Carlos Augusto Santos Silva
Carlos Augusto Santos Silva
IN+, LARSyS, IST, Universidade de Lisboa
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The impact of demand side management strategies in the penetration of renewable electricity
A Pina, C Silva, P Ferrão
Energy 41 (1), 128-137, 2012
Design and implementation of hybrid renewable energy systems on micro-communities: A review on case studies
D Neves, CA Silva, S Connors
Renewable and Sustainable Energy Reviews 31, 935-946, 2014
High-resolution modeling framework for planning electricity systems with high penetration of renewables
A Pina, CA Silva, P Ferrão
Applied Energy 112, 215-223, 2013
The relevance of the energy resource dynamics in the mid/long-term energy planning models
G Haydt, V Leal, A Pina, CA Silva
Renewable energy 36 (11), 3068-3074, 2011
Modeling hourly electricity dynamics for policy making in long-term scenarios
A Pina, C Silva, P Ferrão
Energy Policy 39 (9), 4692-4702, 2011
Baseline mercury and zinc concentrations in terrestrial and coastal organisms of Admiralty Bay, Antarctica
IR Dos Santos, EV Silva-Filho, C Schaefer, SM Sella, CA Silva, V Gomes, ...
Environmental Pollution 140 (2), 304-311, 2006
Comparing demand response and battery storage to optimize self-consumption in PV systems
G Lorenzi, CAS Silva
Applied Energy 180, 524–535, 2016
Distributed supply chain management using ant colony optimization
CA Silva, JMC Sousa, TA Runkler, JMGS Da Costa
European Journal of Operational Research 199 (2), 349-358, 2009
Comparative assessment of low-complexity models to predict electricity consumption in an institutional building: Linear regression vs. fuzzy modeling vs. neural …
H Pombeiro, R Santos, P Carreira, C Silva, JMC Sousa
Energy and Buildings 146, 141-151, 2017
Clustering representative days for power systems generation expansion planning: Capturing the effects of variable renewables and energy storage
IJ Scott, PMS Carvalho, A Botterud, CA Silva
Applied Energy 253, 113603, 2019
Rescheduling and optimization of logistic processes using GA and ACO
CA Silva, JMC Sousa, TA Runkler
Engineering Applications of Artificial Intelligence 21 (3), 343-352, 2008
Demand response modeling: A comparison between tools
D Neves, A Pina, CA Silva
Applied Energy 146, 288-297, 2015
Impact of solar and wind forecast uncertainties on demand response of isolated microgrids
D Neves, MC Brito, CA Silva
Renewable energy 87, 1003-1015, 2016
Peer-to-peer energy trading potential: An assessment for the residential sector under different technology and tariff availabilities
D Neves, I Scott, CA Silva
Energy 205, 118023, 2020
Optimal electricity dispatch on isolated mini-grids using a demand response strategy for thermal storage backup with genetic algorithms
D Neves, CA Silva
Energy 82, 436-445, 2015
Algorithm for Demand Response to Maximize the Penetration of Renewable Energy
EHRC A. A. Hadi, C. A. S. Silva
IEEE Access 8 (10.1109/ACCESS.2020.2981877), 55279-55288, 2020
Environmental, economic, and social impacts of feed-in tariffs: A Portuguese perspective 2000–2010
P Behrens, JFD Rodrigues, T Brás, C Silva
Applied energy 173, 309-319, 2016
Energy reduction potential from the shift to electric vehicles: The Flores island case study
A Pina, P Baptista, C Silva, P Ferrão
Energy Policy 67, 37-47, 2014
Integrating GIS spatial dimension into BREEAM communities sustainability assessment to support urban planning policies, Lisbon case study
J Pedro, C Silva, MD Pinheiro
Land Use Policy 83, 2019
Modeling the long-term impact of demand response in energy planning: The Portuguese electric system case study
J Anjo, D Neves, C Silva, A Shivakumar, M Howells
Energy 165, 456-468, 2018
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