Simulating Electricity Spot Prices in Brazil Using Neural Network and Design of Experiments

Abstract

The electricity price has been one of the most important variables since the introduction of deregulation on the electricity sector. On this way, efficient forecasting methods of spot prices have become crucial to maximize the agent benefits. In Brazil the electricity price is based on the marginal cost provided by an optimization software (NEWAVE). Forecasting the operational marginal cost (OMC) and its volatility has been one big problem in the Brazilian market because of the computational time taken by this software. This work presents a fast and efficient model to simulate the OMC using DOE (design of experiments) and ANN (artificial neural networks) techniques. The paper proved that the combined techniques provided a promising result and may be applied to risk management and investment analysis.