Yakıt hücresi birleşik soğutma, ısıtma ve güç sistemi: Ekonomi ve enerji verimliliğini göz önünde bulunduran enerji yönetimi stratejisi ve çok amaçlı optimizasyon konfigürasyonu

Özet (abstract)

This study investigates the fuel cell combined cooling, heating and power (FC-CCHP) system, and proposes a novel Following Coordinated Thermal-Electric Load (FCTEL) strategy to overcome the multi-load mismatching defects of conventional FTL and FEL strategies. Simulation results show that compared with FTL and FEL strategies, the FCTEL strategy reduces system daily cost by 5.35 % and 4.48 %, increases energy coefficient by 1.35 % and 1.02 %, and improves exergy efficiency by 2.54 % and 1.91 %, respectively; benchmarked against the mixed-integer-linear-programming-based day-ahead predictive scheduling (DAPS) strategy, the daily cost of FCTEL is only 3.4 % higher than that of DAPS, while its energy coefficient and exergy efficiency reach 99.4 % and 98.0 % of those of DAPS through real-time scheduling rather than day-ahead predictive scheduling. The performance ranking of the three strategies remains unchanged under load perturbations and electricity price variations, confirming the robustness of the proposed strategy to both load and price uncertainties. A high-precision BP neural network surrogate model is constructed and combined with the improved MOPSO algorithm to obtain the Pareto frontier, and TOPSIS is adopted to select optimal compromise configurations, the obtained scheme reduces cost by 4.53 % versus the efficiency-optimal solution, and increases energy coefficient and exergy efficiency by 6.90 % and 33.91 % versus the economic-optimal scheme. Furthermore, the Pareto frontier is divided into two typical regions with clear basis, providing differentiated configuration suggestions for residential scenarios with different efficiency and budget demands. Annual dynamic simulation verifies the system can adapt to seasonal load variations and realize smooth switching among different working conditions. The proposed strategy-coupled multi-objective optimization framework can effectively balance economic and energy performance, providing theoretical support and engineering guidance for FC-CCHP application.

Yazarların özeti; kaynağından alınmıştır. Energy Conversion and Management, 2026 · DOI ↗