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Adequate supply of electricity at a competitive price is pivotal to sustainable development. More often than not, the generation of electricity which drives modern growth and development is currently powered by limited fossil fuels in many nations. Electricity generation and megawatt demand are also usually fluctuating due to several pertinent factors. In a bid to articulate the impact of inherent variations in process parameters on the performance of steam power plant at different loads, this paper presents an investigation into the efficacy of two validation strategies in predicting the net power output from the plant using GMDH Shell software. Using the combinatorial algorithm, the k-fold cross-validation strategy and the training/testing validation technique were applied to empirical data of a power plant in Nigeria. The performance of the models returned from the two validation strategies was evaluated using maximum negative error, maximum positive error, mean absolute percentage error (MAPE), root mean square percentage error (RMSPE), residual sum, the standard deviation of residuals, coefficient of determination (R2) and correlation. For the number of folds and the training/testing split percentage considered in this study, results show that both models obtained were quite competitive, with the k-fold model having a slight edge over the other model. It is expected that the outcome of the study will be handy in researches for providing knowledge base information on choosing and setting optimum operating conditions at various load demand.

Industrial activities, including the process of power generation from thermal plants, are inevitably associated with the generation of gaseous wastes and particulate matters. Industrial activities, therefore, contribute largely to the emission of environmental pollutants. In addition to causing environmental degradation, the emission of pollutants, particularly greenhouse gases, have far-reaching social negative externalities, mainly in the area of unconducive temperature rise and adverse climatic impact. The unintended impacts of industrial emissions have motivated the development of plans and strategies for their abatement. In this study, predictive models of the global warming potential and carbon tax of the gaseous emission at various fuel consumption levels and different air–fuel ratio for the combustion process in a thermal power plant were developed. It is expected that the models serve as a veritable tool for projecting the environmental & economic costs of natural gas burning and optimizing the process of the fuel combustion for lower greenhouse gas emissions.

It is crystal clear that appropriate technical sizing has a significant effect on the techno-economic analysis of an off-grid standalone energy system. As a result, this study presents the effect of incorporating the temperature coefficient in the optimal analysis of an off-grid hybrid system using a standard fuel (gas) station in Nigeria as a case study. Comparative analysis with and without the temperature coefficient was performed. The results showed that the inclusion of temperature coefficient leads to extra operation hours of the generator which will result in an increase in fuel consumption and annual operation cost of the diesel generator. Also, the initial cost of the PV/BAT/diesel is relatively higher than the diesel generator but, the generating emission of the hybrid system is lower when compared to the diesel-only which enhances the atmospheric condition of the society.Keywords: Techno-economic Analysis, Hybrid System, Temperature Coefficient, Fuel ConsumptionJEL Classifications: Q4, Q43DOI: https://doi.org/10.32479/ijeep.9886

Adoption of energy efficiency and conservation techniques in public buildings in Nigeria is significantly low due to the ignorance of its potential benefits. Consequently, this study presents the prospects of energy saving using different methods in a public building at a Nigerian University. A proposed remodelled students’ residential hostel at the University of Lagos, Nigeria was chosen as a pilot study. This research utilized three energy efficient lighting technology alternatives namely; intelligent controlled Incandescent lamp (ICIL), compact fluorescent lamp (CFL), and intelligent controlled CFL (ICCFL) and compared with a base case of conventional incandescent lighting configuration. Energy consumption, at the proposed hostel is analysed and modelled. The effectiveness of each lighting technology alternative and base case in terms of cost is estimated using economic indices such as the net present value (NPV), savings to investment ratio (SIR) and the discounted payback period (DPP). Results show that the CFL lighting technology give 39% cost benefit as compared to ICCFL which gives 11% overall cost benefit. From the study, it is established that adoption of energy efficient lighting techniques save a significant amount of energy, operational cost, electricity bills and consequently reduce emission.Keywords: Energy saving, Net present value, Savings to investment ratio, discounted payback periodJEL Classifications: C63, Q48DOI: https://doi.org/10.32479/ijeep.9905

