Electricity Demand Forecasting Using Regression Techniques

Wani, Tanveer Ahmad; Shiraz, Mohd

doi:10.1007/978-981-13-7557-6_9

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…Untuk meramalkan konsumsi listrik industri maquiladora negara bagian perbatasan Meksiko, model regresi linier berganda digunakan menggunakan alat regresi Microsoft Excel. Metode regresi berganda ketika diterapkan pada data permintaan listrik India menuai hasil yang cukup sebanding dengan teknik penggunaan akhir parsial [16]. Untuk Afrika Selatan, penggunaan kerangka pemodelan regresi-SARIMA mengungkapkan beberapa variabel penting yang mengatur permintaan di negara tersebut [17].…”

Section: Optimis DI Mana Kondisi Perekonomian Provinsiunclassified

Kebutuhan Energi Listrik Guna Menggerakkan Sektor Ekonomi Strategis di Provinsi Kalimantan Selatan

Putri

Nurhakim²,

Novianti³

et al. 2022

J. Geosapta

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Pemenuhan kebutuhan energi listrik di Provinsi Kalimantan Selatan diperkirakan tumbuh pesat, dengan adanya kawasan ekonomi khusus dan kawasan industri, sehingga diperlukan suplai energi listrik yang cukup besar. Kajian akan dihadapkan pada dua kondisi ekonomi, yaitu Business as Usual, dimana Provinsi Kalimantan Selatan masih mengalami pemulihan kondisi perekonomian yang merupakan dampak pandemi Covid-19, dan pertumbuhan ekonomi optimis, dimana Provinsi Kalimanatan Selatan mengalami percepatan ekonomi yang ditandai dengan terlaksananya rencana investasi proyek-proyek dalam kawasan ekonomi khusus dan kawasan industri. Metode yang digunakan dalam menentukan kebutuhan energi listrik adalah permodelan ekonometrika dengan pendekatan Ordinary Least Square (OLS). Model konsumsi energi listrik menggunakan variabel independent PDRB, jumlah penduduk, tarif rata-rata listrik, dan rasio elektrifikasi. PDRB dimodelkan menggunakan variabel independent jumlah tenaga kerja, pengeluaran pemerintah, dan investasi. Seluruh variabel menggunakan data historis dari tahun 2010 sampai dengan tahun 2021. Skenario 1 menghasilkan forecast PDRB dengan laju pertumbuhan rata-rata 2,72%.

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Section: Optimis DI Mana Kondisi Perekonomian Provinsiunclassified

Kebutuhan Energi Listrik Guna Menggerakkan Sektor Ekonomi Strategis di Provinsi Kalimantan Selatan

Putri

Nurhakim²,

Novianti³

et al. 2022

J. Geosapta

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“…Another study in 2020, predicted the electricity consumption in India with regression. Results demonstrated that sector-wise Net Domestic Savings was the most effective variable on future electricity demand in the domestic sector [22]. A study was conducted in 2021 to predict electricity consumption in various consumer sectors in India.…”

Section: Introductionmentioning

confidence: 99%

Application of a hybrid model based on multiple linear regression -principle component analysis (MLR-PCA) for electricity export forecasting

2022

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International electricity trade as a strategic commodity plays a prominent role in the foreign trade market of countries.Electricity export forecasting leads to better production planning, supply security, blackouts reduction, and obligations fulfillment. This paper aimed to provide a model for electricity export forecasting. In this regard, electricity consumption in different consumer sectors, gas consumption, population, GDP, and electricity prices have been entered into the multiple regression model as predictor variables. Although R 2 =.976, F=66.110, and SIG<.05 indicate the model appropriateness, the high correlation between the predictor variables created collinearity. In other words, Tolerance, VIF (variance inflation factor), Eigenvalue and the Condition Index are less than .2, more than 10, close to zero, and more than 15 respectively. To solve this problem, two hybrid methods of Multiple Regression-First Difference Function and Multiple Regression-PCA have been used. In the first hybrid method (R 2 =.553) the Tolerance and VIF index still show the presence of collinearity. In the second hybrid method (R 2 =.936, F=169.9, SIG<.05) due to all the mentioned indicators, the collinearity has been completely resolved. So, the MLR-PCA method is the most appropriate model for electricity export forecasting. The data collected from Iran have been used to illustrate the model.

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Meeting India's electricity demand in 2030

Dasgupta¹,

Sarangi²

2021

Energy and Climate Change

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Electricity Demand Forecasting Using Regression Techniques

Cited by 3 publications

References 8 publications

Kebutuhan Energi Listrik Guna Menggerakkan Sektor Ekonomi Strategis di Provinsi Kalimantan Selatan

Kebutuhan Energi Listrik Guna Menggerakkan Sektor Ekonomi Strategis di Provinsi Kalimantan Selatan

Application of a hybrid model based on multiple linear regression -principle component analysis (MLR-PCA) for electricity export forecasting

Meeting India's electricity demand in 2030

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