1 resultado para Nasir-Mohammed, Sultan of Egypt, 1284-1341.
em Instituto Politécnico do Porto, Portugal
Filtro por publicador
- Academic Research Repository at Institute of Developing Economies (4)
- Adam Mickiewicz University Repository (1)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (5)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (1)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (7)
- Archive of European Integration (53)
- Aston University Research Archive (13)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (16)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (18)
- Biblioteca Virtual del Sistema Sanitario Público de Andalucía (BV-SSPA), Junta de Andalucía. Consejería de Salud y Bienestar Social, Spain (2)
- Biodiversity Heritage Library, United States (5)
- Bioline International (2)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (89)
- Brock University, Canada (4)
- Bucknell University Digital Commons - Pensilvania - USA (6)
- CentAUR: Central Archive University of Reading - UK (35)
- Cochin University of Science & Technology (CUSAT), India (53)
- Coffee Science - Universidade Federal de Lavras (1)
- Comissão Econômica para a América Latina e o Caribe (CEPAL) (3)
- Consorci de Serveis Universitaris de Catalunya (CSUC), Spain (12)
- CUNY Academic Works (1)
- Dalarna University College Electronic Archive (4)
- Department of Computer Science E-Repository - King's College London, Strand, London (2)
- Digital Commons - Michigan Tech (4)
- Digital Commons - Montana Tech (1)
- Digital Commons @ DU | University of Denver Research (1)
- Digital Commons at Florida International University (1)
- Digital Knowledge Repository of Central Drug Research Institute (1)
- DigitalCommons@The Texas Medical Center (12)
- Digitale Sammlungen - Goethe-Universität Frankfurt am Main (3)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (6)
- Duke University (1)
- Gallica, Bibliotheque Numerique - Bibliothèque nationale de France (French National Library) (BnF), France (1)
- Harvard University (8)
- Helvia: Repositorio Institucional de la Universidad de Córdoba (1)
- Instituto Politécnico do Porto, Portugal (1)
- Martin Luther Universitat Halle Wittenberg, Germany (1)
- Memoria Académica - FaHCE, UNLP - Argentina (6)
- Ministerio de Cultura, Spain (1)
- National Center for Biotechnology Information - NCBI (3)
- Nottingham eTheses (1)
- Ohio University (1)
- Portal de Revistas Científicas Complutenses - Espanha (2)
- Publishing Network for Geoscientific & Environmental Data (224)
- QSpace: Queen's University - Canada (1)
- RepoCLACAI - Consorcio Latinoamericano Contra el Aborto Inseguro (1)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (2)
- Repositório da Produção Científica e Intelectual da Unicamp (3)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (27)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (2)
- School of Medicine, Washington University, United States (4)
- Scielo Saúde Pública - SP (25)
- South Carolina State Documents Depository (2)
- Universidad del Rosario, Colombia (10)
- Universidad Politécnica de Madrid (2)
- Universidade Complutense de Madrid (2)
- Universidade do Minho (1)
- Universidade Federal do Rio Grande do Norte (UFRN) (1)
- Universidade Metodista de São Paulo (3)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (7)
- Université de Lausanne, Switzerland (30)
- Université de Montréal, Canada (9)
- University of Michigan (193)
- University of Queensland eSpace - Australia (8)
- WestminsterResearch - UK (1)
Resumo:
The paper proposes a methodology to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The proposed methodology is based on statistical failure and repair data of distribution components and it uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A mixed integer nonlinear programming optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.