| 1 |
Impacts of future weather data typology on building energy performance - Investigating long-term patterns of climate change and extreme weather conditions
Moazami A, Nik VM, Carlucci S, Geving S
Applied Energy, 238, 696, 2019 |
| 2 |
Machine learning methods to assist energy system optimization
Perera ATD, Wickramasinghe PU, Nik VM, Scartezzini JL
Applied Energy, 243, 191, 2019 |
| 3 |
Economic feasibility of building retrofitting mitigation potentials: Climate change uncertainties for Swedish cities
Mata E, Wanemark J, Nik VM, Kalagasidis AS
Applied Energy, 242, 1022, 2019 |
| 4 |
Machine learning methods to assist energy system optimization
Perera ATD, Wickramasinghe PU, Nik VM, Scartezzini JL
Applied Energy, 243, 191, 2019 |
| 5 |
Impacts of urban morphology on reducing cooling load and increasing ventilation potential in hot-arid climate
Javanroodi K, Mandavinejad M, Nik VM
Applied Energy, 231, 714, 2018 |
| 6 |
Passive design optimization of newly-built residential buildings in Shanghai for improving indoor thermal comfort while reducing building energy demand
Gou SQ, Nik VM, Scartezzini JL, Zhao Q, Li ZR
Energy and Buildings, 169, 484, 2018 |
| 7 |
Electrical hubs: An effective way to integrate non-dispatchable renewable energy sources with minimum impact to the grid
Perera ATD, Nik VM, Mauree D, Scartezzini JL
Applied Energy, 190, 232, 2017 |
| 8 |
An integrated approach to design site specific distributed electrical hubs combining optimization, multi-criterion assessment and decision making
Perera ATD, Nik VM, Mauree D, Scartezzini JL
Energy, 134, 103, 2017 |
| 9 |
Application of typical and extreme weather data sets in the hygrothermal simulation of building components for future climate - A case study for a wooden frame wall
Nik VM
Energy and Buildings, 154, 30, 2017 |
| 10 |
Making energy simulation easier for future climate - Synthesizing typical and extreme weather data sets out of regional climate models (RCMs)
Nik VM
Applied Energy, 177, 204, 2016 |
