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Economic Emission Dispatch with Stochastic Renewable Power and Voltage Source Converters via Reinforcement Learning Multi-Objective Differential Evolution
Lv, Derong1; Xiong, Guojiang1; Fu, Xiaofan1; Wong, Man Chung2; Dessaint, Louis A.3; Al-Haddad, Kamal3
2024
Source PublicationIEEE Transactions on Power Systems
ISSN0885-8950
Volume39Issue:6Pages:6889 - 6900
Abstract

Multi-objective economic emission dispatch (MOEED) is a key fundamental problem for the optimal operation of power systems. With the increasing scale of grid integration of renewable power sources such as wind and solar power, the VSC-based multi-port systems can improve the system operation flexibility to increase the consumption of renewable power. In this context, the structure of a multi-port system is more compact, making the corresponding MOEED more complicated. Considering the uncertainty of wind and solar power, a MOEED model for VSC-based multi-port systems is established in this study. The overestimation and underestimation situations of renewable power are modeled. To solve the MOEED model, we presented an enhanced multi-objective differential evolution, namely RLMOQILDE. Moreover, mating pool-based quadratic interpolation, reinforcement learning, and constraint processing technology are combined to boost its performance. Finally, the feasibility of the MOEED model and the effectiveness of RLMOQILDE are verified on two three-port systems constructed by expanding a modified IEEE 30-bus system.

KeywordCosts Differential Evolution Economic Emission Dispatch Generators Optimization Methods Power Generation Renewable Energy Sources Stochastic Processes Uncertainty Uncertainty Voltage Source Converter
DOI10.1109/TPWRS.2024.3371833
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:001342803800005
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC445 HOES LANE, PISCATAWAY, NJ 08855-4141
Scopus ID2-s2.0-85186987751
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionTHE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
Corresponding AuthorXiong, Guojiang; Fu, Xiaofan
Affiliation1.College of Electrical Engineering, Guizhou University, Guiyang, China
2.Department of Electrical and Computer Engineering and the State Key Laboratory of Internet of Thing smart City, University of Macau, Macau, China
3.Department of Electrical Engineering, École de Technologie Supérieure, Université du Québec, Montreal, Canada
Recommended Citation
GB/T 7714
Lv, Derong,Xiong, Guojiang,Fu, Xiaofan,et al. Economic Emission Dispatch with Stochastic Renewable Power and Voltage Source Converters via Reinforcement Learning Multi-Objective Differential Evolution[J]. IEEE Transactions on Power Systems, 2024, 39(6), 6889 - 6900.
APA Lv, Derong., Xiong, Guojiang., Fu, Xiaofan., Wong, Man Chung., Dessaint, Louis A.., & Al-Haddad, Kamal (2024). Economic Emission Dispatch with Stochastic Renewable Power and Voltage Source Converters via Reinforcement Learning Multi-Objective Differential Evolution. IEEE Transactions on Power Systems, 39(6), 6889 - 6900.
MLA Lv, Derong,et al."Economic Emission Dispatch with Stochastic Renewable Power and Voltage Source Converters via Reinforcement Learning Multi-Objective Differential Evolution".IEEE Transactions on Power Systems 39.6(2024):6889 - 6900.
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