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The Nigerian government is committed to sustaining rice production to meet national demand. Nevertheless, political tension and climate-induced stressors remain crucial constraints in achieving policy targets. This study examines whether climate change and political instability significantly threaten rice production in Nigeria. First, we employed nonparametric methods to estimate the country's rainfall and temperature trends between 1980Q1 and 2015Q4. Second, we employed the autoregressive distributed lag (ARDL) technique to examine the effects of climate change and political instability on rice production. The results show that while temperature has an increasing pattern, rainfall exhibits no significant trend. The findings from the ARDL estimate reveal that rice production responds negatively to temperature changes but is less sensitive to changes in rainfall. In addition, political instability adversely affects rice production in Nigeria. We argue that Nigeria's slow growth in rice production can be traced back to the impact of climate change and political tension in rice farming areas. As a result, reducing the overall degree of conflict to ensure political stability is critical to boosting the country's self-sufficiency in rice production. We also recommend that farmers be supported and trained to adopt improved rice varieties less prone to extreme climate events while supporting them with irrigation facilities to facilitate rice production.

Abstract In this paper, an exergoeconomic analysis and optimization of a combined solar and wind energy based system is proposed. The trigeneration system produces ammonia, hydrogen and electricity through integrated solar photovoltaic panels and wind turbines. Also, an ammonia fuel cell unit is utilized for generating power during insufficient available energy. The overall exergetic efficiency is found to be 29.7% and the corresponding energetic efficiency is 28.5% under design conditions. In addition, the total cost rate is obtained as 63,345 $/h. Moreover, multi-objective optimization is performed with various decision variables at different combinations of solar intensities and wind speeds, considering the maximization of exergy efficiency and minimization of total cost rates. The developed system provides better optimal operation points under high wind speeds. The optimal exergy efficiency is found to vary between 10.9% and 38.2% depending on the available solar and wind energy. The corresponding optimal total cost rates vary between 11,959 $/h and 59,755 $/h, respectively. Several parametric studies are also performed to determine the effects of changing system conditions on the thermodynamic and economic performance of the developed system.

Co-simulation of heterogeneous systems allows for in-depth analysis of various aspects of power systems’ operation while staying within the environments of the simulation tools that are best fit to represent their respective domains. Equipped with a proprietary co-simulation platform, the paper focuses on the issue of power-conjugate coupling between parts of power grids modeled in transient stability and electromagnetic transient simulation tools. The problems of co-simulation stability and precision in presence of delays are tackled by means of designing a proper coupling interface. It is shown that two established interface methods – the V-I method and the Transmission Line Interface – are special cases of a generalized interface framework proposed in the paper. Moreover, a new interface algorithm is described by parametrizing the generalized framework. Analytical tools are also formulated to aid in the analysis of interface stability and precision via the concepts of passivity and transparency. Simulation results of benchmark systems of various complexity demonstrate the application of the developed power coupling interface.

Abstract Hydrogen fuel cells are received increasingly wide attention in order to develop green ships and reduce greenhouse gas emissions in the field of waterway transportation. Metal hydrides (MHs) can be used to store hydrogen for green ships due to their high volumetric storage capacity and safety. Various measures should be considered in the design and manufacture process of the MH reactor to strengthen its performance of heat and mass transfer and obtain an acceptable hydrogen storage capacity. In this work, LaNi5 hydride is used as the hydrogen storage material and packed in the reactor. A basic axisymmetric numerical model for the hydrogen storage system without a heat exchanger has been developed and proved to be effective through the comparison between its simulation results and the published data during dehydriding. A hybrid heat exchanger, which is consisted of a phase change material (PCM) jacket and a coiled-tube, has been applied into the hydrogen storage system to relieve the thermal effect of MH in the dehydriding process on system performance. Effects of the heat transfer coefficient between the circulating heating water in the coil-tube and the MH bed, the temperature of circulating heating water and the pressure at the outlet on the dehydriding performance have been investigated. Based on parametric study, the relationships among the average dehydriding rate, the heat transfer coefficient, the heating water temperature and the outlet pressure have been found and fitted as simple equations. These fitted equations can be considered as a reference, which provides an important method to effectively control the dehydriding rate in order to satisfy the fuel requirement of the power unit and ensure the safe navigation of green ships in the future.

Abstract Eradicating poverty and mitigating greenhouse gas (GHG) emissions are core issues of global sustainable development goals (SDGs), and China is struggling in realizing these targets. The poverty reduction that leads to popualtion structure and lifestyle changes would have an impact on GHG emission changes. However, few studies have assessed the historical and future impacts of the poverty allevation on China's emissions. Here by linking Chinese Multi-Regional Input Output (MRIO) database to the global MRIO database EXIOBASE, and using provincial household consumption data, we identified the distribution of Chinese household greenhouse gas footprints (HGFs) by income groups in 2015 at the national and provinical levels. Moreover, we focused on the historical impact of poverty alleviation on HGFs during 2010–2015, and developed four scenarios to project future HGFs changes due to poverty alleviation by 2030. We find that eradicating extreme poverty in the secanrio S2, i.e., bringing people to an income above $1.9 daily, does not cause a large emission impact with current technological level. However, lifting people from a higher poverty line of $5.5 per day in the sceanrio S4 results in a 1.6% increase in emissions compared with the scenario S1 without any poverty reduction goals. Furthermore, realizing a higher poverty reduction target will result in an increase of emissions contribution from internatioanl supply chains due to the differences in consumption patterns among different income groups. Our study highlights the conflict between the high poverty alleviaition goal and emission reduciton in China, and reminds us of the need to make more technological efforts for avoiding the large emissions embodied in international supply chains.

In this chapter, turbulent flow of water-based optimization (TFWO) inspired based on whirlpools created in turbulent flow of water is used to solve the maximum power point tracking (MPPT) of photovoltaic systems in partial shading conditions. The TFWO is used to determine the optimal duty cycle of the DC/DC converter with the objective of maximizing the extracted power of the photovoltaic system. The capability of proposed method is evaluated in different patterns of partial shading to achieve global optimal power. The simulation results showed that TFWO is able to track the global maximum power point (GMPP), successfully in PSC and also fast climate changing. The TFWO has a better tracking capability with faster tracking speed and accuracy than particle swarm optimization (PSO) in obtaining the GMPP. Moreover, the results indicate that the use of buck–boost converter led to faster and more accurate access to the global optimal point than the system equipped with boost converter. The results showed that photovoltaic system with boost converter cannot obtain global maximum power in climate changing condition and limited the efficiency of the MPPT algorithm, while the photovoltaic system with buck–boost converter could be tracked GMPP due to its wider operating area.