Multi-objective integrated energy control system that uses compromise programming method

This paper establishes a mathematical model for the optimal scheduling problem of the P2G-CCS integrated energy system. The model comprehensively optimizes the allocation and scheduling of various energy forms within the IES, such as electricity, thermal energy, and gas, focusing on economic efficie...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:2025 4th International Conference on Smart Grid and Green Energy (ICSGGE) s. 60 - 65
Hlavní autoři: Qu, Haoming, Li, Yang
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 28.02.2025
Témata:
Carbon dioxide
Compromise Programming
Costs
Electricity
Fuzzy Decision Making
Integrated Energy System
Mathematical models
Optimal scheduling
P2G-CCS Technology
Power system stability
Programming
Resource management
Stability analysis
Thermal stability
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:This paper establishes a mathematical model for the optimal scheduling problem of the P2G-CCS integrated energy system. The model comprehensively optimizes the allocation and scheduling of various energy forms within the IES, such as electricity, thermal energy, and gas, focusing on economic efficiency, environmental impact, and system robustness. The compromise programming method transforms the multi-objective problem into a single-objective problem. During the solution process, the max-min comparison method and fuzzy decision-making are used to select the most suitable compromise solution between economic efficiency and environmental impact. Simulation analysis demonstrates the method's effectiveness, yielding an optimal compromise solution costing 12,856.3689 Yuan(Y) and carbon emissions of \mathbf{1 0, 0 2 0. 2 9 0 8} \mathbf{k g}. Through optimal allocation and scheduling, the integrated energy system can significantly reduce operational costs and carbon emissions while ensuring the stability and reliability of the energy supply.
DOI:10.1109/ICSGGE64667.2025.10985321