of nonlinearities and non-smooth characteristics as valve-point effects. As also environmental criteria are added, the optimum schedule obtained might not be the best and the complexity increase as EED has conflicting objectives, since the emission‘s minimization is in contradiction to that of cost.
Novel techniques have proven lately to be fast and reliable for solving EED problem. In this work two recent meta-heuristic approaches are introduced, Bacterial Foraging Optimization Algorithm (BFOA) and Shuffled Frog Leaping Algorithm (SFLA). The BOFA is designed to handle complex and non-gradient objective function, where the bacteria with good foraging strategy survive. While the SFLA mimics the evolution of a group of frogs, which are partitioned and share information globally to get the optimum solution.
A Comparison is set between the two methods and other approaches after being applied to different systems with different complexity using MATLAB® program, to demonstrate the effectiveness of both algorithms. The proposed approaches showed promising results to the solution of the economic emission dispatch EED problem.