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Among the most important subjects for modern systems, we can refer to electronic energy production for power systems with the aim of minimization the total production costs for active units which are present in power network. In other words, the purpose of economic dispatching is proper and optimal planning for production units by considering the present factors and nonlinear limitations in power network and production units. In this article, by considering the nonlinear limitations such as losses of transfer network, valve point effect on production unit function, balance of production and consumption in system, prohibited zone, production limit and increasing and decreasing rates (ramp rate), the problem of economic dispatching has converted into an optimization topic and finally, it is discussed by algorithm sine cosine and software environment, MATLAB. In order to evaluate the efficiency of proposed method, experimental systems of 6 and 13 units have been used as case studies with function of increasing fuel cost. The simulation results obtained by this proposed algorithm have been compared with the results obtained by other algorithm existing in articles. Numerical results, it shows  has the better ability for solved economic dispatching with SCA algorithm compared with other than algorithms.

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: This paper presents a learning backtracking search algorithm (LBSA) that combines the ideas of TLBO and BSA to solve optimal power flow problem that has both discrete and continuous optimization variables. The proposed method is an evolutionary technique of optimization with simple structure and single control parameter to solve numerical optimization problem. The objective functions are considered as the system real power losses, fuel cost and the gaseous emissions of the generating units and voltage profile. The proposed algorithm is applied on modified IEEE 30 bus test power system in Matlab software and the results obtained are compared with results of other algorithm.