Estimating electricity forward prices in Brazil with mixed conditional value-at-risk preference

Published: 31 August 2021| Version 3 | DOI: 10.17632/fxgdtkv6zp.3


Authors: Felipe Van de Sande Araujo, Cristina Spineti Luz, Leonardo Lima Gomes, Luiz Eduardo Teixeira Brandão The files provided here are the calculations for the paper with the same title. They are organized in the following way: Data - contain datasets of forecasted spot prices for electricity in SE/CO region of Brazil for the year 2020 or 2021, as well as estimated forward price for electricity for the same years. This data is loaded by the R scripts. Plots - contain the plots generated by these scripts. The main level contain the scripts that can be executed, provided the data is organized in the same structure as this repository. All code was developed for the article. Paper Abstract: Despite its continental size and integrated electrical system, Brazil does not have an exchange for trading forward and futures contracts for electricity. Thus, price information for long-term contracts is often obtained through market research and expert opinions, which is often time-consuming and results in disparate expectations. This article proposes a new approach to estimate forward prices for electricity in the Brazilian energy market using an equilibrium framework between two representative agents negotiating bilateral contracts, and having the agents’ risk aversion determined by mixed conditional value-at-risk preferences. Once the framework is calibrated it can provide forward price estimations using expected spot prices series obtained by the system operator’s model (NEWAVE-DECOMP). This approach can provide market agents with a single common source for forward prices, which offers more transparency and can be useful for markets with low liquidity. Keywords: electricity forward prices, bilateral contracts, multi-agent equilibrium, mixed CVaR, Optimization.


Steps to reproduce

The code was last run in R 4.0.3 All R files must be run in the working directory and the folder structure must be preserved. Libraries required for chart generation: plotly (for interactive and non-interactive plots) and viridis (optimized for colorblind visualization support).


Pontificia Universidade Catolica do Rio de Janeiro


Electricity Market, Brazil, Applied Economics