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

Author

Queiroz, A.R. ; Oliveira, F.A. ; Lima, J. W Marangon ; Balestrassi, P.P.

fYear

2007

Firstpage

2029

Lastpage

2034

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.

Keywords

design of experiments; electricity supply industry deregulation; neural nets; optimisation; power engineering computing; risk management; NEWAVE optimization software; agent benefits; artificial neural networks; design of experiments; electricity sector deregulation; electricity spot prices; forecasting methods; investment analysis; operational marginal cost; risk management; Artificial neural networks; Computational modeling; Cost function; Economic forecasting; Electricity supply industry deregulation; Investments; Neural networks; Risk analysis; Risk management; US Department of Energy; Design of Experiments and Artificial Neural Networks; Electricity Prices; Simulation;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Tech, 2007 IEEE Lausanne

Conference_Location

Lausanne

Print_ISBN

978-1-4244-2189-3

Electronic_ISBN

978-1-4244-2190-9

Type

conf

DOI

10.1109/PCT.2007.4538630

Filename

4538630