Forecasting Electricity Generation and Shares by Energy Resources by Time Series Analysis: A Case-Study of Turkey

Aziz Kemal Konyalıoğlu; Nuri Çelik

doi:10.1007/978-3-030-62784-3_10

Forecasting Electricity Generation and Shares by Energy Resources by Time Series Analysis: A Case-Study of Turkey

Aziz Kemal Konyalıoğlu^*, Nuri Çelik

^*Corresponding author for this work

Department of Management Engineering

Gebze Technical University

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

Abstract

Electricity generation has always been a debatable topic to investigate since industrialization grows up day by day. The accurate planning and directing of the system of supplying electricity depends on reliable modelling and forecasting. Better forecasting and modelling provide more efficient planning, more suitable investments of time, cost and performance and more satisfied customers and citizens. A suitable forecast model for electricity generation is a difficult process to perform, since it involves many parameters such as climate conditions, population, industrial tendency and habitualness of each country or region. In this paper, we tried to forecast electricity generation and shares by energy resources in Turkey by using Time Series Analysis in R software. The study provides not only an effective forecasting for electricity consumption in order to meet the demand in Turkey, but also an efficient segmentation according to the shares by energy resources since the usage of electricity differs from resources. The data, which correspond to the period 1970–2018, are used to forecast the electricity generation in Turkey.

Original language	English
Title of host publication	Digital Conversion on the Way to Industry 4.0 - Selected Papers from ISPR2020, 2020 Online - Turkey
Editors	Numan M. Durakbasa, M. Güneş Gençyılmaz
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	115-120
Number of pages	6
ISBN (Print)	9783030627836
DOIs	https://doi.org/10.1007/978-3-030-62784-3_10
Publication status	Published - 2021
Event	International Symposium for Production Research, ISPR 2020 - Antalya, Turkey Duration: 24 Sept 2020 → 26 Sept 2020

Publication series

Name	Lecture Notes in Mechanical Engineering
ISSN (Print)	2195-4356
ISSN (Electronic)	2195-4364

Conference

Conference	International Symposium for Production Research, ISPR 2020
Country/Territory	Turkey
City	Antalya
Period	24/09/20 → 26/09/20

Bibliographical note

Publisher Copyright:
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Box-Jenkins models
Electricity forecasting
Electricity generation
Time series analysis

UN SDGs

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

Access to Document

10.1007/978-3-030-62784-3_10

Cite this

Konyalıoğlu, A. K., & Çelik, N. (2021). Forecasting Electricity Generation and Shares by Energy Resources by Time Series Analysis: A Case-Study of Turkey. In N. M. Durakbasa, & M. G. Gençyılmaz (Eds.), Digital Conversion on the Way to Industry 4.0 - Selected Papers from ISPR2020, 2020 Online - Turkey (pp. 115-120). (Lecture Notes in Mechanical Engineering). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-62784-3_10

Konyalıoğlu, Aziz Kemal ; Çelik, Nuri. / Forecasting Electricity Generation and Shares by Energy Resources by Time Series Analysis : A Case-Study of Turkey. Digital Conversion on the Way to Industry 4.0 - Selected Papers from ISPR2020, 2020 Online - Turkey. editor / Numan M. Durakbasa ; M. Güneş Gençyılmaz. Springer Science and Business Media Deutschland GmbH, 2021. pp. 115-120 (Lecture Notes in Mechanical Engineering).

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title = "Forecasting Electricity Generation and Shares by Energy Resources by Time Series Analysis: A Case-Study of Turkey",

abstract = "Electricity generation has always been a debatable topic to investigate since industrialization grows up day by day. The accurate planning and directing of the system of supplying electricity depends on reliable modelling and forecasting. Better forecasting and modelling provide more efficient planning, more suitable investments of time, cost and performance and more satisfied customers and citizens. A suitable forecast model for electricity generation is a difficult process to perform, since it involves many parameters such as climate conditions, population, industrial tendency and habitualness of each country or region. In this paper, we tried to forecast electricity generation and shares by energy resources in Turkey by using Time Series Analysis in R software. The study provides not only an effective forecasting for electricity consumption in order to meet the demand in Turkey, but also an efficient segmentation according to the shares by energy resources since the usage of electricity differs from resources. The data, which correspond to the period 1970–2018, are used to forecast the electricity generation in Turkey.",

