INTELLIGENT ENERGY MANAGEMENT IN SMART CITIES: EVALUATING ECONOMIC IMPACT AND DEVELOPING A STRATEGIC FRAMEWORK

Abstract

The global urban population is rising at an unprecedented pace, leading to escalating energy demands and environmental challenges. Smart cities provide a pathway for sustainable development through innovative energy management practices. Intelligent Energy Management Systems (IEMS), integrating advanced technologies like Artificial Intelligence (AI) and Internet of Things (IoT), can transform energy distribution and consumption patterns. Despite numerous pilot projects, existing research on energy systems in smart cities often lacks economic assessments and scalable frameworks that integrate cutting-edge technologies with measurable ROI and long-term sustainability goals. This study evaluates the economic impact of IEMS in smart cities, emphasizing cost-effectiveness, revenue generation, and the reduction of energy wastage. It also proposes a robust, scalable framework for intelligent energy management to optimize urban energy infrastructure. A mixed-methods approach was adopted, including a review of existing literature, case study analysis of global smart city initiatives, and economic modeling using cost-benefit analysis (CBA). A conceptual framework was developed and validated through simulations using energy consumption data from real-world urban environments. The proposed framework demonstrated a 30% reduction in energy costs, significant ROI, and revenue generation through dynamic pricing and carbon credits. Case studies highlighted the scalability of the system across diverse urban settings. The findings provide actionable insights for urban planners, policymakers, and researchers, emphasizing the economic viability and scalability of IEMS. The research contributes to sustainable development goals by bridging the gap between technological innovation and practical implementation.