Cloud Motion Forecasting and Cloud Base Height Estimation Using Two Low-Cost Sky Cameras

Can Zhang; Yang Du; Xiaoyang Chen; Eng Gee Lim

doi:10.1109/EI2.2018.8582657

Cloud Motion Forecasting and Cloud Base Height Estimation Using Two Low-Cost Sky Cameras

Can Zhang
, Yang Du
, Xiaoyang Chen
, Eng Gee Lim

Xi'an Jiaotong-Liverpool University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

11 Citations (Scopus)

Abstract

Passing cloud results in rapid irradiance changes. The intermittency of PV output power has drawn serious concern as the PV system installation increases. Consequently, power ramp-rate control (PRRC) is introduced as the regulation to limit significant power fluctuations. These requirements are driving an increasing demand for ultra short-term PV power forecasting. Sky imager has been used as an effective tool to predict the cloud motion, then to forecast the PV power. However, the high cost of sky imager system and low update frequency are still hindering its application in PRRC. The estimation of cloud base height (CBH) is also a challenging using sky imager. In this paper, a low-cost cloud motion tracking system has been developed. Ultra short-term cloud motion forecasting has been achieved in seconds level which can be used in PRRC application. The proposed cloud tracking method improves the forecasting accuracy by multiple cloud centroid tracking. Secondly, a novel sky camera based CBH estimation method is proposed. The effectiveness of the proposed CBH estimation method has been verified by experiment results.

Original language	English
Title of host publication	2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538685495
DOIs	https://doi.org/10.1109/EI2.2018.8582657
Publication status	Published - 19 Dec 2018
Event	2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Beijing, China Duration: 20 Oct 2018 → 22 Oct 2018

Publication series

Name	2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings

Conference

Conference	2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018
Country/Territory	China
City	Beijing
Period	20/10/18 → 22/10/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

cloud base height estimation
cloud motion vector tracking
solar power ramp-rate control
ultra short-time forecasting

Access to Document

10.1109/EI2.2018.8582657

Cite this

Zhang, C., Du, Y., Chen, X., & Lim, E. G. (2018). Cloud Motion Forecasting and Cloud Base Height Estimation Using Two Low-Cost Sky Cameras. In 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings Article 8582657 (2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EI2.2018.8582657

Zhang, Can ; Du, Yang ; Chen, Xiaoyang et al. / Cloud Motion Forecasting and Cloud Base Height Estimation Using Two Low-Cost Sky Cameras. 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. (2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings).

@inproceedings{8092a8f73b0447868235ec85ea786703,

title = "Cloud Motion Forecasting and Cloud Base Height Estimation Using Two Low-Cost Sky Cameras",

abstract = "Passing cloud results in rapid irradiance changes. The intermittency of PV output power has drawn serious concern as the PV system installation increases. Consequently, power ramp-rate control (PRRC) is introduced as the regulation to limit significant power fluctuations. These requirements are driving an increasing demand for ultra short-term PV power forecasting. Sky imager has been used as an effective tool to predict the cloud motion, then to forecast the PV power. However, the high cost of sky imager system and low update frequency are still hindering its application in PRRC. The estimation of cloud base height (CBH) is also a challenging using sky imager. In this paper, a low-cost cloud motion tracking system has been developed. Ultra short-term cloud motion forecasting has been achieved in seconds level which can be used in PRRC application. The proposed cloud tracking method improves the forecasting accuracy by multiple cloud centroid tracking. Secondly, a novel sky camera based CBH estimation method is proposed. The effectiveness of the proposed CBH estimation method has been verified by experiment results.",

keywords = "cloud base height estimation, cloud motion vector tracking, solar power ramp-rate control, ultra short-time forecasting",

author = "Can Zhang and Yang Du and Xiaoyang Chen and Lim, \{Eng Gee\}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 ; Conference date: 20-10-2018 Through 22-10-2018",

year = "2018",

month = dec,

day = "19",

doi = "10.1109/EI2.2018.8582657",

language = "English",

series = "2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings",

}

Zhang, C, Du, Y, Chen, X & Lim, EG 2018, Cloud Motion Forecasting and Cloud Base Height Estimation Using Two Low-Cost Sky Cameras. in 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings., 8582657, 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018, Beijing, China, 20/10/18. https://doi.org/10.1109/EI2.2018.8582657

Cloud Motion Forecasting and Cloud Base Height Estimation Using Two Low-Cost Sky Cameras. / Zhang, Can; Du, Yang; Chen, Xiaoyang et al.
2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8582657 (2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - Cloud Motion Forecasting and Cloud Base Height Estimation Using Two Low-Cost Sky Cameras

AU - Zhang, Can

AU - Du, Yang

AU - Chen, Xiaoyang

AU - Lim, Eng Gee

PY - 2018/12/19

Y1 - 2018/12/19

N2 - Passing cloud results in rapid irradiance changes. The intermittency of PV output power has drawn serious concern as the PV system installation increases. Consequently, power ramp-rate control (PRRC) is introduced as the regulation to limit significant power fluctuations. These requirements are driving an increasing demand for ultra short-term PV power forecasting. Sky imager has been used as an effective tool to predict the cloud motion, then to forecast the PV power. However, the high cost of sky imager system and low update frequency are still hindering its application in PRRC. The estimation of cloud base height (CBH) is also a challenging using sky imager. In this paper, a low-cost cloud motion tracking system has been developed. Ultra short-term cloud motion forecasting has been achieved in seconds level which can be used in PRRC application. The proposed cloud tracking method improves the forecasting accuracy by multiple cloud centroid tracking. Secondly, a novel sky camera based CBH estimation method is proposed. The effectiveness of the proposed CBH estimation method has been verified by experiment results.

AB - Passing cloud results in rapid irradiance changes. The intermittency of PV output power has drawn serious concern as the PV system installation increases. Consequently, power ramp-rate control (PRRC) is introduced as the regulation to limit significant power fluctuations. These requirements are driving an increasing demand for ultra short-term PV power forecasting. Sky imager has been used as an effective tool to predict the cloud motion, then to forecast the PV power. However, the high cost of sky imager system and low update frequency are still hindering its application in PRRC. The estimation of cloud base height (CBH) is also a challenging using sky imager. In this paper, a low-cost cloud motion tracking system has been developed. Ultra short-term cloud motion forecasting has been achieved in seconds level which can be used in PRRC application. The proposed cloud tracking method improves the forecasting accuracy by multiple cloud centroid tracking. Secondly, a novel sky camera based CBH estimation method is proposed. The effectiveness of the proposed CBH estimation method has been verified by experiment results.

KW - cloud base height estimation

KW - cloud motion vector tracking

KW - solar power ramp-rate control

KW - ultra short-time forecasting

UR - https://www.scopus.com/pages/publications/85060884422

U2 - 10.1109/EI2.2018.8582657

DO - 10.1109/EI2.2018.8582657

M3 - Conference Proceeding

AN - SCOPUS:85060884422

T3 - 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings

BT - 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018

Y2 - 20 October 2018 through 22 October 2018

ER -

Zhang C, Du Y, Chen X , Lim EG. Cloud Motion Forecasting and Cloud Base Height Estimation Using Two Low-Cost Sky Cameras. In 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. 8582657. (2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings). doi: 10.1109/EI2.2018.8582657

Cloud Motion Forecasting and Cloud Base Height Estimation Using Two Low-Cost Sky Cameras

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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