Prediction interval based on type-2 fuzzy systems for wind power generation and loads in microgrid control design

Luis G. Marín; Felipe Valencia; Doris Sáez

doi:10.1109/FUZZ-IEEE.2016.7737705

Prediction interval based on type-2 fuzzy systems for wind power generation and loads in microgrid control design

Luis G. Marín
, Felipe Valencia
, Doris Sáez

Universidad de Chile

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

32 Scopus citations

Abstract

An important issue in the operation of isolated microgrids is how to properly address the uncertainties associated with renewable resources and loads. In this work, a new interval prediction model based on type-2 fuzzy systems is derived for capturing these uncertainties. This model provides the upper and lower boundaries of the predicted values with a certain coverage probability, as well as their expected values. This information could be used in the design of microgrid controllers, such as energy management systems. The proposed method is applied to forecast the wind power generation and the loads of the Huatacondo microgrid, which is located in northern Chile. A comparison with both linear and Takagi-Sugeno fuzzy interval models is also performed.

Original language	English
Title of host publication	2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	328-335
Number of pages	8
ISBN (Electronic)	9781509006250
DOIs	https://doi.org/10.1109/FUZZ-IEEE.2016.7737705
State	Published - 07 Nov 2016
Externally published	Yes
Event	2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016 - Vancouver, Canada Duration: 24 Jul 2016 → 29 Jul 2016

Publication series

Name	2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016

Conference

Conference	2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016
Country/Territory	Canada
City	Vancouver
Period	24/07/16 → 29/07/16

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Energy management system
Fuzzy systems
Microgrid
Prediction interval
Renewable energy

Access to Document

10.1109/FUZZ-IEEE.2016.7737705

Cite this

Marín, L. G., Valencia, F., & Sáez, D. (2016). Prediction interval based on type-2 fuzzy systems for wind power generation and loads in microgrid control design. In 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016 (pp. 328-335). Article 7737705 (2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FUZZ-IEEE.2016.7737705

Marín, Luis G. ; Valencia, Felipe ; Sáez, Doris. / Prediction interval based on type-2 fuzzy systems for wind power generation and loads in microgrid control design. 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 328-335 (2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016).

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title = "Prediction interval based on type-2 fuzzy systems for wind power generation and loads in microgrid control design",

abstract = "An important issue in the operation of isolated microgrids is how to properly address the uncertainties associated with renewable resources and loads. In this work, a new interval prediction model based on type-2 fuzzy systems is derived for capturing these uncertainties. This model provides the upper and lower boundaries of the predicted values with a certain coverage probability, as well as their expected values. This information could be used in the design of microgrid controllers, such as energy management systems. The proposed method is applied to forecast the wind power generation and the loads of the Huatacondo microgrid, which is located in northern Chile. A comparison with both linear and Takagi-Sugeno fuzzy interval models is also performed.",

keywords = "Energy management system, Fuzzy systems, Microgrid, Prediction interval, Renewable energy",

author = "Mar{\'i}n, \{Luis G.\} and Felipe Valencia and Doris S{\'a}ez",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016 ; Conference date: 24-07-2016 Through 29-07-2016",

year = "2016",

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language = "English",

series = "2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016",

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Marín, LG, Valencia, F & Sáez, D 2016, Prediction interval based on type-2 fuzzy systems for wind power generation and loads in microgrid control design. in 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016., 7737705, 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016, Institute of Electrical and Electronics Engineers Inc., pp. 328-335, 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016, Vancouver, Canada, 24/07/16. https://doi.org/10.1109/FUZZ-IEEE.2016.7737705

Prediction interval based on type-2 fuzzy systems for wind power generation and loads in microgrid control design. / Marín, Luis G.; Valencia, Felipe; Sáez, Doris.
2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 328-335 7737705 (2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016).

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

TY - GEN

T1 - Prediction interval based on type-2 fuzzy systems for wind power generation and loads in microgrid control design

AU - Marín, Luis G.

AU - Valencia, Felipe

AU - Sáez, Doris

PY - 2016/11/7

Y1 - 2016/11/7

N2 - An important issue in the operation of isolated microgrids is how to properly address the uncertainties associated with renewable resources and loads. In this work, a new interval prediction model based on type-2 fuzzy systems is derived for capturing these uncertainties. This model provides the upper and lower boundaries of the predicted values with a certain coverage probability, as well as their expected values. This information could be used in the design of microgrid controllers, such as energy management systems. The proposed method is applied to forecast the wind power generation and the loads of the Huatacondo microgrid, which is located in northern Chile. A comparison with both linear and Takagi-Sugeno fuzzy interval models is also performed.

AB - An important issue in the operation of isolated microgrids is how to properly address the uncertainties associated with renewable resources and loads. In this work, a new interval prediction model based on type-2 fuzzy systems is derived for capturing these uncertainties. This model provides the upper and lower boundaries of the predicted values with a certain coverage probability, as well as their expected values. This information could be used in the design of microgrid controllers, such as energy management systems. The proposed method is applied to forecast the wind power generation and the loads of the Huatacondo microgrid, which is located in northern Chile. A comparison with both linear and Takagi-Sugeno fuzzy interval models is also performed.

KW - Energy management system

KW - Fuzzy systems

KW - Microgrid

KW - Prediction interval

KW - Renewable energy

UR - https://www.scopus.com/pages/publications/85006810403

U2 - 10.1109/FUZZ-IEEE.2016.7737705

DO - 10.1109/FUZZ-IEEE.2016.7737705

M3 - Conference contribution

AN - SCOPUS:85006810403

T3 - 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016

SP - 328

EP - 335

BT - 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016

Y2 - 24 July 2016 through 29 July 2016

ER -

Marín LG, Valencia F, Sáez D. Prediction interval based on type-2 fuzzy systems for wind power generation and loads in microgrid control design. In 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 328-335. 7737705. (2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016). doi: 10.1109/FUZZ-IEEE.2016.7737705

Prediction interval based on type-2 fuzzy systems for wind power generation and loads in microgrid control design

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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