Multi-objective-optimal placement of distributed generators using adaptive optimization engaging with voltage stability indicator

Abstract Over the past decade, the impact of distributed generation (DG), including both renewable and non-renewable sources, has significantly increased in power distribution systems. This paper proposes an Adaptive Spider Monkey Optimization (ASMO) algorithm to determine the optimal placement and sizing of DG units for improving the voltage profile and overall system performance. The proposed method considers multiple objectives, including minimization of power loss, total harmonic distortion (THD), and emission, along with enhancement of voltage stability and system reliability. A novel Voltage Stability Index (VSI) is introduced and incorporated into the multi-objective framework to improve system stability. In addition, the Line Capacity Index (LCI) is utilized to identify candidate buses for optimal DG placement. The effectiveness of the proposed approach is validated on standard benchmark distribution systems, including IEEE 33, IEEE 69, IEEE 119, and Indian 52-bus systems under different operating conditions. The results demonstrate that the proposed ASMO significantly reduces power loss from 202.68 kW to 53.93 kW in the IEEE 33 bus system and from 224.96 kW to 102.61 kW in the IEEE 69 bus system. In addition, the method achieves THD values of 5.88%, 5.74%, 6.03%, and 6.19% for the respective systems. Furthermore, system reliability is improved to 94.2%, 94.2%, 95.2%, and 91.2%, respectively. These results confirm the superiority of the proposed ASMO compared to existing optimization techniques.