<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The Present study focuses on the impact of various factors on the growth of wind power generation in seven most wind energy prone states of India, that contain 97 % of India’s total wind power potential. The impact of state-wise policy parameters Feed-in Tariff (FIT) rate, Renewable Purchase Obligations (RPO) and Power Purchase Agreement (PPA) are evaluated in terms of aggregate policy indices that indicate the likelihood of wind power deployment in that state, through multivariate statistical analysis. The wind energy technology with reference to wind turbine specific policies, scaling of the project, the impact of hybrid policy, grid-related technological advancements and the improvement of capacity utilization factor (CUF) are discussed. Further, the impact of per capita net domestic product (PCNDP) and power demand-supply scenario are assessed. It was found that these two factors are non-influential on wind power growth. The outcome of the present study is that aggregate policy indices, captive/third party use of feasibility, presence of repowering policy, actual CUF obtained at the location, delay in cash flow and total available power potential are the factors that significantly influence the growth of cumulative installed capacity. This study provides an insight for policymakers for a quantitative assessment of the existing policies along with other factors and assists the project developers to compare and identify suitable locations for wind power projects in the near future. The exchange rate of 1 USD ($) = 69.38 INR (₹) has been taken throughout the manuscript.</p></abstract>

The Present study focuses on the impact of various factors on the growth of wind power generation in seven most wind energy prone states of India, that contain 97 % of India’s total wind power potential. The impact of state-wise policy parameters Feed-in Tariff (FIT) rate, Renewable Purchase Obligations (RPO) and Power Purchase Agreement (PPA) are evaluated in terms of aggregate policy indices that indicate the likelihood of wind power deployment in that state, through multivariate statistical analysis. The wind energy technology with reference to wind turbine specific policies, scaling of the project, the impact of hybrid policy, grid-related technological advancements and the improvement of capacity utilization factor (CUF) are discussed. Further, the impact of per capita net domestic product (PCNDP) and power demand-supply scenario are assessed. It was found that these two factors are non-influential on wind power growth. The outcome of the present study is that aggregate policy indices, captive/third party use of feasibility, presence of repowering policy, actual CUF obtained at the location, delay in cash flow and total available power potential are the factors that significantly influence the growth of cumulative installed capacity. This study provides an insight for policymakers for a quantitative assessment of the existing policies along with other factors and assists the project developers to compare and identify suitable locations for wind power projects in the near future. The exchange rate of 1 USD ($) = 69.38 INR (₹) has been taken throughout the manuscript.

Assessment of Factors Affecting Onshore Wind Power Deployment in India

Environmental and Climate Technologies

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Assessment of Factors Affecting Onshore Wind Power Deployment in India"}

The Present study focuses on the impact of various factors on the growth of wind power generation in seven most wind energy prone states of India, that contain...

Assessment of Factors Affecting Onshore Wind Power Deployment in India

Data publikacji: 06 kwi 2020

Zakres stron: 185 - 208

DOI: https://doi.org/10.2478/rtuect-2020-0012

Słowa kluczowe
Multivariate statistical analysis, policy, power generation, renewable energy, wind energy

© 2020 Alok Das et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Assessment of Factors Affecting Onshore Wind Power Deployment in India

Data publikacji: 06 kwi 2020

Zakres stron: 185 - 208

DOI: https://doi.org/10.2478/rtuect-2020-0012

Słowa kluczoweMultivariate statistical analysis, policy, power generation, renewable energy, wind energy

© 2020 Alok Das et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Multivariate statistical analysis, policy, power generation, renewable energy, wind energy