Electricity supply in Nigeria is a huge problem with great economic and political consequences. After unbundling and privatization of generation and distribution companies, not much improvement has been experienced by electricity consumers; this is due to lack of investment in infrastructure. Lack of investment in infrastructure especially from private investors is caused largely by non-cost reflective tariff among other factors highlighted in this study. While many believe tariff has to be controlled such that it does not go beyond the reach of average citizens, many also believe that the average citizens can pay much more than the current tariff. The latter is evident considering the average amount spend on the use of portable gasoline generators by most homes and small enterprises both in rural and urban centers. The whole life cost method is used to show here that it costs a home or business premise that operates a portable gasoline generator for 6 hours daily NGN 37, 000 per month and costs NGN 157,000 to operate 20 kVA diesel generator. This shows the consumers’ capacity to pay the appropriate tariff that can attract investors to the sector.Keywords: Utility, tariff, electric power generation cost, life cost method, consumerJEL Classification: Q43DOI: https://doi.org/10.32479/ijeep.8590

In order to realize the goal of optimal use of energy sources and cleaner environment at a minimal cost, researchers; field professionals; and industrialists have identified the expediency of harnessing the computational benefits provided by artificial intelligence techniques. This article provides an overview of artificial intelligence (AI), chronological blueprints of the emergence of artificial neural networks (ANNs) and some of its applications in the energy sector. This short survey reveals that despite the initial hiccups at the developmental stages of artificial neural networks, ANN has tremendously evolved, is still evolving and have been found to be effective in handling highly complex problems even in the areas of modeling, control, and optimization, to mention a few.Keywords: artificial neural networks, energy sector, optimizationJEL Classifications: Q4, P28DOI: https://doi.org/10.32479/ijeep.8691

Purpose This study aims to analyze the effects of variations in annual real interest rates in the assessment of the techno-economic feasibility of a hybrid renewable energy system (HRES) for an off-grid community. Design/methodology/approach Hybrid Optimization of Multiple Energy Resources (HOMER) software is used to propose an HRES for Abadam community in northern Nigeria. The HRES was designed to meet the basic needs of the community over a 25-year project lifespan. Based on the available energy resources in the community, photovoltaic (PV), wind turbine, diesel generator and battery were suggested for integration to serve the load requirements. Findings When the annual real interest rates were taken as 10 and 8 per cent, the total amount of total energy fraction from PV, wind turbine and the diesel generator is 28, 57 and 15 per cent, respectively. At these interest rates, wind turbines contributed more energy across all months than other energy resources. The energy resource distribution for 0, 2,4 and 6 per cent annual real interest rates have a similar pattern, but PV contributed a majority of the energy. Practical implications This study has used annual real interest and inflation rates dynamic behavior to determine optimal HRES for remote communities. Hence, its analysis will equip decision-makers with the necessary information for accurate planning. Originality/value The results of this study can be used to plan and design HRES infrastructure for off-grid communities around the world.

The 2030 Agenda for Sustainable Development suggests that all countries both developed and developing strive to attain the seventeen sustainable development goals (SDGs). Some items on the SDGs like implementation of renewable energy technologies to electrify regions disconnected from power grids are targeted to eradicate extreme poverty and hunger while ensuring environmental sustainability. Hence, the role of integrated renewable energy in improving the productivity and environmental sustainability of the agricultural sector cannot be overemphasized. This paper presents a brief survey of the application of renewable energy resources technologies in the agricultural sector. Keywords: Sustainable agriculture; Water-food-energy nexus; Renewable energy; Techno-economic.JEL Classifications: Q2, Q4DOI: https://doi.org/10.32479/ijeep.7775

Presented in this study is an optimal hybrid renewable off‐grid energy system model that supplies a typical rural healthcare center across the six regions in Nigeria. A technical and economic evaluation was carried out to identify the optimal off‐grid hybrid energy system combination based on photovoltaic (PV), wind, diesel generator and battery. Due to governments’ fuel subsidy in many developing countries, the pump price of fuel is reduced and not a true reflection of what is obtainable in a deregulated market. In order to comprehensively capture the reality, the study considered the effect of subsidy removal by carrying out a sensitivity analysis on the fuel pump price. Therefore, the impact of a change in diesel fuel pump price and interest rates on the economic performance criteria of the optimal configuration is explored. Results show that across all the locations considered, PV/diesel/battery system is the most economically viable with a net present cost and renewable fraction (RF) ranging between $12 779 and $13 646 and 70%‐80% respectively. The cost of energy (COE) is also estimated to range between 0.507 and 0.542 $/kWh.