Allocation of distributed generator in power networks through an enhanced jellyfish search algorithm

Abstract

This study presents the Jellyfish Search Optimizer (JS), a novel metaheuristic optimization algorithm, for the efficient allocation of multi-type distributed generations (DGs) in distribution power systems. To further enhance the performance of the original JS algorithm, a leader-based mutation-selection approach called LJS is proposed to circumvent local optima. The effectiveness of LJS is evaluated with various benchmark problems and compared with other competitive optimization algorithms. Moreover, LJS is utilized to allocate different types of DGs (Type I, Type II, and Type III) in standard IEEE and practical Portuguese distribution systems. The optimization problem of the DG allocation is performed to minimize the power loss and enhance the voltage profile by minimizing the voltage deviation (VD) and maximizing the voltage stability index (VSI) as single- and multi-objectives optimization problems. The results obtained demonstrate the superior performance of LJS in achieving optimal solutions for benchmark problems as well as for the allocation of multi-type DGs. Notably, the integration of DG Type III leads to a remarkable reduction in total power loss, achieving a reduction of 94.44 %, 98.10 % and 96.07 in IEEE 33-bus,IEEE 69-bus and 94 bus systems, respectively.

Keywords

• Jellyfish search optimizer (JS)
• Distributed generations (DGs)
• Multi-type DG allocation
• Voltage deviation
• Voltage stability