Adaptive operational allocation of D-SVCs in distribution feeders using modified artificial rabbits algorithm

Abstract

Voltage and reactive power management is crucial for the efficient operation of electrical distribution systems which improves power quality, reduces system losses, and maintains voltage stability, even under varying load conditions. This research introduces Modified Artificial Rabbits Optimization (MARO) to optimize the deployment and operation of Distribution-Static VAR Compensator (D-SVC). The proposed MARO incorporates two key enhancements of a Collaborative Searching Operator (CSO) to improve exploration and avoid local optima, and a Time Function (TF) mechanism to dynamically adjust the balance between exploration and exploitation during optimization. Also, an adaptive optimization model is developed that optimally allocates D-SVCs while considering hourly loading variations over a 24-hour period. Three distinct optimization scenarios are evaluated, addressing (i) minimization of energy losses, (ii) trade-off between operational savings and investment costs, and (iii) reduction of apparent power demand. Simulation results demonstrate significant improvements in cost savings and system performance considering IEEE 33 bus and large scale 85-bus distribution systems. The proposed MARO is implemented and outperforms the standard ARO and benchmark algorithms by achieving lower power losses, improved voltage stability, and higher economic savings. The algorithm demonstrated consistent performance, with lower standard deviation values across all scenarios, indicating high reliability.