Optimizing technical and economic aspects of off-grid hybrid renewable systems: A case study of Manoka Island, Cameroon

The lack of accessible and reliable electrical energy in Cameroon has become a pervasive obstacle to the nation\u27s progress, with energy availability, quality, and cost identified as key hindrances to development over the past 15 years. Conventional solutions that rely on combustion engines and electrochemical storage systems have proven to be cost-prohibitive, limited in power output, and constrained in capacity. The dependence on traditional diesel generators has perpetuated maintenance challenges and a continuous demand for fuel supply, while the accompanying noise and pollution have restricted their use in residential areas. Recognizing the imperative of reducing dependence on fossil fuels and curbing greenhouse gas emissions, the need for clean and sustainable energy sources has emerged as a critical concern for the advancement of civilization. Against this backdrop, this research endeavors to identify the most cost-effective and efficient blend of renewable energy sources capable of meeting the power requirements of three small communities on Manoka Island, a district of Douala, Cameroon. Through a comprehensive technical, environmental, and economic analysis, this study addresses the substantial energy needs of 334 households, with an average daily power consumption of 1082.90 kWh and a peak electrical load of 183.99 kW. Leveraging the Hybrid Optimization Model for Electric Renewables (HOMER) program, this investigation assesses the feasibility of implementing Hybrid Renewable Energy Systems (HRES) to meet the region\u27s energy demands. The research highlights the most optimal scenario integrating solar panels, wind turbines, battery cells, fuel cell generators, biogas, and an electrolyzer within an off-grid HRES system. Notably, the study demonstrated an absence of idle load, resulting in remarkably low unit energy costs of { \ } $0.1981 and a compelling net present value of$ { \ } 2,209,741. The cost-effective arrangement featured 201 batteries, yielding a project profit of { \ } $ 57,387, with an impressive Internal Rate of Return (IRR) of 9.09%, Return on Investment (ROI) of 6.19%, and a payback period of 8.76 years over a 25-year term. In essence, the insights gleaned from this exploration of hybrid energy systems represent a pioneering case study in sustainable electricity provision. This research significantly contributes to the knowledge base on renewable energy within the nation, underscoring its tremendous potential for sustainable development and energy security

A Comprehensive Review of the Soiling Effects on PV Module Performance

Photovoltaic (PV) systems are a popular renewable energy source globally, owing to their beneficial environmental and economic properties. However, their efficiency is impacted by various environmental and weather conditions, including dust accumulation, which harms the performance of solar cells, particularly in hot and dry regions. Several researchers have studied how to clean and minimize dust on PV modules. This paper reviews recent studies on the effects of dust on PV systems and effective cleaning methods. Some locations experience power losses of over 1% each day and 80% monthly efficiency reduction due to dust, which is substantial. This paper delivers a thorough review of the issue of dust on PV modules. It analyzes previous research on how photovoltaic (PV) systems function when exposed to a mix of dust accumulation and other environmental factors. It also delves into the development of models to forecast dust accumulation. Furthermore, it examines various aspects of PV module design, including the frequency of cleaning methods, economic factors, and their advantages and disadvantages. Additionally, the study identifies several research gaps that require further exploration. These gaps include developing artificial intelligence-based models for reducing dust accumulation, dynamic optimization models for cleaning schedules, as well as advanced techniques for predicting dust accumulation, taking into account environmental conditions and ageing procedures. This information is essential for engineers, designers, and researchers who work on PV systems

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population