Published July 20, 2022
| Version v1
Conference paper
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Preliminary Results of Advanced Heuristic Optimization in the Risk-based Energy Scheduling Competition
- 1. GECAD Research Center, Polytechnic of Porto Porto, Portugal
Description
In this paper, multiple evolutionary algorithms are applied to solve an energy resource management problem in the day-ahead context involving a risk-based analysis corresponding to the proposed 2022 competition on evolutionary computation. We test numerous evolutionary algorithms for a risk-averse day-ahead operation to show preliminary results for the competition. We use evolutionary computation to follow the competition guidelines. Results show that the HyDE algorithm obtains a better solution with lesser costs when compared to the other tested algorithm due to the minimization of worst-scenario impact.
Notes
This research has received funding from FEDER funds through the Operational Programme for Competitiveness and Internationalization (COMPETE 2020), under Project POCI-01-0145-FEDER-028983; by National Funds through the FCT Portuguese Foundation for Science and Technology, under Projects PTDC/EEI-EEE/28983/2017 (CENERGETIC), CEECIND/02814/2017, UIDB/000760/2020, and UIDP/00760/2020.
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Additional details
Funding
- PTDC/EEI-EEE/28983/2017 – Coordinated energy resource management under uncertainty considering electric vehicles and demand flexibility in distribution networks PTDC/EEI-EEE/28983/2017
- Fundação para a Ciência e Tecnologia
- CEECIND/02814/2017/CP1417/CT0002 – Not available CEECIND/02814/2017/CP1417/CT0002
- Fundação para a Ciência e Tecnologia
- UIDP/00760/2020 – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development UIDP/00760/2020
- Fundação para a Ciência e Tecnologia