Modeling Electricity Generation and Consumption in Cameroon

Blaise Fombuwing; Neyre Tekbıyık Ersoy

Makale detayları

Modeling Electricity Generation and Consumption in Cameroon

Yazarlar:

Blaise Fombuwing | Neyre Tekbıyık Ersoy

Yayıncı:

Murat YAKAR

Ana Başlıklar:

Environmental Engineering (Other)

Dergi:

Turkish Journal of Engineering Vol.8 Issue 4, pp.593-602

Belge Tipi:

Makale

Yayın Tarihi:

10/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001329385

pISSN:

2587-1366

Anahtar kelimeler:

Özet:

 Currently, there is a significant gap between electricity generation and consumption in Cameroon. Research has shown that electricity consumption in the country is estimated to increase by 965.7 GWh in five years, from 2020 to 2024 due to demographic and economic growth. Hence, this study aims to find methods that can be useful in developing strategies to balance the energy supply and demand in the country. This is done by developing models that can predict future electrical power consumption and generation. Correlation analysis and regression analysis were performed by using data obtained from various databases, and related models were developed accordingly. The model parameters were carbon dioxide emissions, electricity consumption per capita, final consumption expenditures, electricity installed capacity, fossil fuel installed capacity, labor force, and GDP. The models results demonstrated excellent performance coefficients with RMSE of 0.17041, 0.23893, 0.27571, and 0.2465 for hydroelectricity generation, fossil fuel electricity generation, net electricity generation, and net electricity consumption respectively. Also, hydroelectricity generation, net electricity generation, and net electricity consumption models showed very good RRMSE performance indicating that the models can make predictions with only 4.26, 5.26, and 5.77 deviation from the mean values of hydroelectricity generation, net electricity generation, and net electricity consumption, respectively.

 Currently, there is a significant gap between electricity generation and consumption in Cameroon. Research has shown that electricity consumption in the country is estimated to increase by 965.7 GWh in five years, from 2020 to 2024 due to demographic and economic growth. Hence, this study aims to find methods that can be useful in developing strategies to balance the energy supply and demand in the country. This is done by developing models that can predict future electrical power consumption and generation. Correlation analysis and regression analysis were performed by using data obtained from various databases, and related models were developed accordingly. The model parameters were carbon dioxide emissions, electricity consumption per capita, final consumption expenditures, electricity installed capacity, fossil fuel installed capacity, labor force, and GDP. The models results demonstrated excellent performance coefficients with RMSE of 0.17041, 0.23893, 0.27571, and 0.2465 for hydroelectricity generation, fossil fuel electricity generation, net electricity generation, and net electricity consumption respectively. Also, hydroelectricity generation, net electricity generation, and net electricity consumption models showed very good RRMSE performance indicating that the models can make predictions with only 4.26, 5.26, and 5.77 deviation from the mean values of hydroelectricity generation, net electricity generation, and net electricity consumption, respectively.

 Currently, there is a significant gap between electricity generation and consumption in Cameroon. Research has shown that electricity consumption in the country is estimated to increase by 965.7 GWh in five years, from 2020 to 2024 due to demographic and economic growth. Hence, this study aims to find methods that can be useful in developing strategies to balance the energy supply and demand in the country. This is done by developing models that can predict future electrical power consumption and generation. Correlation analysis and regression analysis were performed by using data obtained from various databases, and related models were developed accordingly. The model parameters were carbon dioxide emissions, electricity consumption per capita, final consumption expenditures, electricity installed capacity, fossil fuel installed capacity, labor force, and GDP. The models results demonstrated excellent performance coefficients with RMSE of 0.17041, 0.23893, 0.27571, and 0.2465 for hydroelectricity generation, fossil fuel electricity generation, net electricity generation, and net electricity consumption respectively. Also, hydroelectricity generation, net electricity generation, and net electricity consumption models showed very good RRMSE performance indicating that the models can make predictions with only 4.26, 5.26, and 5.77 deviation from the mean values of hydroelectricity generation, net electricity generation, and net electricity consumption, respectively.

 Currently, there is a significant gap between electricity generation and consumption in Cameroon. Research has shown that electricity consumption in the country is estimated to increase by 965.7 GWh in five years, from 2020 to 2024 due to demographic and economic growth. Hence, this study aims to find methods that can be useful in developing strategies to balance the energy supply and demand in the country. This is done by developing models that can predict future electrical power consumption and generation. Correlation analysis and regression analysis were performed by using data obtained from various databases, and related models were developed accordingly. The model parameters were carbon dioxide emissions, electricity consumption per capita, final consumption expenditures, electricity installed capacity, fossil fuel installed capacity, labor force, and GDP. The models results demonstrated excellent performance coefficients with RMSE of 0.17041, 0.23893, 0.27571, and 0.2465 for hydroelectricity generation, fossil fuel electricity generation, net electricity generation, and net electricity consumption respectively. Also, hydroelectricity generation, net electricity generation, and net electricity consumption models showed very good RRMSE performance indicating that the models can make predictions with only 4.26, 5.26, and 5.77 deviation from the mean values of hydroelectricity generation, net electricity generation, and net electricity consumption, respectively.

Makale detayları

Modeling Electricity Generation and Consumption in Cameroon

Yazarlar:

Blaise Fombuwing | Neyre Tekbıyık Ersoy

Yayıncı:

Murat YAKAR

Ana Başlıklar:

Environmental Engineering (Other)

Dergi:

Turkish Journal of Engineering Vol.8 Issue 4, pp.593-602

Belge Tipi:

Makale

Yayın Tarihi:

10/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001329385

pISSN:

2587-1366

Cameroon

Correlation Analysis

Electricity Consumption

Electricity Generation

Regression Analysis

Sayı

Makale detayları

Modeling Electricity Generation and Consumption in Cameroon

Yazarlar: Blaise Fombuwing | Neyre Tekbıyık Ersoy

Yayıncı: Murat YAKAR

Ana Başlıklar: Environmental Engineering (Other)

Dergi: Turkish Journal of Engineering Vol.8 Issue 4, pp.593-602

Belge Tipi: Makale

Yayın Tarihi: 10/2024

Belge Dili: İngilizce

Document ID (Org No.): 2001329385

pISSN: 2587-1366

Cameroon

Correlation Analysis

Electricity Consumption

Electricity Generation

Regression Analysis

Sayı

Yazarlar:

Blaise Fombuwing | Neyre Tekbıyık Ersoy

Yayıncı:

Murat YAKAR

Ana Başlıklar:

Environmental Engineering (Other)

Dergi:

Turkish Journal of Engineering Vol.8 Issue 4, pp.593-602

Belge Tipi:

Makale

Yayın Tarihi:

10/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001329385

pISSN:

2587-1366