A Critical Analysis of Modeling Aspects of D-STATCOMs for Optimal Reactive Power Compensation in Power Distribution Networks

Distribution static compensators (D-STATCOMs) can enhance the technical performance of the power distribution network by providing rapid and continuous reactive power support to the connected bus. Accurate modeling and efficient utilization of D-STATCOMs can maximize their utility. In this regard, this article offers a novel current-injection-based D-STATCOM model under the power control mode of operation for the reactive power compensation of the power distribution network. The versatility of the proposed D-STATCOM model is demonstrated by combining it with two of the most established distribution load flow techniques, viz., the forward–backward sweep load flow and the BIBC–BCBV-matrix-based direct load flow. Further, the allocation of the proposed D-STATCOM model is carried out under a multiobjective mathematical formulation consisting of various technical and economic indices such as the active power loss reduction index, voltage variation minimization index, voltage stability improvement index and annual expenditure index. A novel parameter-free metaheuristic algorithm, namely a student-psychology-based optimization algorithm, is proposed to determine the optimal assignment of the different number of D-STATCOM units under the multiobjective framework. The proposed allocation scheme is implemented on a standard 33-bus test system and on a practical 51-bus rural distribution feeder. The obtained results demonstrate that the proposed D-STATCOM model can be efficiently integrated into the distribution load flow algorithms. The student-psychology-based optimization algorithm is found to be robust and efficient in solving the optimal allocation of D-STATCOMs as it yields minimum power loss compared to other established approaches for 33-bus PDNs. Further, the economic analysis carried out in this work can guide network operators in deciding on the number of D-STATCOMs to be augmented depending on the investment costs and the resulting savings.