Impacts of Renewable Energy Sources by Battery Forecasting on Smart Power Systems

Mehdi Bagheri; Venera Nurmanova; Oveis Abedinia; Mohammad Salay Naderi; Noradin Ghadimi; Mehdi Salay Naderi

doi:10.1109/EEEIC.2018.8493801

Impacts of Renewable Energy Sources by Battery Forecasting on Smart Power Systems

Mehdi Bagheri, Venera Nurmanova, Oveis Abedinia, Mohammad Salay Naderi, Noradin Ghadimi, Mehdi Salay Naderi

School of Engineering and Digital Sciences

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

13 Citations (Scopus)

Abstract

In this work the impacts of lead acid batteries by considering renewable sources (i.e., solar and wind energies) on power system is presented. First of all, we modeled the power system by lead-acid battery in stand-alone synthetic solar and wind production model and then the suggested forecasting model will be applied on wind and solar to estimate the available output power of each units. After that, the prediction subject will be calculated that is taken as constraint status based state of charge (SOC) of the batteries. The proposed solution includes of filtering the candidate inputs, synthetic prediction model based honey bee mating optimization (HBMO). By this method, the SOC of batteries will be in appropriate range and the on-or-off switching number of wind turbines and PV modules will be reduced. The suggested model is compared with methods to show the validity of suggested strategy.

Original language	English
Title of host publication	Proceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538651858
DOIs	https://doi.org/10.1109/EEEIC.2018.8493801
Publication status	Published - Oct 16 2018
Event	2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018 - Palermo, Italy Duration: Jun 12 2018 → Jun 15 2018

Publication series

Name	Proceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018

Other

Other	2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018
Country/Territory	Italy
City	Palermo
Period	6/12/18 → 6/15/18

Keywords

Feature Selection
Forecasting
Lead acid battery
State of charge

ASJC Scopus subject areas

Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering
Industrial and Manufacturing Engineering
Environmental Engineering
Hardware and Architecture

UN SDGs

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

Access to Document

10.1109/EEEIC.2018.8493801

Cite this

Bagheri, M., Nurmanova, V., Abedinia, O., Naderi, M. S., Ghadimi, N., & Naderi, M. S. (2018). Impacts of Renewable Energy Sources by Battery Forecasting on Smart Power Systems. In Proceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018 Article 8493801 (Proceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EEEIC.2018.8493801

Impacts of Renewable Energy Sources by Battery Forecasting on Smart Power Systems. / Bagheri, Mehdi; Nurmanova, Venera; Abedinia, Oveis et al.
Proceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8493801 (Proceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018).

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

Bagheri, M, Nurmanova, V, Abedinia, O, Naderi, MS, Ghadimi, N & Naderi, MS 2018, Impacts of Renewable Energy Sources by Battery Forecasting on Smart Power Systems. in Proceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018., 8493801, Proceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018, Institute of Electrical and Electronics Engineers Inc., 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018, Palermo, Italy, 6/12/18. https://doi.org/10.1109/EEEIC.2018.8493801

Bagheri M, Nurmanova V, Abedinia O, Naderi MS, Ghadimi N, Naderi MS. Impacts of Renewable Energy Sources by Battery Forecasting on Smart Power Systems. In Proceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8493801. (Proceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018). doi: 10.1109/EEEIC.2018.8493801

Bagheri, Mehdi ; Nurmanova, Venera ; Abedinia, Oveis et al. / Impacts of Renewable Energy Sources by Battery Forecasting on Smart Power Systems. Proceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018. Institute of Electrical and Electronics Engineers Inc., 2018. (Proceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018).

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abstract = "In this work the impacts of lead acid batteries by considering renewable sources (i.e., solar and wind energies) on power system is presented. First of all, we modeled the power system by lead-acid battery in stand-alone synthetic solar and wind production model and then the suggested forecasting model will be applied on wind and solar to estimate the available output power of each units. After that, the prediction subject will be calculated that is taken as constraint status based state of charge (SOC) of the batteries. The proposed solution includes of filtering the candidate inputs, synthetic prediction model based honey bee mating optimization (HBMO). By this method, the SOC of batteries will be in appropriate range and the on-or-off switching number of wind turbines and PV modules will be reduced. The suggested model is compared with methods to show the validity of suggested strategy.",

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author = "Mehdi Bagheri and Venera Nurmanova and Oveis Abedinia and Naderi, {Mohammad Salay} and Noradin Ghadimi and Naderi, {Mehdi Salay}",

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AU - Bagheri, Mehdi

AU - Nurmanova, Venera

AU - Abedinia, Oveis

AU - Naderi, Mohammad Salay

AU - Ghadimi, Noradin

AU - Naderi, Mehdi Salay

PY - 2018/10/16

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N2 - In this work the impacts of lead acid batteries by considering renewable sources (i.e., solar and wind energies) on power system is presented. First of all, we modeled the power system by lead-acid battery in stand-alone synthetic solar and wind production model and then the suggested forecasting model will be applied on wind and solar to estimate the available output power of each units. After that, the prediction subject will be calculated that is taken as constraint status based state of charge (SOC) of the batteries. The proposed solution includes of filtering the candidate inputs, synthetic prediction model based honey bee mating optimization (HBMO). By this method, the SOC of batteries will be in appropriate range and the on-or-off switching number of wind turbines and PV modules will be reduced. The suggested model is compared with methods to show the validity of suggested strategy.

AB - In this work the impacts of lead acid batteries by considering renewable sources (i.e., solar and wind energies) on power system is presented. First of all, we modeled the power system by lead-acid battery in stand-alone synthetic solar and wind production model and then the suggested forecasting model will be applied on wind and solar to estimate the available output power of each units. After that, the prediction subject will be calculated that is taken as constraint status based state of charge (SOC) of the batteries. The proposed solution includes of filtering the candidate inputs, synthetic prediction model based honey bee mating optimization (HBMO). By this method, the SOC of batteries will be in appropriate range and the on-or-off switching number of wind turbines and PV modules will be reduced. The suggested model is compared with methods to show the validity of suggested strategy.

KW - Feature Selection

KW - Forecasting

KW - Lead acid battery

KW - State of charge

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Impacts of Renewable Energy Sources by Battery Forecasting on Smart Power Systems

Abstract

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Keywords

ASJC Scopus subject areas

UN SDGs

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