PLANNING FOR ENERGY EFFICIENT SMART CITY JODHPUR, INDIA

Abstract

Energy, defined as the capacity to perform work or induce change, exists in various forms including heat, light, chemical, and electrical energy. Cities, acknowledged as drivers of economic growth, depend fundamentally on energy as a pivotal input. Increased energy consumption correlates with higher output, fostering economic development. In contrast, less developed countries exhibit lower energy consumption and consequently, limited economic output, perpetuating their status within the realm of developing nations. This global disparity is evident where the wealthiest 20 percent of the global population consume a substantial 55 percent of the world’s final energy, leaving only 45 percent for the remaining 80 percent. The energy dynamics observed across different states in India parallel the global disparity between affluent and underprivileged nations. Developed states within India demonstrate advanced electricity generation technologies and high energy consumption rates, mirroring their economic vigor. This phenomenon extends to urban, suburban, and rural settings across various states. Jodhpur City exemplifies this trend and serves as the focal point of this study. The investigation into Jodhpur City's energy landscape involved extensive consultations with experts in energy management, scientists, and administrative officers. A thorough review of literature spanning local, national, and global energy contexts identified critical gaps in energy-focused development. The study aims to formulate a viable model for developing energy-efficient infrastructure in Jodhpur City, crucial for achieving integrated and sustainable urban development. Empirical data collected from 600 households in Jodhpur City forms the foundation of this study, meticulously analyzed using SPSS and Excel software for tabulation, correlation, multiple regression, and graphical analysis. System Dynamics techniques facilitated by STELLA software enabled the development and validation of mathematical models. These models explored the interplay between variables and system behavior under diverse conditions, with energy acting as a catalyst for system development. Initial phases involved identifying control parameters influencing system functions through multiple regression techniques. Subsequently, these parameters were integrated into an energy-efficient model using System Dynamics, validated, and used to forecast scenarios up to 2041. Among various tested scenarios, one emerged as particularly effective, guiding the formulation of policy recommendations for enhancing the city's energy-efficient infrastructure. This research contributes methodological insights and practical recommendations essential for optimizing urban energy systems, critical for sustainable development in rapidly urbanizing contexts.