Decentralized energy in India and its synergies with water-energy-food security (WEF) nexus

Decentralized energy in India and its synergies with water-energy-food security (WEF) nexus

by Varun Gaur, India (PPRE2011-13)


The majority of rural Indian households remain dependent on traditional, inefficient and harmful household energy technologies. Rural households make their energy decisions with respect to the Water-Energy-Food security (WEF) Nexus jointly, however, previous research initiatives have analyzed household energy access problem in isolation. Taking this WEF nexus into account, this thesis investigates factors influencing household energy transition and identifies an optimal village energy system (VES) for the rural communities in Uttar Pradesh, India. The thesis also analyzes the distributional impacts of VES on different categories of rural households.

Using detailed household survey data, Logit and Zoib (zero one inflated beta) regression techniques were applied to analyze household’s activities and to identify factors influencing household energy transition. The results showed that regular non-agricultural income of household’s male member increases the probability of household’s modern cooking energy and modern lighting transition by 8.6% and 13.6%, respectively. It was found that household’s higher agricultural dependence and resource endowments (more labor and cattle) lead to higher share of traditional bioenergy consumption in the total cooking energy mix. Proximity to markets and high household income were observed to positively influence household modern cooking and lighting transition. Local institutions such as local bio-energy markets and barter trade for labor- bioenergy were observed to have significant influence on household energy choice. Results also showed that government’s policy instrument such as household connection to government LPG scheme is associated with 20.5% increased probability of household using modern cooking energy as its primary cooking fuel. Results also indicated that social factors such as higher female education and young age of household head are associated with household’s increased modern cooking energy consumption in its total cooking energy mix.

The thesis utilized linear optimization technique to formulate a village energy model in GAMS (General Algebraic Modeling Software). The model identified an optimal Village Energy System (VES) considering all possible energy sources and technologies (energy systems) as well as their linkages with food security. Results confirmed energy systems interdependencies for the rural communities. For instance, results showed that the levelized cost of electricity generation from biomass gasifier power system is 2.54 INR/ MJ as compared to 2.89 INR/ MJ from grid electricity-battery based power system. However, model selected the latter for fulfilling village’s night time power needs while it assigned higher shadow price of 0.143 INR / MJ to the former. This happened because possible utilization of gasifier power system was expected to create scarcities of local bio-energy resources, resulting in costlier cooking energy system for the village. It was found that DES (Decentralized Energy System) provides demand side energy management opportunities with different energy prices at different timings of the day. Results also showed that high cost of finance deters possible adoption of renewable power technologies, such as solar power.

Lastly, the thesis constructed an agricultural household model linked with VES to analyze VES’s welfare consequences on rich and poor households. Here, household had the opportunity to purchase VES’s energy services and sell its bio-energy feedstocks to VES. For the poor household, this interaction with VES led to its increased agricultural production with around 22% increase in its farm area cultivation in summers, as well as led to reduction in its off-farm labor by around 11% which is then utilized in its own agriculture. Overall, this interaction resulted in around 4% increase in poor household’s annual income. On the down side, this interaction led to poor household shifting towards dirtier cooking energy technologies, resulting in increased external costs and CO2 emissions by around 27% and 45%, respectively. On the other hand, VES did not impact rich household’s food production and only marginally increased its economic gain. However, it led to rich household shifting towards cleaner cooking energy thereby resulting in reduction of its external costs almost by half.

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