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The mastery of demand for electricity in Cameroon is one of the concerns of the State, which is part of the development plan for the electricity sector by 2025. Thus, this paper identifies the factors that influence the electricity sector and mentions positive government actions. We use in this work data on the basis of previous work on one hand and a survey on the other hand in order to reinforce the analysis. The survey was conducted on a sample of 3,000 households in Douala in order to identify socio-economic factors that influence the electricity sector. For this, face-to-face approach was chosen. Households were randomly selected, then a questionnaire was submitted to them, assisting them in their response options. Results show that though certain factors have a positive influence on the electricity sector, Cameroon's current electricity system still remains unsustainable. A comprehensive view of how various factors influence the electricity sector in Cameroon would help in understanding the challenges for the future development of the sector. Government policies in this area would be more enlightened and undergo reorganization. Different models of electricity consumption could thus be formulated and adopted in order to predict the potential impacts of changes in planning.

The electricity needs of populations in Cameroon are increasing and are still very inadequate. Companies, public buildings and households are facing frequent blackout which constrain development and social well-being. Therefore, the present work tried to forecast the electricity demand in the residential sector in Cameroon, in order to contribute significantly to the mastery of electricity consumption and highlight decision-makers in this sector. Six macroeconomics parameters covering the period 1994-2014 are used for these issues. Stationarity tests within gross domestic product, gross domestic product per capita, electricity consumption, population and numbers of subscribers and households respectively; reveal that all the series are I(1). Thus, the VAR (Vector Autoregressive) model has been retained to forecast the electricity demand until 2020. The cusum test and the cusum of squared test attest the stability of that model with a margin of error of 0.02%. Previsions are then more reliable and show that the electric request will skip from 1721 GWh in 2014 to more than 2481 GWh in 2020 approximatively, following a growing yearly rate of 5.36%. In order to reach its emergence, Cameroon ought to speed up its production in the domain of hydroelectric and thermal grid in order to meet the requirements in electric power in short and long term.

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Highlights The Grey and Vector autoregressive models are coupled to improve their accuracy. Five economic and demographic parameters are included in the new hybrid model. This new model is a reliable forecasting tool for assessing energy demand.

This paper centres on the estimation of carbon dioxide emissions in a Cameroon thermal power plant called Dibamba Power Development Company, in such a way that they can be included as part of Cameroon energy sector inventory or used by the Dibamba Power Development Company to monitor its policy and technology improvements for mitigating climate change. We have estimated the emissions using national emission factors for the consumption of liquid fossil fuels and simulated a mitigation of these emissions till 2018 using alternative fossil fuels and carbon neutral model. The results show that energy demand and carbon dioxide emissions in 2012 are estimated to be 48.964 ktoe and 164.39 kt CO 2 respectively. National emission factors for electricity generation are estimated to be 660.63 g/kWh. From 2012 to 2018, the thermal power plant will emit into the atmosphere 1298.42 kt CO 2 . These results also show that the use of alternative fuels will reduce 59.22 kt CO 2 per year for the same period while the use of the carbon neutral model will reduce a total amount of 8.08 kt CO 2 . Finally, the total quantity of CO 2 emission reduced for the period 2012 to 2018 will be 489.91 kt CO 2 .

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It is commonly recommended to incorporate diesel generators into distributed hybrid renewable energy systems (HRESs) to lower the system's total cost and make the generated electricity affordable. Due to the environmental and economic issues associated with fossil fuel use, biomass power technologies (BPT) appear to be an attractive alternative to diesel generators. The HOMER software was used to model, simulate, and optimise two photovoltaic/wind/battery systems integrated with different BPT (anaerobic digestion or gasification) to satisfy the electrical needs of Babadam, a remote community in northern Cameroon. The results indicated that the anaerobic digester integrated system's overall optimal architecture included a 98.1 kW photovoltaic array, a 30 kW biogas generator, and 200 batteries, with a cost of energy (COE) of $0.347/kWh. On the other hand, the gasifier integrated option is made up of an 81.8 kW photovoltaic array, a 15 kW syngas generator, and 200 batteries and has a COE of $0.319/kW. Additionally, compared to the PV/Wind/Battery system, integrating the biogas (resp. syngas) generator showed a potential COE decrease of 29% (resp. 40%). The sensitivity analysis highlighted the validity of this COE reduction potential everywhere in sub-Saharan Africa, leading to the conclusion that integrating BPT into HRESs can effectively contribute to Sustainable Development Goal 7.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.