TY - GEN
T1 - Power demand forecasting using meteorological data and human congestion information
AU - Hori, Maiya
AU - Goto, Takayuki
AU - Takano, Shigeru
AU - Taniguchi, Rin Ichiro
N1 - Funding Information:
This research was supported by the Japan Science and Technology Agency (JST) through its Center of Innovation: Science and Technology Based Radical Innovation and Entrepreneurship Program (COI STREAM).
Publisher Copyright:
© 2016 IEEE.
PY - 2016/12/22
Y1 - 2016/12/22
N2 - In this paper, we propose a method for forecasting power demand using meteorological data and human congestion information. In an energy management system (EMS), accurate power demand forecasts reduce the cost on the demand side and stabilize the power supply on the supply side. Although previously observed power consumption and meteorological data are conventionally used for forecasting power demand, it is difficult to estimate power demand in cases that are greatly affected by the behavior of people. Power consumption may vary according to the behavior of just one person, depending on the size of the community. In this study, the power demands of multiple buildings on the campus of a university are estimated accurately by analyzing heterogeneous data obtained with various sensors. Experiments show that using meteorological data and human congestion improves results. Consequently, we confirm that a cyber physical system can play an important role in the construction of an EMS.
AB - In this paper, we propose a method for forecasting power demand using meteorological data and human congestion information. In an energy management system (EMS), accurate power demand forecasts reduce the cost on the demand side and stabilize the power supply on the supply side. Although previously observed power consumption and meteorological data are conventionally used for forecasting power demand, it is difficult to estimate power demand in cases that are greatly affected by the behavior of people. Power consumption may vary according to the behavior of just one person, depending on the size of the community. In this study, the power demands of multiple buildings on the campus of a university are estimated accurately by analyzing heterogeneous data obtained with various sensors. Experiments show that using meteorological data and human congestion improves results. Consequently, we confirm that a cyber physical system can play an important role in the construction of an EMS.
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U2 - 10.1109/CPSNA.2016.14
DO - 10.1109/CPSNA.2016.14
M3 - Conference contribution
AN - SCOPUS:85011281112
T3 - Proceedings - 4th IEEE International Conference on Cyber-Physical Systems, Networks, and Applications, CPSNA 2016
SP - 29
EP - 32
BT - Proceedings - 4th IEEE International Conference on Cyber-Physical Systems, Networks, and Applications, CPSNA 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Cyber-Physical Systems, Networks, and Applications, CPSNA 2016
Y2 - 6 October 2016 through 7 October 2016
ER -