Markov models based short term forecasting of wind speed for estimating day-ahead wind power

Samidha Mridul Verma; Vasanth Reddy; Kusum Verma; Rajesh Kumar

doi:10.1109/ICPECTS.2018.8521645

Markov models based short term forecasting of wind speed for estimating day-ahead wind power

Samidha Mridul Verma
, Vasanth Reddy
, Kusum Verma
, Rajesh Kumar

Malaviya National Institute of Technology

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

30 Citations (Scopus)

Abstract

In order to meet the growing demand of energy, renewable resource utilization has increased in recent years. Wind is the source to a significant percentage of renewable resources and wind farms harvest this energy into electricity with the help of wind turbines. These turbines are very costly to set up and require high amount of maintenance. Accurate short term (from 30 minutes up to 6 hours ahead) wind energy forecasting is therefore important for optimal scheduling of the wind farms. The paper explores the usage of Markov Chains for forecasting wind speed during a short-term period (day-ahead hourly wind generation forecasts for an individual wind farm). The proposed prediction model depends on one variable factor - wind speed, for a specific wind turbine. The geographical location under study is taken at Jodhpur in Rajasthan, India. The performance evaluation of the proposed method is calculated using the different statistical error measures like RMSE, MAPE and MAE.

Original language	English
Title of host publication	Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	31-35
Number of pages	5
ISBN (Electronic)	9781538638170
DOIs	https://doi.org/10.1109/ICPECTS.2018.8521645
Publication status	Published - 2 Nov 2018
Externally published	Yes
Event	1st International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018 - Chennai, India Duration: 22 Feb 2018 → 23 Feb 2018

Publication series

Name	Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018

Conference

Conference	1st International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018
Country/Territory	India
City	Chennai
Period	22/02/18 → 23/02/18

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Markov chain
Short term forecasting
Wind farm
Wind forecasting
Wind power

ASJC Scopus subject areas

Computer Networks and Communications
Energy Engineering and Power Technology
Control and Systems Engineering
Electrical and Electronic Engineering
Mechanical Engineering
Control and Optimization

Access to Document

10.1109/ICPECTS.2018.8521645

Cite this

Verma, S. M., Reddy, V., Verma, K., & Kumar, R. (2018). Markov models based short term forecasting of wind speed for estimating day-ahead wind power. In Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018 (pp. 31-35). Article 8521645 (Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPECTS.2018.8521645

Verma, Samidha Mridul ; Reddy, Vasanth ; Verma, Kusum et al. / Markov models based short term forecasting of wind speed for estimating day-ahead wind power. Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 31-35 (Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018).

@inproceedings{3aeb3a08e0b94728a0d47f4ae5b43ddf,

title = "Markov models based short term forecasting of wind speed for estimating day-ahead wind power",

abstract = "In order to meet the growing demand of energy, renewable resource utilization has increased in recent years. Wind is the source to a significant percentage of renewable resources and wind farms harvest this energy into electricity with the help of wind turbines. These turbines are very costly to set up and require high amount of maintenance. Accurate short term (from 30 minutes up to 6 hours ahead) wind energy forecasting is therefore important for optimal scheduling of the wind farms. The paper explores the usage of Markov Chains for forecasting wind speed during a short-term period (day-ahead hourly wind generation forecasts for an individual wind farm). The proposed prediction model depends on one variable factor - wind speed, for a specific wind turbine. The geographical location under study is taken at Jodhpur in Rajasthan, India. The performance evaluation of the proposed method is calculated using the different statistical error measures like RMSE, MAPE and MAE.",

keywords = "Markov chain, Short term forecasting, Wind farm, Wind forecasting, Wind power",

author = "Verma, \{Samidha Mridul\} and Vasanth Reddy and Kusum Verma and Rajesh Kumar",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 1st International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018 ; Conference date: 22-02-2018 Through 23-02-2018",

year = "2018",

month = nov,

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doi = "10.1109/ICPECTS.2018.8521645",

language = "English",

series = "Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018",

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Verma, SM, Reddy, V, Verma, K & Kumar, R 2018, Markov models based short term forecasting of wind speed for estimating day-ahead wind power. in Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018., 8521645, Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018, Institute of Electrical and Electronics Engineers Inc., pp. 31-35, 1st International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018, Chennai, India, 22/02/18. https://doi.org/10.1109/ICPECTS.2018.8521645

Markov models based short term forecasting of wind speed for estimating day-ahead wind power. / Verma, Samidha Mridul; Reddy, Vasanth; Verma, Kusum et al.
Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 31-35 8521645 (Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018).

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

TY - GEN

T1 - Markov models based short term forecasting of wind speed for estimating day-ahead wind power

AU - Verma, Samidha Mridul

AU - Reddy, Vasanth

AU - Verma, Kusum

AU - Kumar, Rajesh

PY - 2018/11/2

Y1 - 2018/11/2

N2 - In order to meet the growing demand of energy, renewable resource utilization has increased in recent years. Wind is the source to a significant percentage of renewable resources and wind farms harvest this energy into electricity with the help of wind turbines. These turbines are very costly to set up and require high amount of maintenance. Accurate short term (from 30 minutes up to 6 hours ahead) wind energy forecasting is therefore important for optimal scheduling of the wind farms. The paper explores the usage of Markov Chains for forecasting wind speed during a short-term period (day-ahead hourly wind generation forecasts for an individual wind farm). The proposed prediction model depends on one variable factor - wind speed, for a specific wind turbine. The geographical location under study is taken at Jodhpur in Rajasthan, India. The performance evaluation of the proposed method is calculated using the different statistical error measures like RMSE, MAPE and MAE.

AB - In order to meet the growing demand of energy, renewable resource utilization has increased in recent years. Wind is the source to a significant percentage of renewable resources and wind farms harvest this energy into electricity with the help of wind turbines. These turbines are very costly to set up and require high amount of maintenance. Accurate short term (from 30 minutes up to 6 hours ahead) wind energy forecasting is therefore important for optimal scheduling of the wind farms. The paper explores the usage of Markov Chains for forecasting wind speed during a short-term period (day-ahead hourly wind generation forecasts for an individual wind farm). The proposed prediction model depends on one variable factor - wind speed, for a specific wind turbine. The geographical location under study is taken at Jodhpur in Rajasthan, India. The performance evaluation of the proposed method is calculated using the different statistical error measures like RMSE, MAPE and MAE.

KW - Markov chain

KW - Short term forecasting

KW - Wind farm

KW - Wind forecasting

KW - Wind power

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U2 - 10.1109/ICPECTS.2018.8521645

DO - 10.1109/ICPECTS.2018.8521645

M3 - Conference contribution

AN - SCOPUS:85057596748

T3 - Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018

SP - 31

EP - 35

BT - Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 1st International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018

Y2 - 22 February 2018 through 23 February 2018

ER -

Verma SM, Reddy V, Verma K, Kumar R. Markov models based short term forecasting of wind speed for estimating day-ahead wind power. In Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 31-35. 8521645. (Proceedings of the International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2018). doi: 10.1109/ICPECTS.2018.8521645

Markov models based short term forecasting of wind speed for estimating day-ahead wind power

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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