EPMITS: An Efficient Prediction Method Incorporating Trends and Shapes Features for Chemical Process Variables DOI

Yiming Bai,

Huawei Ye,

Jinsong Zhao

et al.

Computers & Chemical Engineering, Journal Year: 2024, Volume and Issue: 191, P. 108855 - 108855

Published: Aug. 24, 2024

Language: Английский

Combined Ultra-Short-Term Photovoltaic Power Prediction Based on CEEMDAN Decomposition and RIME Optimized AM-TCN-BiLSTM DOI

Daixuan Zhou,

Yujin Liu,

Xu Wang

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134847 - 134847

Published: Feb. 1, 2025

Language: Английский

Citations

2
Optimal planning for integrated electricity and heat systems using CNN-BiLSTM-attention network forecasts DOI
Feng Li,

Shiheng Liu,

Tian-Hu Wang

et al.

Energy, Journal Year: 2024, Volume and Issue: 309, P. 133042 - 133042

Published: Aug. 31, 2024

Language: Английский

Citations

10
Short-term photovoltaic power prediction based on RF-SGMD-GWO-BiLSTM hybrid models DOI
Shaomei Yang,

Y. Luo

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134545 - 134545

Published: Jan. 1, 2025

Language: Английский

Citations

1
Investigation on the Long Short-term Memory-based Models for Rural Heating Load Prediction in Northeast China DOI
Shengming Dong, Tong Liu, Xiaowei Hu

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134751 - 134751

Published: Jan. 1, 2025

Language: Английский

Citations

1
Economic Optimal Dispatch of Networked Hybrid Renewable Energy Microgrid DOI Creative Commons

X Philip Ye,

Peng Yang

Systems, Journal Year: 2025, Volume and Issue: 13(2), P. 109 - 109

Published: Feb. 10, 2025

With the increasing importance of renewable energy in global transition, microgrid has attracted wide attention as an efficient and flexible power solution. However, there are some problems current networked systems, such complex structure, numerous parameters, significant fluctuations generation capacity. Aiming at parameter optimization problem microgrids integrating multiple storage forms, this paper constructs a multi-objective structure decision-making model. The model comprehensively considers operation maintenance costs, fuel abandonment lack-of-power punishment transaction pollution treatment aiming to realize joint economic benefits environmental sustainability. Furthermore, improved particle swarm (IMOPSO) algorithm is designed solve In order verify effectiveness scenarios distributed load fluctuation, uses scenario analysis method data 2000 scenarios, obtains four typical deterministic for simulation experiments. experimental results show that, compared with traditional microgrid, when capacity configuration determined by number wind driven generators, photovoltaic panels, diesel batteries being 5, 189, 2, 107, respectively, proposed net-connected dispatch based on hybrid reduces cost system 96.76 ¥ 428.19 ¥, keeps loss rate stable between 0.34% 4.56%. utilization been raised about 95%.

Language: Английский

Citations

0
Logarithmic mapping and multi-algorithm collaborative optimization for high dynamic load forecasting DOI
Xifeng Guo, Hongye Zhang, Yi Ning

et al.

Electrical Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 23, 2025

Language: Английский

Citations

0
Prediction of Ultra-Short-Term Photovoltaic Power Using BiLSTM–Informer Based on Secondary Decomposition DOI Creative Commons
Ruoqi Zhang, Zishuo Xu, Shuangquan Liu

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(6), P. 1485 - 1485

Published: March 18, 2025

Photovoltaic power generation as a green energy source is often used in systems, but the volatility of PV output and randomness problem affect stability power-grid supply; so, for low prediction accuracy photovoltaic under different weather conditions, this paper proposes Variational Mode Decomposition (VMD), combined with Complementary Ensemble Empirical Adaptive Noise (CEEMDAN) secondary decomposition method original signal decomposition, to reduce complexity feature mapping data, followed by use BiLSTM model timing information decomposed IMF. Simultaneously, Informer predicts components obtained from finally, subsequence reconstructed superimposed obtain value. The results show that RMSE MAE proposed are improved up 10.91% 17.33% on annual dataset, high stability, which can effectively predict ultra-short-term plants.

Language: Английский

Citations

0
Optimal operating strategy of hybrid heat pump − boiler systems with photovoltaics and battery storage DOI Creative Commons
Francesco Nicoletti,

Giuseppe Ramundo,

Natale Arcuri

et al.

Energy Conversion and Management, Journal Year: 2024, Volume and Issue: 323, P. 119233 - 119233

Published: Nov. 7, 2024

Language: Английский

Citations

3
CGAformer: Multi-scale feature Transformer with MLP architecture for short-term photovoltaic power forecasting DOI

Ruo Han Chen,

Gang Liu, Yisheng Cao

et al.

Energy, Journal Year: 2024, Volume and Issue: 312, P. 133495 - 133495

Published: Oct. 21, 2024

Language: Английский

Citations

2
Federated learning and non-federated learning based power forecasting of photovoltaic/wind power energy systems: A systematic review DOI Creative Commons
Filippo Sanfilippo,

Syed Muhammad Salman Bukhari,

Muhammad Hamza Zafar

et al.

Energy and AI, Journal Year: 2024, Volume and Issue: 18, P. 100438 - 100438

Published: Nov. 17, 2024

Language: Английский

Citations

2