Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach
Main Author: | |
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Publication Date: | 2016 |
Other Authors: | |
Format: | Book |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | https://repositorio-aberto.up.pt/handle/10216/84384 |
Summary: | The restructuring of power systems with the introduction of electricity markets and decentralized structures increased the number of participating entities. This is particularly true in generation and retailing which are now provided under competition. Accordingly, it is important to develop models to simulate the behavior of these agents and to optimize their participation in electricity markets. Among them, it is essential to adequately model generation agents namely in countries having a large share of hydro stations. This paper describes an agent-based approach to model the day-ahead electricity market having a particular emphasis on hydro generation. Apart from the characterization of the agents, the paper details the introduction of the Q-Learning algorithm in the model as a way to enhance the performance of generation agents. This paper also presents some preliminary results taking the Portuguese generation system as an example. |
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Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approachEngenharia electrotécnica, Engenharia electrotécnica, electrónica e informáticaElectrical engineering, Electrical engineering, Electronic engineering, Information engineeringThe restructuring of power systems with the introduction of electricity markets and decentralized structures increased the number of participating entities. This is particularly true in generation and retailing which are now provided under competition. Accordingly, it is important to develop models to simulate the behavior of these agents and to optimize their participation in electricity markets. Among them, it is essential to adequately model generation agents namely in countries having a large share of hydro stations. This paper describes an agent-based approach to model the day-ahead electricity market having a particular emphasis on hydro generation. Apart from the characterization of the agents, the paper details the introduction of the Q-Learning algorithm in the model as a way to enhance the performance of generation agents. This paper also presents some preliminary results taking the Portuguese generation system as an example.2016-06-062016-06-06T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://repositorio-aberto.up.pt/handle/10216/84384eng10.1109/EEM.2016.7521334João Tomé SaraivaJosé Carlos Sousainfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-27T16:44:25Zoai:repositorio-aberto.up.pt:10216/84384Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T21:51:42.221397Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach |
title |
Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach |
spellingShingle |
Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach João Tomé Saraiva Engenharia electrotécnica, Engenharia electrotécnica, electrónica e informática Electrical engineering, Electrical engineering, Electronic engineering, Information engineering |
title_short |
Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach |
title_full |
Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach |
title_fullStr |
Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach |
title_full_unstemmed |
Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach |
title_sort |
Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach |
author |
João Tomé Saraiva |
author_facet |
João Tomé Saraiva José Carlos Sousa |
author_role |
author |
author2 |
José Carlos Sousa |
author2_role |
author |
dc.contributor.author.fl_str_mv |
João Tomé Saraiva José Carlos Sousa |
dc.subject.por.fl_str_mv |
Engenharia electrotécnica, Engenharia electrotécnica, electrónica e informática Electrical engineering, Electrical engineering, Electronic engineering, Information engineering |
topic |
Engenharia electrotécnica, Engenharia electrotécnica, electrónica e informática Electrical engineering, Electrical engineering, Electronic engineering, Information engineering |
description |
The restructuring of power systems with the introduction of electricity markets and decentralized structures increased the number of participating entities. This is particularly true in generation and retailing which are now provided under competition. Accordingly, it is important to develop models to simulate the behavior of these agents and to optimize their participation in electricity markets. Among them, it is essential to adequately model generation agents namely in countries having a large share of hydro stations. This paper describes an agent-based approach to model the day-ahead electricity market having a particular emphasis on hydro generation. Apart from the characterization of the agents, the paper details the introduction of the Q-Learning algorithm in the model as a way to enhance the performance of generation agents. This paper also presents some preliminary results taking the Portuguese generation system as an example. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-06-06 2016-06-06T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/book |
format |
book |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://repositorio-aberto.up.pt/handle/10216/84384 |
url |
https://repositorio-aberto.up.pt/handle/10216/84384 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1109/EEM.2016.7521334 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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