The energy-saving potential of an office under different pricing mechanisms - Application of an agent-based model
Authored by Haiyang Lin, Qinxing Wang, Yu Wang, Yiling Liu, Qie Sun, Ronald Wennersten
Date Published: 2017
DOI: 10.1016/j.apenergy.2017.05.140
Sponsors:
Chinese National Natural Science Foundation
Platforms:
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Model Documentation:
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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, be. 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. (C) 2017 Elsevier Ltd. All rights
reserved.
Tags
Agent-based model
Performance
China
Optimization
Demand
Electricity consumption
Residential buildings
Reform
Energy saving potential
Public building
Electricity
price
Energy system
District-heating systems
Air-conditioners
Household electricity