Author
Listed:
- Rajeev Kumar
- Pavan Khetrapal
- Manoj Badoni
- Sourav Diwania
Abstract
Nowadays, to fulfill growing power requirements at reasonable prices, like other European countries, the Indian electricity market is now more oriented towards renewable energy resources. Today, the wind energy industry has grown from a marginal activity to a multi-billion-dollar business in India's power production sector because of its comparatively safer and positive environmental features. Though, there are several wind energy power plants generating electricity in India's different geographical locations, assessing their performance is a crucial task and an important target for stakeholders. In the present study, an attempt is made to quantitatively assess the relative operational efficiencies of 14 wind power plants in India during 2016–2017 to 2019–2020 employing a two-stage data envelopment analysis Tobit model. Further, the sensitivity analysis is implemented in the present study to assess the robustness and efficacy of the data envelopment analysis models with different combinations of inputs and outputs. Data envelopment analysis results indicate that 14% of India's wind power plants were operated at the most productive scale during the observed period 2016–2017 to 2019–2020. The Tobit regression results indicate that the wind turbines’ age adversely affects production efficiency. In contrast, the site elevation has a significant positive impact on the operational efficiency of wind power plants. Findings from the present study may help stakeholders and policy regulators in the wind industry to identify the key factors influencing the performance of ongoing wind power plants in India and optimize operational strategies and policies.
Suggested Citation
Rajeev Kumar & Pavan Khetrapal & Manoj Badoni & Sourav Diwania, 2022.
"Evaluating the relative operational performance of wind power plants in Indian electricity generation sector using two-stage model,"
Energy & Environment, , vol. 33(7), pages 1441-1464, November.
Handle:
RePEc:sae:engenv:v:33:y:2022:i:7:p:1441-1464
DOI: 10.1177/0958305X211043531
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