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Forecasting energy consumption is a major concern for policymakers, oil industry companies, and many other associated businesses. Though there exist many forecasting methodologies, selecting the most appropriate one is critical. GM(1,1) has proven to be one of the most successful forecasting tool. GM(1,1) does not require any specific information and can be adapted to predict energy consumption using a minimum of four observations. Unfortunately, GM(1,1) on its own will generate too large forecast errors because it performs well only when data follow an exponential trend and should be implemented in a political-socio-economic free environment. To reduce these errors, this study proposes a new GM(1,n) convolution model optimized by genetic algorithms integrating a sequential selection mechanism and arc consistency, abbreviated Sequential-GMC(1,n)-GA. Practically, the proposed approach, on one hand, highlights the forecast for petroleum products consumption in Cameroon's household sector. On the other hand, it estimates the amount of CO2 that would be reduced if petroleum products in this sector were switched to clean energy. The new model, like some recent hybrid versions, is robust and reliable, according to the results. Households petroleum products needs by 2025 are estimated to be 150,318 kilo tons of oil equivalent with MAPE of 1.44%, and RMSE of 0.833. Therefore, households GHG emissions would be reduced by 733.85 kilo tons of CO2 equivalent if clean energy was used instead of petroleum products. As a result, the new hybrid model is a valid forecasting tool that can be used to track the growth of Cameroon's household energy demand.

The combination of its sorption capacity, reaction enthalpy, melting temperatures around available industrial waste heat and solar source and high thermal efficiency (compared to others salt hydrates) makes strontium bromide and its two respective hydrates a potential material for low temperature energy storage and building applications. It is considered among suitable materials for low thermochemical and sorption energy storage application (N’Tsoukpoe et al. [7]) due to its high-energy storage density and end-user temperature. Strontium bromide is simultaneously considered as a phase change and a thermochemical material. A short analysis of the general physical and chemical properties such as thermodynamics, melting temperature, density, sorption kinetics, exergy, thermal conductivity, specific heat capacity and permeability highlights the advantageous properties. The review on the use of strontium bromide in pure or modified form is further extended to applications such as building structure, composite design for thermal storage, and heating and cooling. The usefulness and disadvantages of its use in closed/open processes are discussed. Possible solutions to issues are further presented or proposed.

Cameroon is highly growing in energy as a whole, and in electricity in particular. This growth is expected to increase within the next years, thanks to the current emergence as well as the country’s major projects. Therefore, mastering electricity demand in the residential sector is one of State’s priorities. In fact, this falls under the development plan of the electricity sector by 2025. Therefore, this paper highlights the forecast of the electricity consumption regarding the residential sector in Cameroon. The new GM(1,1)-VAR(1) hybrid model which is based on the VAR and Grey models, is used for this purpose. Results from the new model show that the previsional GM(1,1)-VAR(1) model is strong and reliable, just like some recent and modern hybrid models. Electricity needs of the residential sector by 2025 are estimated at 2641.632 GWh, with a 1 . 628 % MAPE, and a 15.42 RMSE. Consequently, the new hybrid model should be a reliable previsional tool that makes it possible to monitor the evolution of electricity demand of the residential sector in cameroon.