Optimal design and sensitivity analysis of distributed biomass‐based hybrid renewable energy systems for rural electrification: Case study of different photovoltaic/wind/battery‐integrated options in Babadam, northern Cameroon

Abstract

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.

Techno‐economic studies on the variable compression ratio dual fuel diesel‐producer gas CI engine utilizing different biomass feedstocks

“…Some of the input variables comprise a wide range of uncertainty than others and are to be prioritized. The following variables are considered to be the most significant economic variables that have a greater impact over the financial viability of the BMPGS 51 The capital cost for investment, given the initial large amounts of capital cost the project needs to recover. Hours of operation, as varies depending on duration of power cuts and maintenance in the BMPGS (4, 6, 8 h). Labor cost, the wages given to workers depends on the plant location and skill of the worker and holds an uncertainty. Cost of diesel, as it keeps on fluctuating in accordance with market oil prices. Cost for biomass feedstock, considering it is the main supply for the entire production. …”

“…The following variables are considered to be the most significant economic variables that have a greater impact over the financial viability of the BMPGS. 51 • The capital cost for investment, given the initial large amounts of capital cost the project needs to recover.…”

Assessment of the Geographic and Technical Potential for Large-Scale Wind Energy Production Using a GIS-Based MCDM-AHP Multi-criteria Analysis Method and Sensitivity Analysis: Case of Cameroon

“…Cameroon's population is estimated at over 25 million in 2019. According to the literature [10][11][12][13][14][15][16][17], there are significant reservoirs of wind generation in the areas of Kaelé and Kousseri in the Far North, the Bamboutos Mountains in the West region and certain localities in the Adamaoua region, Centre and Douala, Limbe, Kribi in the Littoral. In response to the ever-increasing demand for electricity, and the insufficient quantity and quality of electricity for the people of Cameroon, several investment projects for the construction of wind power plants are currently under study in Cameroon.…”

“…The development of wind farm projects requires appropriate technical, economic and socio-environmental planning and assessment. However, previous research on wind in Cameroon has focused mainly on the comparison of numerical methods for estimating Weibull parameters for the installation of a wind farm in Cameroon [10][11][12], the assessment of the potential of wind energy for the cogeneration of electricity and hydrogen in the Far North of Cameroon [13], technical-economic analysis based on meta-heuristic techniques for the optimal sizing of a standalone photovoltaic/wind hybrid system based on hydrogen batteries for rural electrification in Cameroon [14], study of the design and sensitivity analysis of biomass-based distributed hybrid renewable energy systems for rural electrification with a case study of different photovoltaic/wind/battery integrated options in Babadam, northern Cameroon [15], the design of a checkerboard sizing and layout optimization model for a small onshore wind farm with an estimated capacity of 500 kW in Kribi, Cameroon [16]. To our knowledge, only one study has analyzed the suitability of wind farm sites in Cameroon using a Boolean decision-making approach coupled with GIS (geographic information systems) using various climatic, geographic, economic and environmental criteria such as wind resource, slope, road accessibility, proximity to the power grid and optimal distance to airports.…”