• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.11
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• pp.580-591
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• 2017

In accordance with 2015 Paris agreement, each individual country around the world should voluntarily propose not only its (individual) reduction target, but also actively develop and present expansion targets of its scope and concrete reduction goals exceeding the previous ones. Accordingly, it is necessary to prepare a macroscopic, long-range strategy for reducing energy consumption and greenhouse gas emissions, which can cover a single building, town, city and eventually even a province. The purpose of this research is to gather and compile government-acquired data from various sources and (in accordance with contents and specificity), combine building data by stages by using multi-variable matrix and then analyze the significance of combined data for each stage. The first order data presents the probability and the cost effectiveness of energy saving on the scale of a city or a province, based only upon general information, size and power consumption of buildings. The second order data can identify a pattern of energy consumption for a building of a specific purpose and which tends to consume a larger amount of energy during one particular season (than others). Finally, the third order data can derive influential factors (base load, humidity) from the energy consumption pattern of a building, and thus propose an informed and practical energy-saving method to be applied in real time.