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Modeling of Electric Demand for Sustainable Energy and Management in India Using Spatio-Temporal DMSP-OLS Night-Time
Bismay Ranjan Tripathy1, Haroon Sajjad2, Christopher D Elvidge3
1National Centre for Earth Science Studies (Ministry of Earth Sciences), Post Box No.7250, Akkulam, Thiruvananthapuram, 695011, India.
Environmental Management
|December 29, 2017
Summary
This study models future electricity demand in India using nighttime satellite data and economic factors. Results show electricity demand is more sensitive to Gross Domestic Product (GDP) than population growth, aiding sustainable energy management.
Area of Science:
- Environmental Science
- Energy Economics
- Geospatial Analysis
Background:
- Electricity consumption patterns in India significantly impact energy utilization and socio-economic development.
- Assessing the spatial distribution of electricity consumption is crucial for energy resource projection and infrastructure planning.
Purpose of the Study:
- To develop a model for predicting future electricity demand in India for sustainable energy management.
- To analyze the sensitivity of electricity consumption to Gross Domestic Product (GDP) and population growth.
Main Methods:
- Utilized Defense Meteorological Satellite Program-Operational Line-Scan System (DMSP-OLS) nighttime satellite data.
- Integrated electricity consumption data (1993-2013), GDP, and population growth to construct the predictive model.
- Employed correlation analysis to examine the relationship between electricity consumption, GDP, and population.
Main Results:
- The calibrated DMSP model accurately predicted electric demand concerning GDP and population, achieving an R-squared value of 0.91.
- Correlation analysis indicated that electricity demand is more sensitive to GDP (r=0.96) than population growth (r=0.76).
Conclusions:
- The developed model is a valuable tool for forecasting electricity demand in India.
- Findings support informed decision-making for sustainable energy use and management, highlighting the significant influence of economic growth.
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