4E analysis and multi-objective GWO of a novel MSW-fed biomass based multigeneration system integrated with cascaded thermal recovery and alkaline water electrolysis: Monte Carlo risk assessment
International Communications in Heat and Mass Transfer, cilt.180, sa.P1, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 180 Sayı: P1
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.icheatmasstransfer.2026.112408
- Dergi Adı: International Communications in Heat and Mass Transfer
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Academic Search Ultimate (EBSCO), Engineering Source (EBSCO)
- Anahtar Kelimeler: Alkaline water electrolysis (AWE), Biphenyl/diphenyl oxide mixture circulation, High/low-temperature loop, Machine learning optimization, Residual thermal energy, Thermo-economic analysis
- İstanbul Gelişim Üniversitesi Adresli: Evet
Özet
This study presents a novel municipal solid waste (MSW)-based multigeneration system designed for the simultaneous production of power, cooling, freshwater, and green hydrogen. The system employs a cascaded organic Rankine cycle (CORC) with biphenyl/diphenyl oxide (BDO) and Toluene as working fluids to enhance exergy recovery from gas turbine exhaust. A key novelty is the strategic selection of alkaline water electrolysis (AWE) over proton exchange membrane electrolysis (PEME), addressing the latter's stringent ultrapure water requirements and eliminating costly pretreatment subsystems. Baseline analysis reveals that the Brayton cycle and gasifier dominate exergy destruction, contributing 37.11% and 33.07%, respectively. A comprehensive Monte Carlo simulation demonstrates robust financial viability, with a mean net present value (NPV) of 36.69 M$ with 100[jls-end-space/]% probability, and 0.8433 kg/kWh emission rate; Scenario II (optimizing exergy efficiency and hydrogen production) achieves 53.47% exergy efficiency, 39.55 kg/h hydrogen production, and superior financial performance with an NPV of 56.29 M$ and payback period of 3.32 years by 2046. This comprehensive 4E (Energy, Exergy, Economic, Environmental) analysis, coupled with Monte Carlo uncertainty quantification and machine learning-driven optimization, demonstrates the technical and economic viability of the proposed MSW-to-hydrogen multigeneration system, offering a scalable and robust solution for sustainable municipal waste management and clean energy production.