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Unit commitment is one of the most important problems in power system operation. Because of the large amount of parameters and constraints, it contains a high level of complexity. In this paper a new method based on a time-variant acceleration coefficients particle swarm optimization algorithm has been proposed to solve the unit commitment problem. Integer coding (for satisfying minimum up/down constraints) and binary coding (for satisfying spinning reserve constraint) have been utilized in the proposed method. Simulations in the different cases have been done with different sizes. Numerical results have shown the superiority and better convergence of the proposed method in comparison with other methods.

This paper explores the utilization of demand response in the day-ahead operation of an isolated microgrid in the presence of wind units. The operation of the network with high penetration wind units (i.e. uncertainty of wind units) is modeled as a unit commitment problem. In addition, electrical power storage is modeled in a daily power curve to decrease the effect of uncertainty in the wind units. Due to avoiding large-scale complexities and the deeper study effect of demand-side management on operations, the considered network is regarded as an isolated microgrid. The demand-side management is studied as demand shifting. The simulation results and discussion show the flexibility and advantages of the proposed method.

This paper proposes a real-time solution to the unit commitment problem by considering different constraints like ramp-up rate, unit operation emissions, next hours load, and minimum down time. In this method, an optimized trade-off between cost and emission has been taken into consideration. The effectiveness of the proposed method was verified by the significant outcomes demonstrated.