Daywes Pinheiro Neto

Methodology of Investment Risk Analysis for Wind Power Plants in the Brazilian Free Market

Abstract Despite the strong growth of wind power in the world, it is considered a high risk investment due to variability and unpredictability of wind speed. If the energy trade occurs in the free market, there is another risk factor that is the short-term price. This study proposes a methodology of investment risk analysis for wind power plants using innovative stochastic models to generate synthetic time series of wind speed and short-term price. The simulation is implemented using the Monte Carlo method associated with a Cholesky decomposition. The cashflows gross revenue is obtained through an energy trading model for the Free Contracting Environment (FCE) in Brazil. The investment analysis is based on probability distribution of Net Present Value (NPV) of the power plants cash flow, as well as the Value at Risk (VaR) and the Conditional Value at Risk (CVaR). A case study was performed for Natal city of Rio Grande do Norte (RN) state in Brazil, and the results indicated the economic viability of the power plant. A sensitivity analysis is developed considering important parameters of the modeling, and its results provide information to the decision-making process.

Investment risk analysis for photovoltaic power plant in the free contracting environment

This research work presents a methodology for investment risk analysis in a photovoltaic power plant. Stochastic modeling are developed for the variables solar irradiance, photovoltaic panel temperature and price of electricity in the Brazilian spot market. A case study is presented to validate the applicability of the methodology. The method is developed considering various characteristics of the Brazilian market, specifically for the Free Contracting Environment, but can be adapted to other markets.

Technical and economic feasibility of using microturbines for the energy utilization of landfill gas

This article proposes an analysis of the technical and economic feasibility of a Clean Development Mechanism (CDM) project for the generation of electricity through the use of biogas from landfill through the use of microturbine technology. In order to obtain the baseline and project scenarios, the methodology ACM-0001 was used, which is specific for the use of landfill biogas. For the economic viability analysis, the Net Present Value (NPV), the Modified Internal Rate of Return (MIRR) and the Payback method were used. After the results, the methods of economic analysis indicated that its CDM project with microturbine is economically viable.

Investment risk analysis for eolic power plants in the free contracting environment

This research work presents a methodology for investment risk analysis for eolic power plants. A stochastic modelling was developed for the variables Wind Speed and Price Settlement of Differences (PSD), with the aim of analyzing cash flow during a power plants lifespan. Simulated scenarios have been created with the Monte Carlo Method to analyze the random variables involved in the process. The investment analysis is based on the assessment of the probability distribution of the Net Present Value (NPV) and of the Modified Internal Rate of Return (MIRR) for the power plants cash flow, as well as the Value at Risk (VaR) and the Conditional Value at Risk (CVaR). This research work presents a case study to verify the applicability of this methodology.