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This paper proposes a multi-electrolyzer switching scheduling strategy based on the Pelican Optimization Algorithm (POA) to enhance the efficiency of large-scale wind power hydrogen production systems. To validate the effectiveness of the proposed strategy, we analyzed wind power data from three typical days in northern Hebei, China, with a 2.5 MW wind turbine output. We designed three strategies for comparative analysis: a simple start-stop strategy, a rule-based multi-electrolyzer switching strategy, and a POA-based multi-electrolyzer switching strategy. The study results demonstrate that the POA-based strategy exhibits higher hydrogen production efficiency and system stability under various wind conditions. Particularly, in extreme wind scenarios, this strategy significantly reduces the start-stop cycles of electrolyzers, thereby lowering operational costs and improving overall system performance. The main contribution of this study lies in the novel optimization algorithm and its validation through real-world data, demonstrating its effectiveness in large-scale wind power hydrogen production systems. Our findings provide new insights for enhancing the utilization of renewable energy and the economics of hydrogen production systems. [ABSTRACT FROM AUTHOR]

Energy is one of the essential components for the social and economic growth of urban and rural communities worldwide. However, the lack of energy supply is one of the most significant challenges facing remote or local communities in Nigeria. Distributed generation systems based on renewable energy, conventional sources, or hybrid resources are possible energy production solutions for these communities. This paper, therefore, focused on providing an energy generation system based on photovoltaics (PV) and diesel generators (DG) for stand-alone applications. A comparative analysis was carried out to assess the impact of control strategies, namely load following (LF), cycle charging (CC), and combined dispatch (CD). The designed energy systems: 60 kW PV, 78.69 kW PV, PV-DG-LF, PV-DG-CC, and PV-DG-CD were simulated using HOMER Pro while technical, economic, and environmental indices were used as performance metrics. Simulation results showed that 60 kW PV generated 84,927 and 75,859 kWh, without and with temperature effect, respectively, with the corresponding unmet electric load (UEL) of 13.8 and 14.2%. The result further demonstrated that PV-DG-LF is the optimal design with the highest renewable penetration of 80.7% and the least annual total fuel consumption (TFC) of 6,594 l. The economic results further confirm the suitability of PV-DG-LF with the lowest fuel cost (FC) and moderate cost of energy (COE) of $219,934 and 0.302 $/kWh, respectively. The PV-DG-LF is found to be more environmentally friendly, with the least annual CO 2 emission of 16,629.652 kg. The study considers veritable strategies to achieve affordable, clean, and reliable energy in line with research efforts on realizing the sustainable development goal (SDG) 7. [ABSTRACT FROM AUTHOR]

The increasing greenhouse gas (GHG) emission and environmental degradation (ED) is a serious concern for the various economies, and a similar issue is observed in Asia. This paper investigated the role of clean energy from renewable sources, urbanization, and economic growth in determining the level of GHG emissions from 1995 to 2018 for ten Asian States through a cross-sectional autoregressive distributed lagged (CS-ARDL) model. Meanwhile, the current research also examined the cross-sectional dependence, unit root properties, and co-integration between the study variables. The study findings confirmed that clean energy and GDP2 played their constructive role in reducing GHG emissions in the natural environment or targeted economies. In contrast, urbanization and economic growth caused more GHG emissions both in the long and short run. Furthermore, the robust check through augmented mean group (AMG) and common correlated effect means group (CCEMG) also confirmed that clean energy and GDP2 have a good sign for lowering ED compared to GDP and urbanization. The study findings could support policymakers, specifically in the field of energy economics and environmental sustainability. Therefore, it is highly recommended that some strong policy implications are needed to reduce environmental issues through controlling the negative impact of economic growth and urbanization. This study contributes in the literature of GHG emission with respect to economic growth, urbanization and clean energy and guided the regulators while formulating policies related to control the GHG emission. • The increasing GHG emission is a serious concern for the various economies. • We examined the clean energy, urbanization and economic growth impact on GHG emissions. • We examined cross-sectional dependence, unit root and cointegration among variables. • Clean energy plays constructive role in reducing GHG emissions in natural environment. • Urbanization and economic growth caused more GHG emissions in long and short run. [ABSTRACT FROM AUTHOR]