| 1 |
Computer-assisted demand-side energy management in residential smart grid employing novel pooling deep learning algorithm
Jeyaraj PR, Nadar ERS
International Journal of Energy Research, 45(5), 7961, 2021 |
| 2 |
On Entry Cost Dynamics in Australia's National Electricity Market
Simshauser P, Gilmore J
Energy Journal, 41(1), 259, 2020 |
| 3 |
Scenarios analysis on the cross-region integrating of renewable power based on a long-period cost-optimization power planning model
Li TX, Li Z, Li WQ
Renewable Energy, 156, 851, 2020 |
| 4 |
Power system expansion planning under global and local emission mitigation policies
Quiroga D, Sauma E, Pozo D
Applied Energy, 239, 1250, 2019 |
| 5 |
Development of a degradation-conscious physics-based lithium-ion battery model for use in power system planning studies
Li Y, Vilathgamuwa M, Choi SS, Farrell TW, Tran NT, Teague J
Applied Energy, 248, 512, 2019 |
| 6 |
Sizing and Improved Grid Integration of Residential PV Systems With Heat Pumps and Battery Storage Systems
von Appen J, Braun M
IEEE Transactions on Energy Conversion, 34(1), 562, 2019 |
| 7 |
Load forecasting under changing climatic conditions for the city of Sydney, Australia
Ahmed T, Vu DH, Muttaqi KM, Agalgaonkar AP
Energy, 142, 911, 2018 |
| 8 |
Multi-objective optimization for sustainable development of the power sector: An economic, environmental, and social analysis of Iran
Atabaki MS, Aryanpur V
Energy, 161, 493, 2018 |
| 9 |
Policy implications of downscaling the time dimension in power system planning models to represent variability in renewable output
Reichenberg L, Siddiqui AS, Wogrin S
Energy, 159, 870, 2018 |
| 10 |
Benefits of a multi-energy day-ahead market
van Stiphout A, Virag A, Kessels K, Deconinck G
Energy, 165, 651, 2018 |
