11 |
Comparative study of reduced order equivalent circuit models for on-board state-of-available-power prediction of lithium-ion batteries in electric vehicles Farmann A, Sauer DU Applied Energy, 225, 1102, 2018 |
12 |
Prediction of short-term PV power output and uncertainty analysis Liu LY, Zhao Y, Chang DL, Xie JY, Ma ZY, Sun Q, Yin HY, Wennersten R Applied Energy, 228, 700, 2018 |
13 |
Evaluation of data-driven models for predicting solar photovoltaics power output Moslehi S, Reddy TA, Katipamula S Energy, 142, 1057, 2018 |
14 |
A novel hybrid technique for prediction of electric power generation in wind farms based on WIPSO, neural network and wavelet transform Esfetang NN, Kazemzadeh R Energy, 149, 662, 2018 |
15 |
Short-term power prediction for photovoltaic power plants using a hybrid improved Kmeans-GRA-Elman model based on multivariate meteorological factors and historical power datasets Lin PJ, Peng ZN, Lai YF, Cheng SY, Chen ZC, Wu LJ Energy Conversion and Management, 177, 704, 2018 |
16 |
Available power prediction limited by multiple constraints for LiFePO4 batteries based on central difference Kalman filter Xie JL, Ma JC, Chen J International Journal of Energy Research, 42(15), 4730, 2018 |
17 |
Power capability prediction for lithium-ion batteries using economic nonlinear model predictive control Zou CF, Klintberg A, Wei ZB, Fridholm B, Wik T, Egardt B Journal of Power Sources, 396, 580, 2018 |
18 |
Interval prediction of solar power using an Improved Bootstrap method Li KW, Wang R, Lei HT, Zhang T, Liu YJ, Zheng XK Solar Energy, 159, 97, 2018 |
19 |
Wind power prediction using hybrid autoregressive fractionally integrated moving average and least square support vector machine Yuan XH, Tan QX, Lei XH, Yuan YB, Wu XT Energy, 129, 122, 2017 |
20 |
A new chaotic time series hybrid prediction method of wind power based on EEMD-SE and full-parameters continued fraction Wang C, Zhang HL, Fan WH, Ma P Energy, 138, 977, 2017 |