This paper proposes a mutual technique for solving the profit-based unit commitment (PBUC) problem in deregulated power system integrated with wind power. The proposed mutual approach is the joined execution of different solution techniques and known by the non-dominated sorting of moth fly optimization (MFO) with levy flight search (NSMFLF) technique. In the proposed approach, the levy flight search and the traditional moth flame optimization looking conduct is prepared in parallel as for the objective function and update the conceivable combination of generation units. The objective function maximizes the profit of the generating companies as for the revenue and total fuel cost in light of the gauge estimations of power demand, price and reserve power. Here, the uncertainty events of the wind power are predicted by utilizing the artificial intelligence techniques. Thus, the system is ensured with the high utilization of wind power. Finally, the non-dominated sorting is performed to choose the optimal solution from the conceivable generated combinations. The optimal combination used to maximize the profit of the generating companies and solve the PBUC problem in light of the objective function. The proposed method is implemented in the matrix laboratory working stage and the outcomes are analyzed with the current strategies.
Unit commitment based on modified firefly algorithm
