Multi-criteria optimization for the design and operation of distributed energy systems considering sustainability dimensions

被引:51
作者
Fonseca, Juan D. [1 ,3 ]
Commenge, Jean-Marc [2 ]
Camargo, Mauricio [1 ]
Falk, Laurent [2 ]
Gil, Ivan D. [3 ]
机构
[1] Univ Lorraine, Equipe Rech Proc Innovatifs ERPI, 8 Rue Bastien Lepage, F-54000 Nancy, France
[2] Univ Lorraine, Lab React & Genie Proc LRGP, 1 Rue Grandville,BP 20451, F-54001 Nancy, France
[3] Univ Nacl Colombia, Sede Bogota, Dept Chem & Environm Engn, Grp Proc Quim & Bioquim, Carrera 30 45-03, Bogota, Colombia
关键词
Renewable energy; Power-to-gas; Multi-energy system; Seasonal storage; Energy system design; Social criterion;
D O I
10.1016/j.energy.2020.118989
中图分类号
O414.1 [热力学];
学科分类号
摘要
The growing concerns about climate change and energy security have led to a shift in the paradigm of the energy framework. In this regard, distributed generation offers the possibility to deal with inefficiencies in energy delivering, and the fossil fuel dependence of conventional and centralized power plants. This work presents a modeling and multi-criteria optimization strategy for designing and operating decentralized power plants including different energy vectors. The modeling approach considers the time-varying operation of the energy conversion units for responding to electricity and hydrogen demands, along with the seasonal behavior of the storage system. A multi-criteria evaluation addressing economic, environmental and social aspects was implemented. The objective functions are the total annualized cost, the CO2 emissions and the grid dependence. According to optimization results, it is highlighted the influence of the assessed criteria upon the structure and the operating policy of the power plant. Additionally, by comparing the performance of the distributed energy system with respect to a centralized scenario, it is noted the significant potential of the decentralized generation. Indeed, depending on the optimization goal, CO2 emission reduction up to 89%, and self-sufficiency up to 81% can be achieved. (C) 2020 The Author(s). Published by Elsevier Ltd.
引用
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页数:16
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