Sustainable digital grid asset management: UPQC-weighted SEASWARM for automated disposal and ecological impact assessment

Abstract

As the world transitions toward a more sustainable and digitalized energy landscape, the management of grid assets has become increasingly complex and critical to ensuring the efficient delivery of electricity. The integration of renewable energy systems (RES) with grid-connected load infrastructures has proven to be an effective solution for enhancing system reliability and reducing transmission losses. However, this integration often introduces power quality (PQ) issues, such as voltage sags, swells, and fluctuations, which can compromise grid stability. To address these challenges, this research proposes a novel solution for sustainable digital grid asset management using the Unified Power Quality Conditioner (UPQC) and Weighted Salp Swarm Driven One-Class Support Vector Machine (WSS-OCSVM), which integrates the Weighted Salp Swarm Algorithm (WSSA) with Weighted One-Class Support Vector Machine (WOCSVM). The approach aims to mitigate PQ disturbances, optimize asset disposal strategies, and evaluate the ecological impact of grid components. The methodology is implemented in several stages: first, the UPQC is used to regulate power quality, followed by the integration of WSS-OCSVM to optimize decision-making processes for asset management. This system is further enhanced by the SEASWARM platform, which enables intelligent adaptation and decision-making for asset disposal, considering environmental factors like carbon emissions and recyclability. The efficacy of the suggested method is confirmed by MATLAB simulation studies, which show better performance than existing techniques. Although evaluated on the 39-bus system, the suggested UPQC + WSS-OCSVM approach produced results of 99.94% accuracy. The results indicate that the UPQC + WSS-OCSVM model moderates PQ disturbances and also optimizes asset lifecycle management and promotes ecological sustainability. This comprehensive solution offers a significant advancement in the development of intelligent, resilient, and environmentally conscious modern power grids.