Tianyu Wen
Tianyu Wen has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Lingling Li
State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, China
2 shared publications - Cheng-Jian Lin
Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung, Taiwan
1 shared publication - Dingshan Wu
State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China
1 shared publication Honghao Liu
Hebei Univ Technol, Key Lab Reliabil & Intelligence Elect Equipment, Tianjin 300401, Peoples R China
1 shared publication- Lin Wu
Nottingham University Business School China, University of Nottingham
1 shared publication
Latest Publications
- Open Access
- 29 November 2024
- Published by MYU K.K. in Sensors and Materials
- Vol. 36 (11) , 5049-5063
Configuration Optimization of Distributed Energy System Considering Multi-energy Complementary and Load Metering Devices: A Multi-objective Exponential Distribution Optimization Algorithm
- 29 November 2024
- Published by MYU K.K. in Sensors and Materials
- Vol. 36 (11) , 5049-5063
Open AccessConfiguration Optimization of Distributed Energy System Considering Multi-energy Complementary and Load Metering Devices: A Multi-objective Exponential Distribution Optimization Algorithm
- Open Access
Microgrid Operation Optimization Method Considering Power-to-Gas Equipment: An Improved Gazelle Optimization Algorithm
With the increasingly prominent defects of traditional fossil energy, large-scale renewable energy access to power grids has become a trend. In this study, a microgrid operation optimization method, including power-to-gas equipment and a hybrid energy storage system, is proposed. Firstly, this study constructs a microgrid system structure including P2G equipment and a hybrid energy storage system of electricity and hydrogen. Secondly, aiming at minimizing the system operation cost and carbon emission penalty cost, a low-carbon economic operation optimization model of the proposed microgrid is established. Then, this study proposes a microgrid optimization method based on an improved gazelle optimization algorithm to symmetrically improve economic and environmental performance. Finally, the practicability and superiority of the above model and optimization method are verified using a real microgrid case. The results show that considering the participation of P2G equipment and a hybrid energy storage system in the optimal operation, the carbon emission of the microgrid is reduced to 33.56% of the microgrid considering only a single electric energy storage system, and the comprehensive operation cost is reduced by 6.54%. This study is conducive to promoting the development of clean energy and symmetrically enhancing the economic and environmental performance of the microgrid.
Open AccessMicrogrid Operation Optimization Method Considering Power-to-Gas Equipment: An Improved Gazelle Optimization Algorithm
With the increasingly prominent defects of traditional fossil energy, large-scale renewable energy access to power grids has become a trend. In this study, a microgrid operation optimization method, including power-to-gas equipment and a hybrid energy storage system, is proposed. Firstly, this study constructs a microgrid system structure including P2G equipment and a hybrid energy storage system of electricity and hydrogen. Secondly, aiming at minimizing the system operation cost and carbon emission penalty cost, a low-carbon economic operation optimization model of the proposed microgrid is established. Then, this study proposes a microgrid optimization method based on an improved gazelle optimization algorithm to symmetrically improve economic and environmental performance. Finally, the practicability and superiority of the above model and optimization method are verified using a real microgrid case. The results show that considering the participation of P2G equipment and a hybrid energy storage system in the optimal operation, the carbon emission of the microgrid is reduced to 33.56% of the microgrid considering only a single electric energy storage system, and the comprehensive operation cost is reduced by 6.54%. This study is conducive to promoting the development of clean energy and symmetrically enhancing the economic and environmental performance of the microgrid.