1 resultado para emissions trading
em Repositório Científico do Instituto Politécnico de Lisboa - Portugal
Filtro por publicador
- Repository Napier (1)
- Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España (7)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (4)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (11)
- Aquatic Commons (1)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (8)
- Archive of European Integration (26)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (6)
- B-Digital - Universidade Fernando Pessoa - Portugal (1)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (7)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (4)
- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (1)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (57)
- Boston University Digital Common (2)
- Brock University, Canada (3)
- Bucknell University Digital Commons - Pensilvania - USA (2)
- CaltechTHESIS (1)
- Cambridge University Engineering Department Publications Database (51)
- CentAUR: Central Archive University of Reading - UK (102)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (63)
- Cochin University of Science & Technology (CUSAT), India (4)
- Comissão Econômica para a América Latina e o Caribe (CEPAL) (10)
- CORA - Cork Open Research Archive - University College Cork - Ireland (2)
- Corvinus Research Archive - The institutional repository for the Corvinus University of Budapest (4)
- CUNY Academic Works (1)
- Dalarna University College Electronic Archive (14)
- DI-fusion - The institutional repository of Université Libre de Bruxelles (1)
- Digital Archives@Colby (2)
- Digital Commons - Michigan Tech (13)
- Digital Commons at Florida International University (2)
- Digital Peer Publishing (1)
- DigitalCommons - The University of Maine Research (1)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (1)
- DRUM (Digital Repository at the University of Maryland) (1)
- Duke University (6)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (25)
- Helda - Digital Repository of University of Helsinki (24)
- Indian Institute of Science - Bangalore - Índia (10)
- Instituto Politécnico do Porto, Portugal (4)
- Nottingham eTheses (1)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (6)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (54)
- Queensland University of Technology - ePrints Archive (205)
- RDBU - Repositório Digital da Biblioteca da Unisinos (1)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (1)
- Repositório digital da Fundação Getúlio Vargas - FGV (27)
- Repositório Digital da Universidade Municipal de São Caetano do Sul - USCS (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (4)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (55)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (9)
- School of Medicine, Washington University, United States (17)
- South Carolina State Documents Depository (1)
- Universidad del Rosario, Colombia (1)
- Universidad Politécnica de Madrid (3)
- Universitat de Girona, Spain (4)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (7)
- Université de Montréal, Canada (7)
- University of Michigan (2)
- WestminsterResearch - UK (9)
- Worcester Research and Publications - Worcester Research and Publications - UK (2)
Resumo:
In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.