Optimization of Multiple Electricity Markets Participation Using Evolutionary PSO
| Main Authors: | Ricardo Faia, Tiago Pinto, Zita Vale, Juan Manuel Corchado |
|---|---|
| Format: | Proceeding Journal |
| Bahasa: | eng |
| Terbitan: |
, 2018
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/1465879 |
Daftar Isi:
- Electric power systems have undergone major changes in recent years. Electricity markets are one of the sectors that has been most affected by these changes. Electricity market design is being updated in order to support efficient operation and investments incentives. However, the development of efficient rules is neither easy nor guaranteed. This paper addresses the simulation of multi-participation in electric energy markets. The purpose of this simulation is to offer solutions to electricity market players, in order to support their decisions on future participation situations. For this, artificial intelligence techniques will be used, namely for forecasting and optimization processes. In specific, an optimization approach based on Evolutionary Particle Swarm Optimization (EPSO) is proposed. The achieved results are compared to those of a deterministic resolution method, and of the classical Particle Swarm Optimization (PSO). Results show that the proposed approach is able to achieve higher mean and maximum objective function results than the classical PSO, with a smaller standard deviation. The execution time is higher than using PSO, but still very fast when compared the deterministic method. The case study is based on real data from the Iberian electricity market.
- This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO) and No 703689 (project ADAPT) and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013.