| 1 |
Energy consumption forecasting in agriculture by artificial intelligence and mathematical models
Bolandnazar E, Rohani A, Taki M
Energy Sources Part A-recovery Utilization and Environmental Effects, 42(13), 1618, 2020 |
| 2 |
Machine learning-based energy consumption clustering and forecasting for mixed-use buildings
Culaba AB, Del Rosario AJR, Ubando AT, Chang JS
International Journal of Energy Research, 44(12), 9659, 2020 |
| 3 |
Optimal design for solar greenhouses based on climate conditions
Esmaeli H, Roshandel R
Renewable Energy, 145, 1255, 2020 |
| 4 |
Learning is not enough: Diminishing marginal revenues and increasing abatement costs of wind and solar
Das S, Hittinger E, Williams E
Renewable Energy, 156, 634, 2020 |
| 5 |
When is the sun going to shine for the Brazilian energy sector? A story of how modelling affects solar electricity
Barbosa J, Dias LP, Simoes SG, Seixas J
Renewable Energy, 162, 1684, 2020 |
| 6 |
Life cycle assessment of hydrogen from proton exchange membrane water electrolysis in future energy systems
Bareiss K, de la Rua C, Mockl M, Hamacher T
Applied Energy, 237, 862, 2019 |
| 7 |
Forecasting peak electricity demand for Los Angeles considering higher air temperatures due to climate change
Burillo D, Chester MV, Pincetl S, Fournier ED, Reyna J
Applied Energy, 236, 1, 2019 |
| 8 |
Hourly-resolution analysis of electricity decarbonization in Spain (2017-2030)
Victoria M, Gallego-Castillo C
Applied Energy, 233, 674, 2019 |
| 9 |
Modeling India's energy future using a bottom-up approach
du Can SD, Khandekar A, Abhyankar N, Phadke A, Khanna NZ, Fridley D, Zhou N
Applied Energy, 238, 1108, 2019 |
| 10 |
Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm
Wang W, Hong TZ, Xu XD, Chen JY, Liu Z, Xu N
Applied Energy, 248, 217, 2019 |
