Waste management (New York, N.Y.) · 2026
4E analysis and thermo-economic optimization in transitioning waste-to-energy plants from mono-generation to cogeneration.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Qin Pengcheng, Ying Yuxuan, Hu Siyi, An Zhaohui, Long Jisheng, Zhang Hao, Li Xiaodong
Аннотация
As global energy networks decarbonize, municipal waste-to-energy (WtE) plants are increasingly required to evolve from static baseload providers into flexible energy hubs. However, extracting heat from systems originally designed for pure power generation (PG) incurs off-design thermal penalties, and the thermodynamic trade-offs of this flexibility remain poorly quantified. This study proposes a comprehensive 4E (Energy, Exergy, Economic, Environmental) framework to decode the mechanisms of exergy destruction and off-design adaptability across PG, separate heat and power (SHP), and combined heat and power (CHP) modes. By systematically tracing irreversibilities across subsystems using actual operational data, this study reveals that flexible operations reconfigure the system's thermodynamic bottlenecks. Notably, the SHP mode achieves a First-Law efficiency of 73.70% while its exergy efficiency remains as low as 22.64%, which quantitatively reveals the work potential destroyed by direct throttling of high-parameter steam. Conversely, CHP effectively eliminates substantial condenser cold-end losses through cascaded energy utilization, achieving the highest exergy efficiency of 27.26% among the studied cases. The CHP system yields a CO2 emission of -0.174 t CO2 per ton waste, representing a 196% improvement relative to the PG baseline. Furthermore, a multi-objective optimization utilizing the NSGA-II algorithm is coupled with empirical Distributed Control System data. The derived Pareto frontier quantitatively maps the real-world thermo-economic dispatch limits, revealing the precise performance gap between theoretical optimization and current operational strategies. These findings provide critical quantitative boundaries for the optimal thermo-economic design and heat-to-power dispatch of future adaptable WtE infrastructures.