Assessment of Factors Affecting Onshore Wind Power Deployment in India

Abstract

<jats:title>Abstract</jats:title><jats: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.</jats:p>

Wind Power Forecasting by the BP Neural Network with the Support of Machine Learning

“…Wind power is affected by wind [9]. e wind in nature is related to meteorological factors such as temperature, air pressure, and humidity.…”

Energy, exergy, economic, environmental, advanced exergy and exergoeconomic (extended exergy) analysis of hybrid wind-solar power plant

“…Pr government policies on the economics of the power projects which leads to lower system costs 31 has not been evaluated so far for the hybrid energy system. In order to bridge the research gap, the objective of the present study is to apply instantaneous multidimensional 6E analysis (energy, exergy, economic, environmental, advance exergy and exergoeconomic (extended exergy)) on a 5.6 MW HWSES having equal wind and solar installation capacity (2.8 MW each for wind turbine and solar PV) (Figure 1).…”

“…NPV indicates the net value of the energy project at the end of the project lifetime, whereas the LCOE is the cost of energy generation per unit of power generation. 45 Both NPV and LCOE are based on the net cash flow approach; therefore, any one of these parameters is sufficient for the representation of the system economics. The expression of LCOE remains the same for any kind of power generation system as given in Table 3.…”

“…The expression of LCOE remains the same for any kind of power generation system as given in Table 3. 45 The particulars used for the LCOE evaluation are tabulated in Table 7. Indian government provides Accelerated depreciation (AD) policy to RE projects, which allows the developers to depreciate 40.0% of the loan amount during the first year of operation.…”

A Multi-Factorial Review of Repowering Wind Generation Strategies

“…Moreover, it concluded that 1/4 of the wind power plants installed by then could not withstand power outages, subsequently creating an excellent opportunity for the wind repowering market. Recently, in 2020, Das et al analyzed the main factors that were influencing the onshore wind energy deployment in India, being the presence of repowering policy one of them [95]. However, in that country, only four states have such type of politics.…”