Dynamic optimal power flow using hybrid particle swarm optimization and simulated annealing

This paper proposes a hybrid particle swarm optimization and simulated annealing (PSO-SA) method to solve the dynamic optimal power flow (DOPF) problem while the prohibited zones, valve-point effects, and ramp rate constraints are taken into account. In the conventional optimal power flow, the total load is constant and the problem is solved for just one period, but in the proposed approach, the multiperiod OPF is considered. Also, the operating region of the units having prohibited zones is broken into isolated feasible sub-regions, which results in multiple decision spaces for the discontinuous OPF problem. Also, nonlinear characteristics of the alternative current (AC) power flow as well as technical constraints, for example, 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 a hybrid PSO-SA algorithm to solve the DOPF problem. The hybrid PSO-SA algorithm can efficiently search and explore solution space while it profits from privileges of both PSO and SA algorithms. The IEEE 30-bus test system is implemented to illustrate the application of the proposed modeling framework. Copyright (c) 2012 John Wiley & Sons, Ltd.