A Volatility Index for Bilateral Electricity Contracting Auctions



Electricity auctions, ARIMA, Metaheuristics, Time Series, MIBEL


The use of electricity auctions in daily and intraday trading is one of the most common means of trading on electricity exchanges. Auctions are carried out aiming to reach a marginal price that will be charged for all agents involved. The identification of appropriate moments for placing bids interests consumers and generators, as negotiated demand is directly related to the marginal price established at the end of each auction. In the stock market several indexes assist investors in decision making on operations. However, energy auctions still lack this type of tool. In this context, this paper presents an index proposal based on aggregate supply and demand curves. Machine learning models and time series statistics are employed to predict bid value volatility trends. The experiments used real data from a 958 bid auction promoted by the Iberian Energy Market Operator  (Operador del Mercado Ibérico de Energia - OMIE), the stock exchange responsible for the spot market in Spain and Portugal. Based on the results, it was possible to identify moments in which the parties involved in the auction chose to compromise on bid values with specification of the magnitude of these concessions.


Download data is not yet available.

Author Biographies

Ciniro Aparecido Leite Nametala, University of São Paulo

Ciniro Nametala is a PhD student in Electrical Engineering at University of São Paulo (USP, Brazil). He has previously received a B.Sc. in System Analysis and Development from the Federal Institute of Education, Science and Technology of Minas Gerais (IFMG, Brazil - 2007), a specialist diploma in Software Engineering of Federal University of Lavras (UFLA, Brazil - 2009), and a M.Sc in Electrical Engineering at Federal University of Minas Gerais (UFMG, Brazil - 2015). He has experience in Applied Computer Science, Computer Systems Modelling, Computing Teachs and Public Information Technology Management. Ciniro has worked as an IT technician, as the Information Systems coordinator, and as director of IT at the central administration of the Federal Institute of Minas Gerais (IFMG), besides joining several committees, councils and work commissions in the organizations/campi in which he worked. He is a certified professions by the international associations EXIN and ISACA in frameworks ITIL® V3 and COBIT® 4.1. He was also member of the Operational Research and Complex Systems Laboratory (ORCS Lab) of UFMG, today works in the Research Group on Computational Systems (GPSisCom) of IFMG and Electrical Energy Systems Analysis Laboratory (LASSE) of USP. He works as an assistant professor at IFMG - Campus Bambuí, where he teaches Computing lectures to the undergraduate courses in Computer Engineering and System Analysis and Development, as well as to the Computing Technical Course. Ciniro's main interests are multi-objective optimization, artificial neural networks, evolutionary computation and statistics for the analysis of time series. His current research focuses on application of time series analysis, machine learning models and optimization techniques for trading environments related to electricity markets.

Wandry Rodrigues de Faria, University of São Paulo

Wandry Rodrigues de Faria é mestrando em Engenharia Elétrica pela Universidade de São Paulo (USP) e Bacharel em Engenharia Elétrica pelo Instituto Federal de Goiás (IFG). Atualmente é membro do Laboratório de Análise de Sistemas de Energia Elétrica (LASSE) da USP. Tem experiência na área de engenharia elétrica, com ênfase em sistemas elétricos de potência, abordando principalmente planejamento e otimização de sistemas de transmissão e distribuição por meio da aplicação de metaheurísticas.

Benvindo Rodrigues Pereira Júnior, University of São Paulo

Benvindo Rodrigues Pereira Júnior possui grau de bacharel, mestre e doutor em Engenharia Elétrica pela Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP). Atualmente é professor do Departamento de Engenharia Elétrica e Computação da Escola de Engenharia de São Carlos da Universidade de São Paulo (USP) e atua como orientador e pesquisador junto ao Laboratório de Análise de Sistemas de Energia Elétrica (LASEE) da USP. Desenvolve pesquisas nas áreas de Planejamento de Sistemas de Energia Elétrica, atuando principalmente no desenvolvimento de modelos matemáticos e aplicação de técnicas metaheurísticas para planejamento e operação de sistemas de distribuição de energia elétrica.

How to Cite

Aparecido Leite Nametala, C., Rodrigues de Faria, W., & Rodrigues Pereira Júnior, B. (2020). A Volatility Index for Bilateral Electricity Contracting Auctions. IEEE Latin America Transactions, 18(5), 938–946. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/2598