LAPSE:2023.30465
Published Article
LAPSE:2023.30465
Penalty Electricity Price-Based Optimal Control for Distribution Networks
Qingle Pang, Lin Ye, Houlei Gao, Xinian Li, Yang Zheng, Chenbin He
April 14, 2023
With the integration of large-scale renewable energy and the implementation of demand response, the complexity and volatility of distribution network operations are increasing. This has led to the inconsistency between the actual net power consumption of power users and their optimal dispatching orders. As a result, the distribution networks cannot operate according to their optimization strategy. The study proposed a penalty electricity price mechanism and the optimal control method based on this electricity price mechanism for distribution networks. First, we established the structure of the distribution network optimal control system. Second, aiming at the actual net power consumption (including power generation and consumption) of power users tracking their dispatching orders, we established a penalty electricity price mechanism. Third, we designed an optimal control strategy and process of distribution networks based on the penalty electricity price. Finally, we verified the proposed method by taking the IEEE-33 node system as an example. The verification results showed that the penalty electricity price could effectively limit the net power consumption fluctuations of power users to achieve optimal control of distribution networks.
Keywords
distribution networks, optimal control, optimal dispatching order, penalty electricity price, supply and demand balance
Suggested Citation
Pang Q, Ye L, Gao H, Li X, Zheng Y, He C. Penalty Electricity Price-Based Optimal Control for Distribution Networks. (2023). LAPSE:2023.30465
Author Affiliations
Pang Q: School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China [ORCID]
Ye L: School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China
Gao H: School of Electrical Engineering, Shandong University, Jinan 250061, China
Li X: School of Information and Electronic Engineering, Shandong Technology and Business University, Yantai 264005, China
Zheng Y: School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China
He C: School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China
Journal Name
Energies
Volume
14
Issue
7
First Page
1806
Year
2021
Publication Date
2021-03-24
Published Version
ISSN
1996-1073
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PII: en14071806, Publication Type: Journal Article
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LAPSE:2023.30465
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doi:10.3390/en14071806
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