Spatial Model for Prediction of the Vulnerable Towers Affected by River Meandering

Act, 2003 [1] and is mandated to develop, operate and maintain inter state, inter-regional and cross-border transmission systems as well as renewable energy integration. It has a network of 1,81,185 ckm transmission lines and 287 substations spread across the country. It maintains system availability above 99.84% using latest technologies in maintenance. Several cross-border links to neighbouring countries such as Bhutan, Nepal and Bangladesh are owned and operated by this utility with cumulative capacity of 4,000 MW. Presently, a number of transmission projects are under construction for strengthening of integrated Grid, enabling increased penetration of renewable energy as well as augmentation of cross-border power transfer capability.

Transmission network of major Indian utilities are spread across the country including various strategic locations such as Ladakh, Himalayan region, North-Eastern Region (NER) etc. passing through tough terrains, different climatic zones, rivers and avalanche prone areas. The change in river course, a natural phenomenon which takes place due to several reasons like floods, avalanches, heavy rain, soil erosion, landslides etc., impacts the foundation of transmission towers close to the riverbed and thus affecting stability of the tower. This increases the probability of loss of reliable power supply. Black / Greyouts have been observed lately in Eastern and NER mainly near Kosi and Brahmaputra rivers.

The risk of river meandering to transmission network, can be addressed by analysis of change in river course over time and monitoring of vulnerable towers in vicinity of rivers, using historical as well as latest spatial data.

To identify vulnerable towers due to river meandering, a solution based on utilization of advanced satellite image processing / machine learning solutions has been developed and validated.

The main objective of the developed solution is to frame a methodology and develop a GIS spatial model for identification of towers affected by change in river course or river meandering based on past data.