Geospatial Data Visualization of an Energy Landscape and Geographical Mapping of a Power Transmission Line Distribution Network

The developing country like India nowadays relies on the utilization of renewable energy which consist of solar, wind, biomass, hydropower and geothermal energy. Non-renewable energy includes oil, coal, nuclear power and natural gas. The macro-level goal of the undertaken research work is the design and development of big data analytics framework for rural electrification demand planning. The micro-level objective is the geographical mapping and the geospatial energy landscape data visualization of a National Grid’s power transmission line distribution network. This energy landscape data visualization would help the engineers to design the rural electrification plan accordingly based on the geospatial, population density and environmental variables of the proposed energy supply chain network. The proposed decision support system visualizes the existing energy landscape of the power transmission line with substations as nodes and distances between nodes as relationships. The respective data sets required to build the proposed decision support system are collected from the official web sources of Tamil Nadu State Government, India. The explanatory variables are identified from the data set, and feature engineering is done for geospatial energy landscape for data visualization. The IPO cycle (input–process–output cycle) of the system is designed with the identified input variables of energy landscapes. The geospatial latitude and longitude values of the Kodaikanal mountain villages are the input variables for the proposed supply chain network data visualization. The geographical mapping done through the online dynamic maps of energy landscape is shown, and patterns of them are discussed extensively.