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The energy-saving potential of an office under different pricing mechanisms – Application of an agent-based model

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  • Lin, Haiyang
  • Wang, Qinxing
  • Wang, Yu
  • Liu, Yiling
  • Sun, Qie
  • Wennersten, Ronald

Abstract

This paper developed an agent-based model (ABM) to explore the energy saving potentials (ESPs) of various types of appliances in offices under different pricing mechanisms. The model included four types of commonly used appliances in office buildings: an air conditioner (AC), computers, lights and a basic load. The total ESPs of the entire office are 6.7% and 17.4% on the second and the third price tier of the tiered pricing mechanism (TEP), while the ESPs are 11.8% and 14.2% under the peak-valley pricing (PVP) and critical peak pricing (CPP), respectively. Within different types of appliances, AC consumes the largest amount of electricity, over 50%, while the ESPs of the AC under different pricing mechanisms are only 6.9–12.1%. In contrast, the lights have the biggest ESP, i.e. 14.1–53.4%, under various pricing levels. Both the pricing mechanisms of PVP and CPP only have the effect of peak clipping and do not have a significant effect of valley filling, since there is no people working in the office during the valley price period. The maximum ESP, which is based on people’s maximum-saving behavior, is much larger than the ESPs on the basis of people’s ordinary consumption patterns. This implies the importance of improving people’s awareness of energy saving and refining their behaviors. Lastly, the model developed in this study provides a generic platform for simulating many types of energy systems and is very effective for handling the complicated relations between different types of technology and the way how they are used and interacted with each other. ABMs have very good adaptability and capacity in simulating energy systems.

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  • Lin, Haiyang & Wang, Qinxing & Wang, Yu & Liu, Yiling & Sun, Qie & Wennersten, Ronald, 2017. "The energy-saving potential of an office under different pricing mechanisms – Application of an agent-based model," Applied Energy, Elsevier, vol. 202(C), pages 248-258.
    • Handle: RePEc:eee:appene:v:202:y:2017:i:c:p:248-258
    DOI: 10.1016/j.apenergy.2017.05.140
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