Muti‐units day‐ahead scheduling involving the pumped storages and considering deep‐load regulation

Abstract This paper presents a day‐ahead scheduling for multi‐energy entities. The deep load regulation involving pumped storages, which refers to deep peak regulation, is adopted to address the impact of wind power and photovoltaic (PV) uncertainties, thereby improving the economic efficiencies of day‐ahead dispatching. And the impact of different peak valley electricity price differences on the peak shaving effectiveness of pumped storage energy was studied. Firstly, the multi‐scenario random programming method is applied to solve the prediction uncertainties of wind power and PV output in the day‐ahead. Subsequently, the multi‐scenario set of day‐ahead wind power and PV output and the load forecasting curve are considered. A pumped storage scheduling model is then established integrating the hydropower, thermal power and pumped storage. The optimal generation scheduling of pumped storage and thermal units is determined by minimizing load fluctuations and peak shaving costs. Finally, a local power grid in the Hunan province of China is selected for verification. It is shown that the proposed model can effectively accommodate the fluctuation of renewable energy output, reduce the peak regulating pressure of thermal units, and improve the operational economy of the power system.

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Publication Details

Journal
The Journal of Engineering
Published
2024-11-01
DOI
https://doi.org/10.1049/tje2.70019
Citations
1
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.21
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Muti‐units day‐ahead scheduling involving the pumped storages and considering deep‐load regulation

Ting Zhou, Ye Cai, Jiaxi Li, Tan Yu-dong et al.
1 citations
The Journal of Engineering
Smart Grid Energy Management
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article

Muti‐units day‐ahead scheduling involving the pumped storages and considering deep‐load regulation

Ting Zhou, Ye Cai, Jiaxi Li, Tan Yu-dong, Ming Wen
article en
1 citations

Abstract

Abstract This paper presents a day‐ahead scheduling for multi‐energy entities. The deep load regulation involving pumped storages, which refers to deep peak regulation, is adopted to address the impact of wind power and photovoltaic (PV) uncertainties, thereby improving the economic efficiencies of day‐ahead dispatching. And the impact of different peak valley electricity price differences on the peak shaving effectiveness of pumped storage energy was studied. Firstly, the multi‐scenario random programming method is applied to solve the prediction uncertainties of wind power and PV output in the day‐ahead. Subsequently, the multi‐scenario set of day‐ahead wind power and PV output and the load forecasting curve are considered. A pumped storage scheduling model is then established integrating the hydropower, thermal power and pumped storage. The optimal generation scheduling of pumped storage and thermal units is determined by minimizing load fluctuations and peak shaving costs. Finally, a local power grid in the Hunan province of China is selected for verification. It is shown that the proposed model can effectively accommodate the fluctuation of renewable energy output, reduce the peak regulating pressure of thermal units, and improve the operational economy of the power system.

The Journal of EngineeringVol. 2024(11)
Hunan Xiangdian Test Research Institute (China) (CN), State Grid Hunan Electric Power Company Limited (CN), Changsha University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 46%
Smart Grid Energy Management
0.21
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