LAPSE:2023.13084
Published Article

LAPSE:2023.13084
A Mid/Long-Term Optimization Model of Power System Considering Cross-Regional Power Trade and Renewable Energy Absorption Interval
February 28, 2023
Abstract
With the integration of large-scale renewable energy into the power grids, cross-regional power trade can play a major role in promoting renewable energy consumption, as it can effectively achieve the optimal allocation of interconnected power grid resources and ensure the safe and economic operation of the power grid. An optimization model on a mid/long-term scale is established, considering the relationship between the renewable energy absorption interval and the regulation of resources in the system. The model is based on the load block curve and the renewable energy power model, considering the maintenance constraints of conventional units, the operation constraints of conventional units and renewable energy units, cross-regional power trade constraints and system operation constraints. By analyzing the results of the adapted IEEE RELIABILITY TEST SYSTEM (IEEE-RTS), the validity of the model and method proposed in this paper is proven. The results show that the coordinated optimization of conventional energy and renewable energy in the system can be achieved, and the complementarity of power supply and load can be promoted.
With the integration of large-scale renewable energy into the power grids, cross-regional power trade can play a major role in promoting renewable energy consumption, as it can effectively achieve the optimal allocation of interconnected power grid resources and ensure the safe and economic operation of the power grid. An optimization model on a mid/long-term scale is established, considering the relationship between the renewable energy absorption interval and the regulation of resources in the system. The model is based on the load block curve and the renewable energy power model, considering the maintenance constraints of conventional units, the operation constraints of conventional units and renewable energy units, cross-regional power trade constraints and system operation constraints. By analyzing the results of the adapted IEEE RELIABILITY TEST SYSTEM (IEEE-RTS), the validity of the model and method proposed in this paper is proven. The results show that the coordinated optimization of conventional energy and renewable energy in the system can be achieved, and the complementarity of power supply and load can be promoted.
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Keywords
cross-regional power trade, power system optimization, Renewable and Sustainable Energy
Subject
Suggested Citation
Ma X, Zhang Z, Bai H, Ren J, Cheng S, Kang X. A Mid/Long-Term Optimization Model of Power System Considering Cross-Regional Power Trade and Renewable Energy Absorption Interval. (2023). LAPSE:2023.13084
Author Affiliations
Ma X: School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710000, China; Northwest Branch of State Grid Corporation of China, Xi’an 710000, China
Zhang Z: School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710000, China
Bai H: School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710000, China
Ren J: School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710000, China; Northwest Branch of State Grid Corporation of China, Xi’an 710000, China
Cheng S: Northwest Branch of State Grid Corporation of China, Xi’an 710000, China
Kang X: School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710000, China
Zhang Z: School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710000, China
Bai H: School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710000, China
Ren J: School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710000, China; Northwest Branch of State Grid Corporation of China, Xi’an 710000, China
Cheng S: Northwest Branch of State Grid Corporation of China, Xi’an 710000, China
Kang X: School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710000, China
Journal Name
Energies
Volume
15
Issue
10
First Page
3594
Year
2022
Publication Date
2022-05-13
ISSN
1996-1073
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PII: en15103594, Publication Type: Journal Article
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LAPSE:2023.13084
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https://doi.org/10.3390/en15103594
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