Wind power feasibility analysis under uncertainty in the Brazilian electricity market

Investors must be able to plan and analyze their investments in order to optimize decisions and turn them into profits associated with a particular project. Since electricity producers in the Brazilian electric power system are exposed to a short-term market, the goal of this paper is to propose a framework for investment analysis capable of encompassing different uncertainties and possibilities for wind power generators in a regulated market, characterized by auctions. In order to reach the proposed objective we employ a simulation technique which allows modeling cash flows considering uncertainties in variables related to project financial premises, electricity generation and producer exposure to the short-term market. For such goal, this study presents a new approach for investment analysis that allows the identification of the main uncertainty parameters and risks associated to this class of projects in the Brazilian electricity market. We also employ the Value at Risk technique to perform a risk management analysis in such context.

[1]  Zhongren Nan,et al.  Risk assessment of water quality using Monte Carlo simulation and artificial neural network method. , 2013, Journal of environmental management.

[2]  Erwin Schmid,et al.  Where the wind blows: Assessing the effect of fixed and premium based feed-in tariffs on the spatial diversification of wind turbines , 2013 .

[3]  Philippe Artzner,et al.  Coherent Measures of Risk , 1999 .

[4]  Antonio Colmenar-Santos,et al.  Repowering: An actual possibility for wind energy in Spain in a new scenario without feed-in-tariffs , 2015 .

[5]  B. Safari,et al.  A statistical investigation of wind characteristics and wind energy potential based on the Weibull and Rayleigh models in Rwanda , 2010 .

[6]  Jui-Cheng Hung,et al.  Estimation of value-at-risk for energy commodities via fat-tailed GARCH models , 2008 .

[7]  Önder Güler,et al.  Calculation of Wind Energy Potential and Economic Analysis by Using Weibull Distribution—A Case Study from Turkey. Part 2: Economic Analysis , 2009 .

[8]  W. R. Hargraves,et al.  Methods for Estimating Wind Speed Frequency Distributions. , 1978 .

[9]  Yasuhiro Yamai,et al.  Value-at-risk versus expected shortfall: A practical perspective , 2005 .

[10]  Claudius Holdermann,et al.  Distributed photovoltaic generation in Brazil: An economic viability analysis of small-scale photovoltaic systems in the residential and commercial sectors , 2014 .

[11]  Laura Castro-Santos,et al.  Economic feasibility of floating offshore wind farms , 2016 .

[12]  Janardan Rohatgi,et al.  Development of the wind power in Brazil: Political, social and technical issues , 2014 .

[13]  Daniel G. Williams.  Scenario simulations do not yield results stochastically consistent with alternative Monte Carlo results: U.S. nuclear plant decommissioning funding adequacy (2000) , 2007 .

[14]  Haitham Saad Mohamed Ramadan,et al.  Wind energy farm sizing and resource assessment for optimal energy yield in Sinai Peninsula, Egypt , 2017 .

[15]  Özgür Yildiz,et al.  Economic risk analysis of decentralized renewable energy infrastructures – A Monte Carlo Simulation approach , 2015 .

[16]  C. Batlle,et al.  Electricity auctions in South America: Towards convergence of system adequacy and RES-E support , 2014 .

[17]  Fernando Ramos Martins,et al.  Enhancing information for solar and wind energy technology deployment in Brazil , 2011 .

[18]  Maurício Dziedzic,et al.  The importance of clean development mechanism for small hydro power plants , 2013 .

[19]  L. L. Gomes,et al.  Can the regulated market help foster a free market for wind energy in Brazil , 2014 .

[20]  Odilon A.Camargo do Amarante,et al.  Atlas do potencial eolico brasileiro , 2001 .

[21]  María Isabel Blanco.  The economics of wind energy , 2009 .

[22]  S. Akdağ,et al.  Calculation of Wind Energy Potential and Economic Analysis by Using Weibull Distribution—A Case Study from Turkey. Part 1: Determination of Weibull Parameters , 2009 .

[23]  R. Madlener,et al.  Economics of Small Wind Power Plants in Urban Settings: An Empirical Investigation for Germany , 2013 .

[24]  Alexandre Szklo,et al.  Incentive policies for promoting wind power production in Brazil: Scenarios for the Alternative Energy Sources Incentive Program (PROINFA) under the New Brazilian electric power sector regulation , 2008 .

[25]  M. Ertürk.  The evaluation of feed-in tariff regulation of Turkey for onshore wind energy based on the economic analysis , 2012 .

[26]  J. Hair.  Multivariate data analysis , 1972 .

[27]  Hedayat Saboori,et al.  Stochastic risk-averse coordinated scheduling of grid integrated energy storage units in transmission constrained wind-thermal systems within a conditional value-at-risk framework , 2016 .

[28]  Pedro Linares,et al.  Back to the future? Rethinking auctions for renewable electricity support , 2014 .

[29]  I. Azevedo,et al.  Economic analysis of the profitability of existing wind parks in Portugal , 2014 .

[30]  Wai Ming Cheung,et al.  Development of a quantitative analysis system for greener and economically sustainable wind farms , 2016 .

[31]  Ryan D. Walters,et al.  Examining the financial performance of micro-generation wind projects and the subsidy effect of feed-in tariffs for urban locations in the United Kingdom , 2011 .

[32]  Ilias P. Tatsiopoulos,et al.  Holistic investment assessment: optimization, risk appraisal and decision making , 2009 .

[33]  Marcio Giannini Pereira,et al.  The renewable energy market in Brazil: Current status and potential , 2012 .

[34]  Temitope Raphael Ayodele,et al.  Wind power utilization assessment and economic analysis of wind turbines across fifteen locations in the six geographical zones of Nigeria , 2016 .

[35]  Chen-Ching Liu,et al.  Risk assessment in energy trading , 2003 .

[36]  R. Kelman,et al.  Allocation of Firm-Energy Rights Among Hydro Plants: An Aumann–Shapley Approach , 2009, IEEE Transactions on Power Systems.

[37]  Ulrike Wachsmann,et al.  Wind power in Brazil—transition using German experience , 2003 .

[38]  Philippe Jorion,et al.  How Informative are Value-at-Risk Disclosures? , 2002 .

[39]  Nasrudin Abd Rahim,et al.  A review on global solar energy policy , 2011 .

[40]  Paulo Rotela Junior,et al.  Wind power generation: An impact analysis of incentive strategies for cleaner energy provision in Brazil , 2016 .

[41]  Cunbin Li,et al.  The investment risk analysis of wind power project in China , 2013 .

[42]  H. C. Peterson,et al.  Governance strategies and transaction costs in a renovated electricity market , 2015 .

[43]  Saad Mekhilef,et al.  Progress and recent trends of wind energy technology , 2013 .

[44]  Marcio Giannini Pereira,et al.  Wind energy in Brazil: From the power sector's expansion crisis model to the favorable environment , 2013 .

[45]  Germán Martínez Montes,et al.  The applicability of computer simulation using Monte Carlo techniques in windfarm profitability analysis , 2011 .