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

Department of Electrical and Computer Engineering

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

3 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

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	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

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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 [8493801] 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; Naderi, Mohammad Salay; Ghadimi, Noradin; Naderi, Mehdi Salay.

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.

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, 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 https://doi.org/10.1109/EEEIC.2018.8493801

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

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AU - Abedinia, Oveis

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AU - Ghadimi, Noradin

AU - Naderi, Mehdi Salay

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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.

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

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Keywords

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