Integrated optimization of solar DG and DSTATCOM placement for enhanced EVCS-Driven Power Distribution Performance

The rapid increase in electric vehicle adoption, driven by their low maintenance, superior performance, and environmental benefits, has significantly elevated the demand on power distribution networks (PDNs). The integration of electric vehicle charging stations (EVCSs) into existing PDNs introduces critical operational challenges such as increased real power losses, reactive power losses, voltage deviations, and line congestion, which compromise system reliability and stability. To address these issues, this study proposes an enhanced optimization framework based on the Black Widow Optimization Algorithm (BWOA) and compares its performance against the conventional slime mould algorithm (SMA). The proposed model simultaneously determines the optimal placement and sizing of photovoltaic-based distributed generators (PV-DGs), distribution static compensators, and EVCSs, minimizing a normalized multiobjective function (MOF) that jointly considers real and reactive power losses, voltage deviation index, voltage stability index, and the total installation and operational cost. The framework is tested on the Institute of Electrical and Electronics Engineers 34-bus PDN under 24-h dynamic load variations and stochastic Photovoltaic system generation profiles. Simulation results demonstrate that BWOA significantly outperforms SMA in technical and economic performance. For instance, at hour 13, BWOA reduces real power losses to 48. 48 kW, compared to 102. 82 kW with SMA (a 52. 8% improvement), while reactive power losses decrease from 30. 4 kVAr to 14. 41 kVAr (a 52. 6% reduction). Voltage performance also improves, with the voltage deviation index reduced from 0. 0574 to 0. 0253 and the voltage stability index increased from 0. 7896 to 0. 9026 under BWOA, compared to 0. 0314 and 0. 8802 with SMA, respectively. Moreover, BWOA achieves significant economic benefits, reducing the total system cost from 16, 745 to 15, 892 at peak hours (5. 1% savings). Over the 24-h horizon, the proposed BWOA-based strategy achieves an average MOF reduction of 35. 7% compared to SMA, highlighting its superior capability to balance technical performance and economic feasibility. Overall, the findings underscore the effectiveness of coordinated PV-DG, distribution static compensators, and EVCS allocation in enhancing operational efficiency, voltage quality, and economic sustainability of modern distribution systems. The integration of cost components into the MOF formulation ensures a holistic optimization approach, making BWOA a promising solution for next-generation smart grid planning and real-time operational control.