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September 10, 2025Proceeding of International Conference on Science and Technology UISU.

Long-Term Load Forecasting At The End Of The Year Using The Linear Regression Method

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Authors

RHRobinson HarahapNorth Sumatra Islamic University SPSamuel Patra PurbaUniversitas Sumatera Utara

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Implication

Long-term load forecasting using the linear regression method shows stable load trends at Glugur Substation, indicating effective electricity distribution system planning.

Key Points

Forecasting results demonstrate a consistent increase in electricity load trends, supporting better planning.
A MAPE value of 2.43% at the Glugur Substation indicates good forecasting accuracy and reliability.
The study utilizes historical load data from 2021 to 2024 to project future electricity demands until 2026.
Evaluation metrics like MAPE, R², MAE, and RMSE confirm the linear regression model's effectiveness for long-term forecasts.

Cite This Study

Harahap et al. (2025) studied this question.

synapsesocial.com/papers/68c1c23d54b1d3bfb60efcca https://doi.org/10.30743/frxcx086

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Implication

Long-term load forecasting using the linear regression method shows stable load trends at Glugur Substation, indicating effective electricity distribution system planning.

Long-Term Load Forecasting At The End Of The Year Using The Linear Regression Method

Discussion

Member takes

Implication

Key Points

Cite This Study

Long-Term Load Forecasting At The End Of The Year Using The Linear Regression Method

Discussion

Member takes

Implication

Key Points

Cite This Study

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