A Linear Multiple Regression approach is used to model the energy consumption of electricity in Togo. This model is developed from the load data recorded at the electric power source stations in Togo during the period from 2016 to 2017. This model predicts four input parameters (Day of the week, the type of day (working day). or not), Hours in the day and Load data of the same time of the previous day) is used to predict the electrical energy consumption data for the period of 2018 with a MAPE of 4.4964% and a correlation coefficient R2 equal to 95.5889%
The quality of short-term electricity load forecasting is crucial to the operation and trading activ...
Ghana suffers from frequent power outages, which can be compensated by off-grid energy solutions. Ph...
This paper presents the modelling and forecasting of residential electricity consumption in Nigeria ...
We study the forecast of the electrical energy demand of the N'Djamena city, Chad, by 2032 using the...
In this paper short term load forecasting (STLF) is done with using multiple linear regression (MLR)...
This paper proposes multi-equation linear regression model with autoregressive AR(2) method for mode...
This paper provides some new techniques to predict the electric load using Multiple Linear Regressio...
© Published under licence by IOP Publishing Ltd. Energy field plays an important role in commercial ...
Short-term electricity consumption data reflects the operating efficiency of grid companies, and acc...
Short-term forecasting of power consumption is an important tool for decision makers in the energy s...
The paper presents a multivariate adaptive regression splines (MARS) modelling approach for daily pe...
This article involves forecasting daily electricity consumption in Thailand. Electricity consumption...
Electricity consumption forecasting plays a crucial role in improving energy efficiency, ensuring st...
Masteroppgave i informasjons- og kommunikasjonsteknologi IKT590 2012 – Universitetet i Agder, Grims...
The goal of this paper is to develop a forecasting model for the hourly electric load demand in the ...
The quality of short-term electricity load forecasting is crucial to the operation and trading activ...
Ghana suffers from frequent power outages, which can be compensated by off-grid energy solutions. Ph...
This paper presents the modelling and forecasting of residential electricity consumption in Nigeria ...
We study the forecast of the electrical energy demand of the N'Djamena city, Chad, by 2032 using the...
In this paper short term load forecasting (STLF) is done with using multiple linear regression (MLR)...
This paper proposes multi-equation linear regression model with autoregressive AR(2) method for mode...
This paper provides some new techniques to predict the electric load using Multiple Linear Regressio...
© Published under licence by IOP Publishing Ltd. Energy field plays an important role in commercial ...
Short-term electricity consumption data reflects the operating efficiency of grid companies, and acc...
Short-term forecasting of power consumption is an important tool for decision makers in the energy s...
The paper presents a multivariate adaptive regression splines (MARS) modelling approach for daily pe...
This article involves forecasting daily electricity consumption in Thailand. Electricity consumption...
Electricity consumption forecasting plays a crucial role in improving energy efficiency, ensuring st...
Masteroppgave i informasjons- og kommunikasjonsteknologi IKT590 2012 – Universitetet i Agder, Grims...
The goal of this paper is to develop a forecasting model for the hourly electric load demand in the ...
The quality of short-term electricity load forecasting is crucial to the operation and trading activ...
Ghana suffers from frequent power outages, which can be compensated by off-grid energy solutions. Ph...
This paper presents the modelling and forecasting of residential electricity consumption in Nigeria ...