Brain storm optimization algorithm based economic dispatch considering wind power

The economic dispatch problem deals with minimization of cost of producing electrical power demanded by power system. The penetration of wind power in power systems is increasing worldwide due to environmental constraints and fossil fuel depletion. The main difficulty, however, is accurate prediction of wind power which otherwise may lead to situation in network operation. For more safe and reliable operation, the penalty and reserve costs must be considered to account for power imbalance in the evaluation process. In this paper, an economic load dispatch problem (ED) for the system consisting of both thermal and wind generators is solved by brain storm optimization algorithm (BSO). The random behavior of wind power is modeled using weibull function. The factors such as overestimation and underestimation of available wind power due to power imbalance are included in cost function in addition to other classical economic dispatch terms. The proposed algorithm is tested with six standard test functions to prove its efficacy. Two test systems consisting six and forty units integrated to wind farm of comparable capacity are studied to determine the overall cost of operation.