Reversible solid oxide cells can provide efficient and cost-effective scheme for electrical-energy storage applications. However, this technology faces many challenges from material development to system-level operational parameters , which should be tackle for practical purposes. Accordingly, this study focuses on developing novel robust artificial intelligence-based blackbox models to optimize operational variables of the system. A genetic-programming algorithm is used for Pareto modeling of reversible solid oxide cells in a multi-objective fashion based on experimental input-output data. The robustness of the obtained optimal model evaluated using Monte Carlo simulations technique. An optimization study adopted to optimize the operating parameters, such as temperature and fuel composition using a differential evolution algorithm. The objective functions that have been considered for Pareto multi-objective modeling process are training error and model complexity. In addition, the discrepancy between maximum and minimum output voltage in the whole operation of the system is chosen as the optimization process objective function. The robustness of the optimal trade-off model is shown in terms of statistical indices for varied uncertainty levels from 1 to 10%. The optimized operational condition based on the suggested model reveals optimal intermediate temperature of 762 °C and fuel mixture of about 29% H 2 , 25% H 2 O, and 14% CO.

The aim of this paper is to review previous works on the performance appraisal of Nigerian government-owned refineries. The review has been done in a general sense, covering appraisal works by engineers, scientists, management experts, economists, sociologists and even historians. The outcome indicates that while there seems to be several works directly and/or indirectly assessing the performance of the refineries in a general sense, there is a dearth of such in the specific area of energy consumption. There also appears to be no single one appraising energy utilisation of all the refineries at the same time in the open literature. This is in spite of the fact that refining processes are energy intensive. Despite popularisation of exergy analysis as a veritable tool, the only energy utilisation appraisal within our reach which was carried out on just one of the refineries has not been done exergetically. However, the work still reveals, within the limitations of 1st Law energy analysis that the energy consumption patterns are below international benchmarks in the oil and gas industry. Some suggestions have also been offered to take care of the energy efficiency challenges in these refineries. These include plant to plant analyses of energy utilisation patterns in the four refineries, periodical determination of GHG emission levels in the refineries using current international best practices as benchmarks, use of exergy analysis to check avoidable energy wastage in the refining processes, shifting refinery fuelling pattern in favour of low carbon content fuels like natural gas and ensuring regular turnaround maintenance of the system

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This study analyses the fuel-mix and energy utilization patterns in Port Harcourt Refining Company from 2000 to 2011. The average fuel mix over the study period is 43% refinery fuel gas, 0% liquefied petroleum gas (LPG), 44% low pour fuel oil (LPFO), 8% Coke, and 5% automotive gas oil (AGO). The present ratio of high-carbon fuel consumption to low-carbon fuel consumption adversely influences the specific fuel consumption by increasing it. Our proposal is that the present AGO and LPFO consumption levels are totally replaced with equivalent amounts of natural gas. This would yield the following fuel mix: 46% refinery fuel gas, 46% natural gas, and 8% coke. This, in effect, would result in a proportion of 92% low-carbon fuels and 8% coke. It would also lead to a specific fuel consumption that is averagely unaffected by high-carbon/low-carbon fuel consumption ratios. Natural gas utilization has its main advantage in its flare/waste and consequent environmental degradation reduction. Finally, the proposed fuel mix would generally lead to a reduction in specific fuel consumption, thus saving energy and reducing costs.

Energy, exergy, and economic analyses of energy sourcing pattern in a Nigerian brewery have been carried out. The mean annual energy efficiencies have varied from 75.62% in 2004 to 81.71% in 2006, while the mean annual exergy efficiencies have varied from 42.66% in 2004 to 57.10% in 2005. Diesel fuel combustion, whether for local electricity generation via internal combustion engines or for process steam raising in boilers, has adversely affected the efficiencies of energy utilisation in the company. The negative effect of steam raising on efficient energy utilisation is more, although steam raising is unavoidable, due to the nature of the company under investigation. The annual mean energy unit costs have also varied from 27.86 USD per Giga-Joule in 2006 to 32.80 USD per Giga-Joule in 2004, confirming the inverse proportion of energy efficiency and costs. On the other hand, the annual mean exergy unit costs have varied from 40.19 USD per Giga-Joule in 2005 to 58.46 USD per Giga-Joule in 2004. The most efficient year has been 2006 energetically and 2005 exergetically. The difference in the two years lies in the proportions of generator diesel and boiler diesel utilised as the system exergy is most sensitive to boiler diesel use while the system energy is more sensitive to generator diesel utilisation due to their different device efficiencies