Gireesh Shrimali

TL;DR: In this article, a set of statistical approaches for extracting end-use and/or appliance level data from an aggregate, or whole-building, energy signal is presented. And the authors explain how appliance-level data affords numerous benefits and why using the algorithms in conjunction with smart meters is the most cost-effective and scalable solution for getting this data.

TL;DR: In this article, the authors used a state fixed-effects model with state-specific time-trends to estimate the effects of state policies on the penetration of various emerging renewable electricity sources, including wind, biomass, geothermal, and solar photovoltaic.

TL;DR: In this article, the authors employed a cross-sectional time-series approach to evaluate the extent to which state solar financial incentives systematically encouraged market deployment of solar photovoltaic (PV) technology from 1997 to 2009.

TL;DR: In this paper, the authors assess the results to date and future prospects of commercial stove operations in India and consider how the ability of these businesses to achieve scale and become self-sustaining has been influenced by six elements of their respective business models: design, customers targeted, financing, marketing, channel strategy, and organizational characteristics.

TL;DR: In this paper, the authors conduct financial modeling of actual renewable projects in India and derive the following insights: the high cost of debt is the most pressing problem: higher cost and inferior terms of debt in India may raise the cost of renewable energy by 24-32% compared to the U.S. and Europe; which focus on finer instruments such as duration of revenue-support, revenue-certainty, investor-risk-perception, and completion/cost certainty; are not likely to be as effective, with potential impacts on the cost in the 3-11% range.