| 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 | 368 | 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 | 271 | 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 | 249 | 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 | 185 | 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 | 159 | 2011 |
| Comparing demand response and battery storage to optimize self-consumption in PV systems G Lorenzi, CAS Silva Applied Energy 180, 524–535, 2016 | 131 | 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 | 123 | 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 | 112 | 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 | 110 | 2019 |
| 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 | 99 | 2020 |
| 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 | 99 | 2008 |
| Demand response modeling: A comparison between tools D Neves, A Pina, CA Silva Applied Energy 146, 288-297, 2015 | 95 | 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 | 93 | 2016 |
| 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 | 88 | 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 | 79 | 2016 |
| 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 | 79 | 2015 |
| 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 | 74 | 2019 |
| 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 | 72 | 2014 |
| Model predictive control for microgrid functionalities: Review and future challenges F Garcia-Torres, A Zafra-Cabeza, C Silva, S Grieu, T Darure, ... Energies 14 (5), 1296, 2021 | 71 | 2021 |
| 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 | 71 | 2018 |
Joao Miguel C. SousaIDMEC, Instituto Superior Técnico, Universidade de Lisboa, PortugalVerified email at tecnico.ulisboa.pt
