A New Filter Collaborative State Transition Algorithm for Two-Objective Dynamic Reactive Power Optimization

Dynamic Reactive Power Optimization(DRPO) is a large-scale, multi-period, and strongly coupled nonlinear mixed-integer programming problem that is difficult to solve directly. First, to handle discrete variables and switching operation constraints, DRPO is formulated as a nonlinear constrained two-objective optimization problem in this paper. The first objective is to minimize the real power loss and the Total Voltage Deviations(TVDs), and the second objective is to minimize incremental system loss. Then a Filter Collaborative State Transition Algorithm(FCSTA) is presented for solving DRPO problems. Two populations corresponding to two different objectives are employed. Moreover, the filter technique is utilized to deal with constraints. Finally, the effectiveness of the proposed method is demonstrated through the results obtained for a 24-hour test on Ward & Hale 6 bus, IEEE 14 bus, and IEEE 30 bus test power systems. To substantiate the effectiveness of the proposed algorithms, the obtained results are compared with different approaches in the literature.

Dynamic reactive power planning method for CSP-PV hybrid power generation system

Aiming at the faults of some weak nodes in the concentrated solar power-photovoltaic(CSP-PV)hybrid power generation system,it is impossible to restore the transient voltage only relying on the reactive power regulation capability of the system itself.We propose a dynamic reactive power planning method suitable for CSP-PV hybrid power generation system.The method determines the installation node of the dynamic reactive power compensation device and its compensation capacity based on the reactive power adjustment capability of the system itself.The critical fault node is determined by the transient voltage stability recovery index,and the weak node of the system is initially determined.Based on this,the sensitivity index is used to determine the installation node of the dynamic reactive power compensation device.Dynamic reactive power planning optimization model is established with the lowest investment cost of dynamic reactive power compensation device and the improvement of system transient voltage stability.Furthermore,the component of the reactive power compensation node is optimized by particle swarm optimization based on differential evolution(DE-PSO).The simulation results of the example system show that compared with the dynamic position compensation device installation location optimization method,the proposed method can improve the transient voltage stability of the system under the same reactive power compensation cost.