Thermal Science and Engineering Progress, Journal Year: 2024, Volume and Issue: 55, P. 102932 - 102932
Published: Sept. 25, 2024
Language: Английский
Thermal Science and Engineering Progress, Journal Year: 2024, Volume and Issue: 55, P. 102932 - 102932
Published: Sept. 25, 2024
Language: Английский
Applied Thermal Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 125605 - 125605
Published: Jan. 1, 2025
Language: Английский
Citations
4Energy Conversion and Management, Journal Year: 2024, Volume and Issue: 307, P. 118373 - 118373
Published: March 30, 2024
Language: Английский
Citations
12Natural Resources Research, Journal Year: 2024, Volume and Issue: 33(5), P. 2037 - 2062
Published: June 19, 2024
Language: Английский
Citations
11Applied Thermal Engineering, Journal Year: 2024, Volume and Issue: 257, P. 124231 - 124231
Published: Aug. 24, 2024
Language: Английский
Citations
7Archives of Computational Methods in Engineering, Journal Year: 2024, Volume and Issue: unknown
Published: May 27, 2024
Language: Английский
Citations
6Applied Thermal Engineering, Journal Year: 2024, Volume and Issue: 248, P. 123143 - 123143
Published: April 8, 2024
Language: Английский
Citations
3Energy Reports, Journal Year: 2025, Volume and Issue: 13, P. 1525 - 1536
Published: Jan. 18, 2025
Language: Английский
Citations
0Renewable Energy, Journal Year: 2025, Volume and Issue: unknown, P. 122532 - 122532
Published: Feb. 1, 2025
Language: Английский
Citations
0Applied Sciences, Journal Year: 2025, Volume and Issue: 15(5), P. 2702 - 2702
Published: March 3, 2025
The microgrid is a small-scale, independent power system that plays crucial role in the transition to carbon-neutral energy systems. Combined heat and (CHP) systems with storage reduce waste within microgrids, enhancing utilization efficiency. key challenge for integrated combined determining optimal configuration operation duration under different scenarios meet users’ electricity demands while minimizing both economic environmental costs. Thus, this paper presents bi-objective mathematical model solve scheduling problem of microgrid. Long Short-Term Memory–Parallel Multi-Objective Energy Valley Optimizer (LSTM-PMOEVO) framework incorporates load prediction using LSTM planning solved via PMOEVO. These strategies address challenges posed by unpredictable fluctuations complexity solving such Finally, public dataset was utilized experiments verify performance proposed algorithm. Comparisons discussions show optimization significantly improve PMOEVO, demonstrating marked advantages over six classical algorithms. In conclusion, PMOEVO developed performs excellently Scheduling Problem Biomass-Hybrid microgrids considering uncertainty. work presented provides new solution microgrid-scheduling future research, will be further advanced application real-world scenarios.
Language: Английский
Citations
0Energy, Journal Year: 2025, Volume and Issue: unknown, P. 135531 - 135531
Published: March 1, 2025
Language: Английский
Citations
0