| Abstract: |
At a fast pace, modern electrical grids are adapting the integration of advanced automation, communication, and intelligent control techniques to meet the challenges of increased energy demand and the sustainability needs. This paper provides an empirical study of smart grid implementations regarding power system automation frameworks, as well as effective control methods based on model predictive control (MPC), fuzzy logic control (FLC) and multi-agent system (MAS). This study examines over 36 months of actual operational data collected from a regional utility grid in central India consisting of 14 substations in three grid zones. Through the application of smart grid interventions, quantitative performance metrics like system reliability index (SAIDI, SAIFI), voltage stability margin (VSM), power loss reduction, demand response efficiency, and renewable energy integration ratio were measured in a systematic manner before and after implementation. Statistical analysis both through ANOVA, regression modelling and paired t-tests verified significant improvements in all the noted parameters, p < 0.01. Results after implementation showed average outage duration reduced by 34.7%, system power losses reduced by 28.3%, demand response participation improvement of 41.5%, and renewable penetration capacity improvement which had a high of 52.6%. Benchmarking against previous studies indicates that compared to conventional automation strategies, integrated intelligent control architectures have produced better performance outcomes. Our results provide empirical justification for the scalability of smart grid implementation options for utility planners, policy makers, and researchers interested in implementing smart grid approaches in developing nations. |
