An Ad-Hoc Initial Solution Heuristic for Metaheuristic Optimization of Energy Market Participation Portfolios
1
Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD), Institute of Engineering, Polytechnic of Porto (ISEP/IPP), Rua Dr. António Bernardino de Almeida, 431, 4200-072 Porto, Portugal
2
Bioinformatics, Intelligent Systems and Educational Technology (BISITE) Research Centre, University of Salamanca, Calle Espejo, s/n, 37007 Salamanca, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Gianfranco Chicco
Energies 2017, 10(7), 883; https://doi.org/10.3390/en10070883
Received: 2 February 2017
/
Revised: 19 June 2017
/
Accepted: 26 June 2017
/
Published: 30 June 2017
The deregulation of the electricity sector has culminated in the introduction of competitive markets. In addition, the emergence of new forms of electric energy production, namely the production of renewable energy, has brought additional changes in electricity market operation. Renewable energy has significant advantages, but at the cost of an intermittent character. The generation variability adds new challenges for negotiating players, as they have to deal with a new level of uncertainty. In order to assist players in their decisions, decision support tools enabling assisting players in their negotiations are crucial. Artificial intelligence techniques play an important role in this decision support, as they can provide valuable results in rather small execution times, namely regarding the problem of optimizing the electricity markets participation portfolio. This paper proposes a heuristic method that provides an initial solution that allows metaheuristic techniques to improve their results through a good initialization of the optimization process. Results show that by using the proposed heuristic, multiple metaheuristic optimization methods are able to improve their solutions in a faster execution time, thus providing a valuable contribution for players support in energy markets negotiations.
View Full-Text
Keywords:
artificial intelligence; decision support; electricity markets; initial solution heuristic; metaheuristic optimization; portfolio optimization
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Faia, R.; Pinto, T.; Vale, Z.; Corchado, J.M. An Ad-Hoc Initial Solution Heuristic for Metaheuristic Optimization of Energy Market Participation Portfolios. Energies 2017, 10, 883. https://doi.org/10.3390/en10070883
AMA Style
Faia R, Pinto T, Vale Z, Corchado JM. An Ad-Hoc Initial Solution Heuristic for Metaheuristic Optimization of Energy Market Participation Portfolios. Energies. 2017; 10(7):883. https://doi.org/10.3390/en10070883
Chicago/Turabian StyleFaia, Ricardo, Tiago Pinto, Zita Vale, and Juan M. Corchado. 2017. "An Ad-Hoc Initial Solution Heuristic for Metaheuristic Optimization of Energy Market Participation Portfolios" Energies 10, no. 7: 883. https://doi.org/10.3390/en10070883
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
