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This paper estimates a model of household-level demand for electricity services and electricity demand in the Indian state of Rajasthan using a combination of household-level survey and administrative data. The model incorporates customer-level demographic characteristics, billing cycle-level weather variables, and the fact that households face increasing block prices of electricity. The model allows estimating consumer response to price changes by four categories of energy services demand, namely, heating and cooling, lighting, and for domestic and business end-uses. The knowledge of demand response across different end-use helps in differentiating the impact of price changes along the income distribution. The model finds that the demand for heating and cooling energy is the most price inelastic and income elastic service, whereas the demand for domestic end-use is the most price elastic and income inelastic service of all four categories. The structural demand model also helps in comparing the welfare implications of current energy tariffs to those based on normative principles of efficient retail electricity pricing. For this analysis, first, the social marginal cost of electricity is calculated using publicly available data on generation, transmission, and distribution losses and emissions. The social marginal cost estimate, in combination with observable household characteristics, is then used to examine alternative tariff structures that are more affordable, equitable, and revenue sufficient for the utility than current price structure. An alternative tariff design, comprising of an energy price set to the social marginal cost of electricity and a fixed cost component determined by proxy indicators of household willingness to pay, performs better on the above parameters than the current schedule. Other sources of technical losses, related to transmission or distribution, are not studied in this paper.

Electric Power --- Electricity Demand --- Energy --- Energy and Poverty Alleviation --- Energy Demand --- Energy Policies and Economics --- Energy Price --- Energy Pricing --- Energy Utility

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This paper estimates the relationship between investments in five distributed generation technologies and hourly net injections to the distribution grid for over 2,000 substations in France between 2005 and 2018. We find that investments in distributed wind and solar capacity have little or no impact on the annual peak of hourly net injections to the distribution grid, while investments in hydroelectric and thermal distributed generation significantly reduce it. An optimistic analysis of battery storage suggests that high levels of investments are required for distributed wind and solar investments to deliver similar reductions in the annual peak of hourly net injections.