Optimizing Rural Household Energy in Karnali through a Linear Programming Approach using Secondary Data

Abstract

This study employs a linear programming (LP) model to optimize the rural household energy consumption in Karnali Province of Nepal. The 80% households of karnali province still rely on the firewood as their primary energy source due to poor electrification rate. This study uses the secondary sources of data from the reliable sources such as government agencies, reports and publically available database. This study constructs a cost minimizing energy mix model of electricity, PV solar, LPG, and firewood. We have taken two scenarios for this simple optimization model of the energy mix. The one is with no restriction on the use of firewood and one restricting the use of firewood is in line with the forest conservation efforts. The result from the energy mix model shows that firewood as the cheapest energy source (NRs. 3.87/kWh), but its use is environmentally costly as it produces the 2.41 billion kg of CO2 annually that requires to cuts over 1.1 million trees each year in karnali. In the restricted model the households that relays on the firewood as energy sources is reduced by 98.7% that cuts the emission by over 2.37 billion kg CO2 per year by maintaining the affordable energy mix of electricity and solar with optimized cost of NRs. 671.72 per month per household. This study shows that transitioning to a balanced mix of electricity and solar energy is financially viable and environmentally critical which aligns with the SDG 7 Affordable and Clean Energy goal and with SDG 13 Climate Action goal. Since this study is aligned with the SDG’s goal, it offers a replicable policy model for rural energy transformation.