1 resultado para energy response
em Repositório Científico do Instituto Politécnico de Lisboa - Portugal
Filtro por publicador
- Repository Napier (1)
- Aberdeen University (14)
- Aberystwyth University Repository - Reino Unido (1)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (3)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (2)
- Aquatic Commons (5)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (3)
- Archive of European Integration (4)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (5)
- Aston University Research Archive (8)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (15)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (7)
- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (1)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (22)
- Brock University, Canada (2)
- Bucknell University Digital Commons - Pensilvania - USA (1)
- CaltechTHESIS (4)
- Cambridge University Engineering Department Publications Database (27)
- CentAUR: Central Archive University of Reading - UK (34)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (21)
- Coffee Science - Universidade Federal de Lavras (1)
- CORA - Cork Open Research Archive - University College Cork - Ireland (5)
- Deakin Research Online - Australia (33)
- Digital Commons - Michigan Tech (4)
- Digital Commons - Montana Tech (1)
- Digital Commons at Florida International University (6)
- DigitalCommons - The University of Maine Research (1)
- DigitalCommons@The Texas Medical Center (4)
- 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 (2)
- Glasgow Theses Service (1)
- Helda - Digital Repository of University of Helsinki (2)
- Illinois Digital Environment for Access to Learning and Scholarship Repository (2)
- Indian Institute of Science - Bangalore - Índia (34)
- Instituto Gulbenkian de Ciência (3)
- Instituto Politécnico de Bragança (1)
- Instituto Politécnico do Porto, Portugal (30)
- National Center for Biotechnology Information - NCBI (8)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (2)
- Publishing Network for Geoscientific & Environmental Data (17)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (34)
- Queensland University of Technology - ePrints Archive (485)
- Repositório Científico da Universidade de Évora - Portugal (4)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (1)
- Repositório Institucional da Universidade Federal de São Paulo - UNIFESP (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (42)
- Repositorio Institucional Universidad de Medellín (1)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (2)
- SAPIENTIA - Universidade do Algarve - Portugal (1)
- Savoirs UdeS : plateforme de diffusion de la production intellectuelle de l’Université de Sherbrooke - Canada (2)
- Scientific Open-access Literature Archive and Repository (1)
- Universidad de Alicante (2)
- Universidad Politécnica de Madrid (17)
- Universidade Complutense de Madrid (3)
- Universidade de Lisboa - Repositório Aberto (3)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (1)
- Université de Lausanne, Switzerland (1)
- University of Michigan (10)
- University of Queensland eSpace - Australia (5)
- University of Washington (2)
Resumo:
This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers' consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed. (C) 2016 Elsevier Ltd. All rights reserved.