期刊论文详细信息
RENEWABLE & SUSTAINABLE ENERGY REVIEWS 卷:103
Integrated decision-support methodology for combined centralized-decentralized waste-to-energy management systems design
Article
Kuznetsova, Elizaveta1,3  Cardin, Michel-Alexandre2  Diao, Mingzhen1  Zhang, Sizhe1 
[1] Natl Univ Singapore, Dept Ind Syst Engn & Management, Singapore, Singapore
[2] Imperial Coll London, Dyson Sch Design Engn, 25 Exhibit Rd, London SW7 2DB, England
[3] Ecole Polytech, Dept Math & Ind Engn, Gerad, Montreal, PQ, Canada
关键词: Mega-cities;    Municipal solid waste;    Waste-to-energy;    Combined centralized-decentralized;    management systems;    Waste sources segregation;    Long-term planning;   
DOI  :  10.1016/j.rser.2018.12.020
来源: Elsevier
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【 摘 要 】

The rapid expansion of urban populations and concomitant increase in the generation of municipal solid waste (MSW) exert considerable pressure on the conventional centralized MSW management system and are beginning to exceed disposal capacities. To tackle this issue, the conventional centralized MSW management system is more likely to evolve toward a more decentralized system with smaller capacity waste treatment facilities that are integrated at different levels of the urban environment, e.g., buildings, districts, and municipalities. In addition, MSW can become an important urban resource to address the rising energy consumption through waste-to-energy (WTE) technologies capable of generating electricity, heat, and biogas. This shift toward the combined centralized-decentralized waste-to-energy management system (WtEMS) requires an adapted decision-support methodology (DSM) that can assist decision-makers in analyzing MSW generation across large urban territories and designing optimal long-term WtEMS. The proposed integrated DSM for WtEMS planning relies on: i) an MSW segregation and prediction methodology, ii) an optimization methodology for the deployment of multi-level urban waste infrastructure combining centralized and decentralized facilities, and iii) a multi-criterion sustainability framework for WtEMS assessment. The proposed DSM was tested on a case study that was located in Singapore. The proposed WtEMS not only reduced the total operational expenses by about 50%, but also increased revenues from electricity recovery by two times in comparison with the conventional MSW management system. It also allowed more optimal land use (capacity-land fragmentation was reduced by 74.8%) and reduced the size of the required transportation fleet by 15.3% in comparison with the conventional MSW system. The Global Warming Potential (GWP) was improved by about 18.7%.

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