| 1 |
Urban long term electricity demand forecast method based on system dynamics of the new economic normal: The case of Tianjin
He YX, Jiao J, Chen Q, Ge SF, Chang Y, Xu Y
Energy, 133, 9, 2017 |
| 2 |
Optimization of combined heat and power production with heat storage based on sliding time window method
Fang TT, Lahdelma R
Applied Energy, 162, 723, 2016 |
| 3 |
Forecasting electric demand of supply fan using data mining techniques
Le Cam M, Daoud A, Zmeureanu R
Energy, 101, 541, 2016 |
| 4 |
Sensitivity of price elasticity of demand to aggregation, unobserved heterogeneity, price trends, and price endogeneity: Evidence from US Data
Miller M, Alberini A
Energy Policy, 97, 235, 2016 |
| 5 |
Multivariate statistical and similarity measure based semiparametric modeling of the probability distribution: A novel approach to the case study of mid-long term electricity consumption forecasting in China
Shao Z, Gao F, Zhang Q, Yang SL
Applied Energy, 156, 502, 2015 |
| 6 |
Forecasting low voltage distribution network demand profiles using a pattern recognition based expert system
Bennett CJ, Stewart RA, Lu JW
Energy, 67, 200, 2014 |
| 7 |
Development and validation of artificial neural network models of the energy demand in the industrial sector of the United States
Kialashaki A, Reisel JR
Energy, 76, 749, 2014 |
| 8 |
Density prediction and dimensionality reduction of mid-term electricity demand in China: A new semiparametric-based additive model
Shao Z, Yang SL, Gao F
Energy Conversion and Management, 87, 439, 2014 |
| 9 |
Impact of oil prices, economic diversification policies and energy conservation programs on the electricity and water demands in Kuwait
Wood M, Alsayegh OA
Energy Policy, 66, 144, 2014 |
| 10 |
Potentials for energy savings and long term energy demand of Croatian households sector
Puksec T, Mathiesen BV, Duic N
Applied Energy, 101, 15, 2013 |
