Demand-Side Energy Landscape Mapping of Gilgit-Baltistan and Chitral

Challenge

Gilgit Baltistan and Chitral (GBC), despite possessing over 56,200 MW of clean hydropower potential, faced a severe and chronic energy shortfall equivalent to two-thirds of the region’s annual electricity demand. The mountainous terrain, poor transmission and distribution infrastructure, and lack of investment meant effective power supply was limited to only three to four days per week in some districts. The problem was further compounded by severe seasonal variance. Water flow dropped in winters precisely when heating demand peaked forcing households to spend disproportionately on dirty alternate fuels like wood, LPG, and kerosene. A 2017 AKRSP survey had mapped energy demand across the region, but by 2019 its data required independent validation before any energy development plan could be built upon it.

Client

Agha Khan Rural Support Program

Approach

Reenergia Impact, undertook a two-tier data validation and energy landscape mapping exercise across ten districts of GBC. A stratified random sampling methodology was applied, stratifying villages by geographic region and population size, ensuring sampled villages represented 85% of the regional population. Spot verification was conducted in 59 villages, while 67 Focus Group Discussions gathered qualitative insights from community members, Village Organization heads, and local support organizations. Field teams navigated significant challenges including poor road infrastructure, security restrictions near border areas, and adverse weather. The refreshed 2019 data was then statistically generalized across the full 854-village master dataset using incremental formulas and gradient methodology.

Outcome

The study produced an updated, district-wise energy demand, supply, and gap analysis for GBC. It confirmed a significant electricity shortfall across all districts, with Chitral, Gilgit, and Skardu recording the largest gaps of 134.69 MW, 110.07 MW, and 101.62 MW respectively. Crucially, the study quantified “latent” energy demand by converting household expenditure on alternate fuels into electricity equivalents, revealing that true demand was dramatically understated — Shigar, for instance, showed a 325% increase in demand under full electrification scenarios. Ten-year demand forecasts were developed for each district, and the study concluded that a decentralized, community-based Micro-Hydro Project model was far more suitable for GBC than a centralized national grid approach, given the terrain, transmission losses, and O&M challenges involved.
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