Published: Jan. 1, 2024
Language: Английский
Published: Jan. 1, 2024
Language: Английский
Applied Energy, Journal Year: 2024, Volume and Issue: 362, P. 122974 - 122974
Published: March 16, 2024
Language: Английский
Citations
21International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: 116, P. 17 - 22
Published: March 11, 2025
Language: Английский
Citations
2International Journal of Fuzzy Systems, Journal Year: 2024, Volume and Issue: 26(7), P. 2109 - 2131
Published: April 20, 2024
Language: Английский
Citations
8Energy, Journal Year: 2024, Volume and Issue: 304, P. 132050 - 132050
Published: June 15, 2024
Language: Английский
Citations
5International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: 73, P. 430 - 442
Published: June 10, 2024
Language: Английский
Citations
4Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134470 - 134470
Published: Jan. 1, 2025
Language: Английский
Citations
0Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134938 - 134938
Published: Feb. 1, 2025
Language: Английский
Citations
0Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134918 - 134918
Published: Feb. 1, 2025
Language: Английский
Citations
0Energy Conversion and Management, Journal Year: 2025, Volume and Issue: 333, P. 119823 - 119823
Published: April 24, 2025
Language: Английский
Citations
0IET Generation Transmission & Distribution, Journal Year: 2024, Volume and Issue: 18(4), P. 844 - 854
Published: Jan. 25, 2024
Abstract In the hydrogen‐based integrated energy system (HIES), there exists a hydrogen trading market where producers and consumers are distinct stakeholders. Current research in predominantly focuses on high‐cost green (GH), which is not aligned with current trend of utilizing from multiple sources. To address this, this paper proposes strategy between virtual plant (VHP) electro‐hydrogen (EHES) based bi‐level model, considering synergy GH produced electrolyzers blue (BH) derived natural gas HIES. VHP level, objective to maximize profit sales, allowing for determination prices. EHES goal minimize cost supply, leading formulation BH purchasing plans Additionally, incorporates risk‐averse model information gap decision theory (IGDT) account impact wind power output uncertainties level. Subsequently, leveraging Karush–Kuhn–Tucker (KKT) conditions problem transformed into solvable single‐level mathematical program equilibrium constraints (MPEC), non‐linear linearized. The proposed optimization validated through case studies encompassing industrial residential utilization within outcomes confirm rationality demonstrating that, comparison exclusively GH, coordinated can increase by 2.7% reduce costs 8.5%.
Language: Английский
Citations
2