1 resultado para market forecast
em Repositório Científico da Universidade de Évora - Portugal
Filtro por publicador
- Aberystwyth University Repository - Reino Unido (4)
- Aquatic Commons (34)
- Archive of European Integration (88)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (27)
- Aston University Research Archive (1)
- Biblioteca Digital de la Universidad Católica Argentina (2)
- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (3)
- Boston University Digital Common (3)
- Brock University, Canada (7)
- CaltechTHESIS (1)
- Cambridge University Engineering Department Publications Database (33)
- CentAUR: Central Archive University of Reading - UK (51)
- Center for Jewish History Digital Collections (1)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (7)
- Cochin University of Science & Technology (CUSAT), India (14)
- Comissão Econômica para a América Latina e o Caribe (CEPAL) (1)
- CORA - Cork Open Research Archive - University College Cork - Ireland (5)
- Cornell: DigitalCommons@ILR (2)
- Corvinus Research Archive - The institutional repository for the Corvinus University of Budapest (1)
- Deakin Research Online - Australia (6)
- DI-fusion - The institutional repository of Université Libre de Bruxelles (7)
- Digital Commons - Michigan Tech (1)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (6)
- DRUM (Digital Repository at the University of Maryland) (2)
- Duke University (9)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (17)
- Greenwich Academic Literature Archive - UK (1)
- Helda - Digital Repository of University of Helsinki (44)
- Indian Institute of Science - Bangalore - Índia (8)
- Instituto Politécnico do Porto, Portugal (31)
- Massachusetts Institute of Technology (5)
- Ministerio de Cultura, Spain (4)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (6)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (143)
- Queensland University of Technology - ePrints Archive (227)
- ReCiL - Repositório Científico Lusófona - Grupo Lusófona, Portugal (1)
- Repositório Científico da Universidade de Évora - Portugal (1)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (8)
- Repositório digital da Fundação Getúlio Vargas - FGV (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (1)
- Repositorio Institucional de la Universidad Pública de Navarra - Espanha (2)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (66)
- SAPIENTIA - Universidade do Algarve - Portugal (2)
- School of Medicine, Washington University, United States (1)
- The Scholarly Commons | School of Hotel Administration; Cornell University Research (1)
- Universidad del Rosario, Colombia (26)
- Universidad Politécnica de Madrid (1)
- Universitat de Girona, Spain (3)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (9)
- Université de Lausanne, Switzerland (1)
- Université de Montréal, Canada (26)
- University of Michigan (3)
- University of Queensland eSpace - Australia (1)
- University of Southampton, United Kingdom (21)
- WestminsterResearch - UK (14)
- Worcester Research and Publications - Worcester Research and Publications - UK (3)
Resumo:
This paper deals with the problem of coordinated trading of wind and photovoltaic systems in order to find the optimal bid to submit in a pool-based electricity market. The coordination of wind and photovoltaic systems presents uncertainties not only due to electricity market prices, but also with wind and photovoltaic power forecast. Electricity markets are characterized by financial penalties in case of deficit or excess of generation. So, the aim o this work is to reduce these financial penalties and maximize the expected profit of the power producer. The problem is formulated as a stochastic linear programming problem. The proposed approach is validated with real data of pool-based electricity market of Iberian Peninsula.