Optimal reactive power dispatch incorporating FACTS devices

What is it about?

In the present work, symbiotic organism search (SOS) algorithm is applied for the solution of optimal reactive power dispatch (ORPD) problem of power system considering flexible AC transmission system (FACTS) devices. The proposed method is tested and examined on modified IEEE 30-bus test system with two types of FACTS devices viz. thyristor controlled series capacitor (TCSC) and thyristor controlled phase shifter (TCPS), placed at some strategic locations. In the current study, ORPD problem has been formulated as single objective, a constrained optimization problem that aims to reduce active power loss or total absolute voltage deviation individually. The formulation for the conventional OPRD problem is evaluated by considering the settings of control parameters and maintaining the constraints of the FACTS devices as an additional entity. The effectiveness of the proposed method is analyzed and compared to the results offered by some other optimization methods. The outcomes of the present work prove the potential of the SOS algorithm in solving ORPD problems of the power system incorporating FACTS devices.

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Why is it important?

RCGA, DE, and BBO have good performance but they are not free of limitations. The conventional RCGA causes an asymmetrical distribution of initial solutions in the search space. Similarly, DE and BBO exhibit unstable convergence in the last period and drop into regional optimum.The SOS aims to move a population in the optimistic region of the search space during the exploration for the optimal solution. This algorithm is implemented on modified IEEE-30 bus test system incorporating FACTS devices (viz. TCSC and TCPS) under four different case studies to explore the active power loss reductions and voltage profile improvement objectives. The recorded results of PLoss are 6.3035 MW, 6.2407 MW, 6.2389 MW and 6.2541MW for Cases 1-4, in order. Similarly, TVDs are found to be 0.12251 p.u., 0.11658 p.u., 0.11328 p.u. and 0.11110 p.u. against all the aforementioned cases. The recorded results and convergence characteristics reflect the efficacy of the proposed SOS method over the others, surfaced recently in the literature. It may be, finally, concluded that the SOS algorithm is competent enough for interpreting some more complex engineering optimization problems in near future.

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