keywords = "Box-Jenkins models, Electricity forecasting, Electricity generation, Time series analysis",

author = "Konyalıoğlu, {Aziz Kemal} and Nuri {\c C}elik",

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Konyalıoğlu, AK & Çelik, N 2021, Forecasting Electricity Generation and Shares by Energy Resources by Time Series Analysis: A Case-Study of Turkey. in NM Durakbasa & MG Gençyılmaz (eds), Digital Conversion on the Way to Industry 4.0 - Selected Papers from ISPR2020, 2020 Online - Turkey. Lecture Notes in Mechanical Engineering, Springer Science and Business Media Deutschland GmbH, pp. 115-120, International Symposium for Production Research, ISPR 2020, Antalya, Turkey, 24/09/20. https://doi.org/10.1007/978-3-030-62784-3_10

Forecasting Electricity Generation and Shares by Energy Resources by Time Series Analysis: A Case-Study of Turkey. / Konyalıoğlu, Aziz Kemal; Çelik, Nuri.
Digital Conversion on the Way to Industry 4.0 - Selected Papers from ISPR2020, 2020 Online - Turkey. ed. / Numan M. Durakbasa; M. Güneş Gençyılmaz. Springer Science and Business Media Deutschland GmbH, 2021. p. 115-120 (Lecture Notes in Mechanical Engineering).

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

TY - GEN

T1 - Forecasting Electricity Generation and Shares by Energy Resources by Time Series Analysis

T2 - International Symposium for Production Research, ISPR 2020

AU - Konyalıoğlu, Aziz Kemal

AU - Çelik, Nuri

PY - 2021

Y1 - 2021

N2 - Electricity generation has always been a debatable topic to investigate since industrialization grows up day by day. The accurate planning and directing of the system of supplying electricity depends on reliable modelling and forecasting. Better forecasting and modelling provide more efficient planning, more suitable investments of time, cost and performance and more satisfied customers and citizens. A suitable forecast model for electricity generation is a difficult process to perform, since it involves many parameters such as climate conditions, population, industrial tendency and habitualness of each country or region. In this paper, we tried to forecast electricity generation and shares by energy resources in Turkey by using Time Series Analysis in R software. The study provides not only an effective forecasting for electricity consumption in order to meet the demand in Turkey, but also an efficient segmentation according to the shares by energy resources since the usage of electricity differs from resources. The data, which correspond to the period 1970–2018, are used to forecast the electricity generation in Turkey.

AB - Electricity generation has always been a debatable topic to investigate since industrialization grows up day by day. The accurate planning and directing of the system of supplying electricity depends on reliable modelling and forecasting. Better forecasting and modelling provide more efficient planning, more suitable investments of time, cost and performance and more satisfied customers and citizens. A suitable forecast model for electricity generation is a difficult process to perform, since it involves many parameters such as climate conditions, population, industrial tendency and habitualness of each country or region. In this paper, we tried to forecast electricity generation and shares by energy resources in Turkey by using Time Series Analysis in R software. The study provides not only an effective forecasting for electricity consumption in order to meet the demand in Turkey, but also an efficient segmentation according to the shares by energy resources since the usage of electricity differs from resources. The data, which correspond to the period 1970–2018, are used to forecast the electricity generation in Turkey.

KW - Box-Jenkins models

KW - Electricity forecasting

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KW - Time series analysis

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M3 - Conference contribution

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PB - Springer Science and Business Media Deutschland GmbH

Y2 - 24 September 2020 through 26 September 2020

ER -

Konyalıoğlu AK, Çelik N. Forecasting Electricity Generation and Shares by Energy Resources by Time Series Analysis: A Case-Study of Turkey. In Durakbasa NM, Gençyılmaz MG, editors, Digital Conversion on the Way to Industry 4.0 - Selected Papers from ISPR2020, 2020 Online - Turkey. Springer Science and Business Media Deutschland GmbH. 2021. p. 115-120. (Lecture Notes in Mechanical Engineering). doi: 10.1007/978-3-030-62784-3_10

Forecasting Electricity Generation and Shares by Energy Resources by Time Series Analysis: A Case-Study of Turkey

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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