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An agent-based model is developed to estimate the potential of energy savings of an office room under different pricing mechanisms. For this aim, an energy balance model was developed to simulate the operation of air conditioner operation, the heat flux of different behavior and the electricity consumption of different types of appliances according different energy consumption patterns was investigated in detail. The total electricity consumption reduced 3.9%-17.1% under different pricing mechanisms. Light's energy saving potential is the biggest among the electric appliances. The maximum-saving behavior is investigated and the total energy saving potential of it is 26.91%. [ABSTRACT FROM AUTHOR]

At present, China's economic and social development is restricted by many factors, such as environmental pollution and the supply of energy, land resources and water resources. Compared with traditional terrestrial photovoltaic (PV) systems, floating PV systems can save a lot of land and water resources and obtain higher power generation efficiency. Although the academics have reached a general consensus about the advantages of floating systems, very few in-depth studies focus on the specifications of floating PV systems. Therefore, this study first discusses the development of PV technology, then studies the power generation efficiency of floating PV systems, and finally comprehensively analyzes the advantages and potential of floating PV systems in China. [ABSTRACT FROM AUTHOR]

Conventional approaches for modelling energy consumption for data center are limited to deal with the randomness, emergence and interdependence in energy systems. To fill the gap, an agent-based method was proposed and implemented to simulate the electricity consumption of a data center and to explore the potential of energy saving. The study found that a large amount of energy can be saved by dynamically operating the cooling load according to the practical load of the servers, namely 13% of the total energy consumption can be saved in the dynamic energy saving case (DESC) and 17% in the enhanced dynamic energy saving case (EDESC). The power usage effectiveness (PUE) of the data center can decrease from 1.71 in the original situation to 1.49 in the DESC and 1.42 in the EDESC. By contrast, the frequency of data backup has a heavy impact on the electricity consumption of the data center, while the frequency of computing tasks do not. [ABSTRACT FROM AUTHOR]