This paper proposes two population based computing techniques such as particle swarm optimization and differential algorithm to solve the dynamic optimal power flow (DOPF) problem with the prohibited zones, valve-point effects, ramp rates and security constraints. In the static optimal power flow, the system total load is constant and the problem is solved for just one period, but in the proposed approach, the multi-period OPF which is termed as dynamic OPF is considered. The, nonlinear characteristics of the alternative current power flow as well as technical constraints, such as valve-point effect and transmission constraints, are all considered for the realistic operation, and they further complicate the proposed problem. These features make the DOPF as a complicated nonlinear and non-convex optimization problem. This paper proposes two population based computing techniques such as particle swarm optimization and differential evolution algorithm to solve the DOPF problem. The IEEE 30-bus test system is implemented to illustrate the application of the proposed modeling framework. The results obtained on the IEEE 30-bus system are also compared with the results reported in the literature.
