The objective of this paper is to verify the robustness of the Least Square Monte Carlo and Grant, Vora & Weeks methods when used to determine the incremental payoff of the carbon market for renewable electricity generation projects, considering that the behavior of the price of Certified Emission Reductions, otherwise known as Carbon Credits, may be modeled using a jump-diffusion process. In addition, this paper analyses particular characteristics, such as absence of monotonicity, found in trigger curves obtained through use of the Grant, Vora & Weeks method to valuate these types of project.

Este trabalho tem por objetivo avaliar a robustez dos métodos de Grant, Vora & Weeks e dos Mínimos Quadrados quando aplicados na avaliação de projetos de geração de energia eletrica a partir de fontes renovavéis desenvolvidos no ambito do Mecanismo de Desenvolvimento Limpo do Protocolo de Quioto. Em primeiro lugar, a metodologia proposta consiste em utilizar o modelo NEWAVE para estabelecer cenários hidrológicos de despacho para as usinas conectadas ao sistema interligado nacional. Em seguida, baseado no escopo da metodologia ACM0002, considera-se a incerteza associada a evolução temporal da linha de base do projeto. Finalmente, o valor incremental do mercado de carbono e estimado utilizando-se a Teoria das Opções Reais. Para tanto os métodos numericos citados anteriormente são utilizados sob a premissa de que o preço do crédito de carbono se comporta de forma aleatoria segundo as premissas de um Movimento Geometrico Browniano

The objective of this paper is to evaluate the robustness of the Grant, Vora & Weeks and Least Square Monte Carlo Methods when used to evaluate renewable generation projects developed according to the rules of the Kyoto Protocol Clean Development Mechanism. The proposed methodology makes use of the NEWAVE model in order to generate futures dispatch sequences for all generators connected to the Brazilian grid. After that, based on the methodology ACM0002, the uncertainty associated to the time evolution of the project's baseline is considered. Finally, the carbon market' incremental payoff is estimated using the Real Options Approach. In order to do that, the numerical methods previously mentioned are used under the assumption that the behavior of the carbon price is random and that the price follows a Geometric Brownian Motion