کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4376245 | 1617495 | 2013 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Maximizing the use of energy in cities using an open systems network approach Maximizing the use of energy in cities using an open systems network approach](/preview/png/4376245.png)
The ability of cities to extract useful work from energy imports is analyzed by considering all of the flows of energy within the city as an ecological network and by accounting for the role the second law of thermodynamics plays in open systems such as cities. We construct a new procedure for generating a variety of flow balanced random networks to test the role that the network structure has on the city's ability to constructively destroy exergy, the useful component of energy in a process. We consider two network types, Erdös–Rényi and scale-free networks, and illustrate how these types, and the various realizations of these types as defined by their control parameters, impact the quantity of exergy destroyed. Specifically we find that the Erdös–Rényi network is best equipped to destroy exergy, but that the scale-free network provides more certainty in this ability for networks that are sparsely connected. This trade-off between the exergy destruction and certainty is observed in a study of Toronto. Overall the findings suggest that the selection of network topology in the development of open systems is an important factor (among others) in the successful development of open systems, their sustainability, and their ability to achieve maximum work extraction from energy imports.
► Flow-balanced and open system networks established to maximize urban energy use.
► Provide method to generate thermodynamic random networks of various topologies.
► Show that city of Toronto exergy network is near scale-free.
► Erdös–Rényi topology extracts more work than scale-free, but with more variability.
► Topology selection involves trade-off between average work extraction and variability.
Journal: Ecological Modelling - Volume 250, 10 February 2013, Pages 155–164