Two Agent Model of Forward Electricity Prices in Brazil with Generalized Extended CVaR Preferences
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. The sensitivity analysis uses an interactive plotly widget that can take a while to fully load. 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. This article proposes a simple yet efficient approach to estimate the forward price of electricity in the Brazilian energy market. The model is based on the equilibrium between two representative agents negotiating bilateral contracts where the agents’ risk aversion is derived from the utility functions related to the Generalized Extended CVaR Preference. This model is comprehensive and can be applied to all agents participating in the electricity futures transaction independent of whether they are directly involved in the production chain or simply carry speculative positions. Our results indicate that the model’s forecasted prices, which are based on the participants' expected behavior, can be used as an indicator for the forward price of electricity, providing more transparency and security for the participants in this market. Key-words: Forward curve, Forward Bilateral Contracts, Multi-Agent Equilibrium, 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).