(untitled) (Modern American Journal of Linguistics, Education, and Pedagogy, 2026)
This study presents an integrated approach to improving the energy efficiency and reliability of urban power supply systems through the coordinated use of renewable energy sources, battery energy storage systems (BESS), Smart Grid technologies, short-term load forecasting, and multi-objective optimization. The proposed framework combines photovoltaic generation, urban loads, intelligent monitoring, an LSTM-based forecasting module, and an NSGA-II optimization procedure. The forecast is used to schedule storage and balance generation and demand, while the optimization stage searches for technically feasible trade-offs among power losses, voltage quality, reliability, investment cost, and renewable-energy utilization. The reported simulation results show that BESS reduces power losses from 14.2% to 10.8%, voltage deviation from 9% to 4%, and SAIDI from 2.1 h to 1.4 h. In the specific NSGA-II test case, the modeled loss ratio decreases from 14.2% to 7.3%, and the integrated scenario improves network reliability and load balancing. The scientific contribution is the unified assessment of forecasting, storage, intelligent control, and multi-criteria optimization within one urban distribution-network framework.