LAPSE:2023.9089
Published Article
LAPSE:2023.9089
Research on Renewable-Energy Accommodation-Capability Evaluation Based on Time-Series Production Simulations
Dan Zhou, Qi Zhang, Yangqing Dan, Fanghong Guo, Jun Qi, Chenyuan Teng, Wenwei Zhou, Haonan Zhu
February 27, 2023
Abstract
In recent years, renewable energy has received extensive attention due to its advantages of sustainability, economy, and environmental protection. However, with the rapid development of renewable energy, the problem of curtailment is becoming increasingly serious. Studying the calculation method and establishing a quantitative evaluation system of renewable energy accommodation capacity are important means to solve this problem. This paper comprehensively considers the factors affecting the accommodation of renewable energy, establishes a accommodation calculation model with the maximum accommodation of renewable energy as the optimization target based on the time series production simulation method, and uses the hybrid particle swarm optimization (PSO) algorithm to solve it. The model is verified with historical data such as load, photovoltaic (PV), and wind power in a certain region throughout the year. The experimental results verify the rationality of the renewable-energy accommodation-capacity model proposed in this paper and the correctness of the theoretical analysis. The calculation results have important reference and guiding significance for the operation and control of power-grid planning and dispatching.
Keywords
accommodation capability, Particle Swarm Optimization, power grid planning, Renewable and Sustainable Energy, time-series production simulation
Suggested Citation
Zhou D, Zhang Q, Dan Y, Guo F, Qi J, Teng C, Zhou W, Zhu H. Research on Renewable-Energy Accommodation-Capability Evaluation Based on Time-Series Production Simulations. (2023). LAPSE:2023.9089
Author Affiliations
Zhou D: College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
Zhang Q: College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
Dan Y: Economic and Technological Research Institute, State Grid Zhejiang Electric Power Co., Ltd., Hangzhou 310016, China
Guo F: College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
Qi J: College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
Teng C: College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
Zhou W: College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
Zhu H: College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
Journal Name
Energies
Volume
15
Issue
19
First Page
6987
Year
2022
Publication Date
2022-09-23
ISSN
1996-1073
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Original Submission
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PII: en15196987, Publication Type: Journal Article
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LAPSE:2023.9089
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https://doi.org/10.3390/en15196987
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