“City Intelligent Energy and Transportation Network Policy” “Based on the Big Data Analysis”

“City Intelligent Energy and Transportation Network Policy” “Based on the Big Data Analysis”

Big Data

City Intelligent Energy Network

Distributed Energy

Multi-resource Model

The China sustainable development is the simultaneously three key facets, including urbanism, industrialization, and information. Building a Smart Low-carbon City is an energy strategy for the sustainable development of Chinese cities. One technology way for this strategy is the City Intelligent Energy Network (CIEN), supporting a green, ecological development of the Chinese cities. CIEN starts from the redistribute of city land-use, taking small gas turbine as the major power, combining with the new energy mode, such as solar energy, wind energy and low level energy (geothermal, ice cold storage, water cold storage). CIEN could supply relatively large network and grid with electricity, heat, and cold, realizing the efficient, integrate and gradable use of the energy network technology. As CIEN is on its starting point, so this kind of technology still need the combination work with the lab research and applicable field test. Considering the city unit scale, the transportation mode, energy resources, and the traditional mode to power grid and other factors, the key point is to balance the economical use and the resource capability and adaptability. This paper tries to use the 2007 statistical data including city economy, construction, population, and different energy parameter, to establish the comprehensive model. Combining the model results, the CIEN adaptability will be discussed, and meaningful policies will be proposed, with the focusing of how to build a Smart Low-carbon city.

85-92

32

Wang, Mingquan

Wang, Jun

Tian, Feng

The 5th International Conference on Ambient Systems, Networks and Technologies (ANT-2014), the 4th International Conference on Sustainable Energy Information Technology (SEIT-2014)

2014

journalArticle

1877-0509

10.1016/j.procs.2014.05.401