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Research Papers

Urban Building Energy Planning With Space Distribution and Time Dynamic Simulation

[+] Author and Article Information
Lin Fu, Zhonghai Zheng, Hongfa Di, Yi Jiang

Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, PR China

J. Sol. Energy Eng 131(3), 031014 (Jul 14, 2009) (6 pages) doi:10.1115/1.3142725 History: Received August 28, 2008; Revised November 08, 2008; Published July 14, 2009

It is important to deal with energy saving in buildings of one city level, and plan the energy system from one building to one city level. We strongly suggest conducting urban building energy planning (UBEP) in the urban planning field in China. There are two main characteristics of an urban building energy system. First, the terminal building energy demand is dynamically timely. Second, the energy demand, energy sources supply, energy equipments, and networks of heating, cooling, gas, and electricity, are distributed in an urban space. It is meaningful to conduct an innovative urban energy planning with space distribution and time dynamic simulation. Therefore, an UBEP simulation tool, developed by our research group, is introduced. Finally, a case of energy planning in Beijing City in 2010 for heating and air conditioning system is dynamically simulated and analyzed. To meet the same building energy demand in Beijing, such as heating, air conditioning, gas, and electricity, different energy equipments, such as boiler, combined heating and power, combined cooling, heating, and power system, and heat pump based on different energy sources, such as coal, gas, and electricity, should be planned alternatively. Also, an optimum urban energy system with high energy efficiency and low environmental emission can be achieved. This simulation tool contains most models of heating and cooling energy systems in China. We can validate the models with statistical data from previous or present simulation, and the simulation results in future planning can serve as guidance for the construction of municipal energy infrastructure. We can conclude that simulation in time dimension shows the characteristics of dynamic load in each nodes of the energy flow. The objective is to present the comparison of different scenarios and optimize the planning schemes.

Copyright © 2009 by American Society of Mechanical Engineers
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References

Figures

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Figure 5

Flow chart of an innovative UBEP method

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Figure 6

The load density in space in heating planning of a certain district in China (with the use of ESRI ARCGIS )

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Figure 7

The yearly average NOx ground concentration (μg/m3) in heating planning of a certain city in China (with the use of ISCST3 with GIS)

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Figure 8

The multilayer energy system model of CHP

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Figure 4

Heating planning in Beijing city (2004–2020)

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Figure 3

Typical dynamic heating and cooling load of residential and commercial buildings in Beijing city (with the use of DEST software)

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Figure 11

The structure of city central heating source in 2001 and 2010

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Figure 12

The dynamic coal and gas consumption in 2010

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Figure 13

The dynamic SO2 and NOx emission in 2010

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Figure 14

The comparison of energy consumption between 2001 and 2010

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Figure 15

The comparison of environment emission between 2001 and 2010

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Figure 2

Dispersed or distributed building energy system

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Figure 1

Central and district building energy system

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Figure 9

Simplification of the multilayer energy system model and directed energy flow from energy source, energy conversion equipment, network to user or building. Where 1=Coal fired power plant, 2=Combined heating and power, 3=Oil-fired boiler, 4=Gas-fired boiler, 5=Household gas furnace, 6=Heating network, 7=Electricity network, 8=user or building

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Figure 10

The operation strategy of multiheat sources during heating season

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