Medium- and Long-Term Power System Planning Method Based on Source-Load Uncertainty Modeling DOI Creative Commons
Wenfeng Yao, Ziyu Huo,

Jin Zou

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(20), P. 5088 - 5088

Published: Oct. 13, 2024

In order to consider the impact of source-load uncertainty on traditional power system planning methods, a medium- and long-term optimization method based modeling time-series production simulation is proposed. First, new energy output probability model developed using non-parametric kernel density estimation, spatial correlation described pair-copula theory analysis output. Secondly, large number scenarios are generated Markov chain Monte Carlo method, optimal selection for discrete state numbers provided, then scenario reduction carried out fast forward elimination technology. Finally, typical curves characteristics obtained incorporated into together with various flexible resources, such as demand-side response storage, rationality scheme judged optimized key indicators cost, wind–light abandonment rate, loss-of-load rate. Based above this paper offers an example supply certain region in next 30 years, providing effective guidance development region.

Language: Английский

A comparative analysis of real and theoretical data in offshore wind energy generation DOI Creative Commons
Fernando M. Camilo, Paulo Santos, A. J. Pires

et al.

e-Prime - Advances in Electrical Engineering Electronics and Energy, Journal Year: 2025, Volume and Issue: unknown, P. 100901 - 100901

Published: Jan. 1, 2025

Language: Английский

Citations

0
Multivariate rolling decomposition hybrid learning paradigm for power load forecasting DOI
Aiting Xu, Jiapeng Chen, Jinchang Li

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 212, P. 115375 - 115375

Published: Jan. 23, 2025

Language: Английский

Citations

0
Environmental policy-driven electricity consumption prediction: A novel buffer-corrected Hausdorff fractional grey model informed by two-stage enhanced multi-objective optimization DOI
Yuansheng Qian, Zhijie Zhu, Xinsong Niu

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 377, P. 124540 - 124540

Published: Feb. 24, 2025

Language: Английский

Citations

0
A Hybrid Model Combined Deep Neural Network and Beluga Whale Optimizer for China Urban Dissolved Oxygen Concentration Forecasting DOI Open Access

Tianruo Wang,

L. Ding, Daizhou Zhang

et al.

Water, Journal Year: 2024, Volume and Issue: 16(20), P. 2966 - 2966

Published: Oct. 17, 2024

The dissolved oxygen concentration (DOC) is an important indicator of water quality. Accurate DOC predictions can provide a scientific basis for environment management and pollution prevention. This study proposes hybrid forecasting framework combined with Variational Mode Decomposition (VMD), convolutional neural network (CNN), Gated Recurrent Unit (GRU), the Beluga Whale Optimization (BWO) algorithm. Specifically, original sequences were decomposed using VMD. Then, CNN-GRU attention mechanism was utilized to extract key features local dependency sequences. Introducing BWO algorithm solved correction coefficients proposed system, aim improving prediction accuracy. used 4-h monitoring China urban quality data from November 2020 2023. Taking Lianyungang as example, empirical findings exhibited noteworthy enhancements in performance metrics such MSE, RMSE, MAE, MAPE within VMD-BWO-CNN-GRU-AM, reductions 0.2859, 0.3301, 0.2539, 0.0406 compared GRU. These results affirmed superior precision diminished errors model, facilitating more precise predictions. system pivotal sustainably regulating quality, particularly terms addressing concerns.

Language: Английский

Citations

2
Medium- and Long-Term Power System Planning Method Based on Source-Load Uncertainty Modeling DOI Creative Commons
Wenfeng Yao, Ziyu Huo,

Jin Zou

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(20), P. 5088 - 5088

Published: Oct. 13, 2024

In order to consider the impact of source-load uncertainty on traditional power system planning methods, a medium- and long-term optimization method based modeling time-series production simulation is proposed. First, new energy output probability model developed using non-parametric kernel density estimation, spatial correlation described pair-copula theory analysis output. Secondly, large number scenarios are generated Markov chain Monte Carlo method, optimal selection for discrete state numbers provided, then scenario reduction carried out fast forward elimination technology. Finally, typical curves characteristics obtained incorporated into together with various flexible resources, such as demand-side response storage, rationality scheme judged optimized key indicators cost, wind–light abandonment rate, loss-of-load rate. Based above this paper offers an example supply certain region in next 30 years, providing effective guidance development region.

Language: Английский

Citations

1