In the face of the burgeoning electricity demands and the imperative for sustainable development amidst rapid industrialization, this study introduces a dynamic and adaptable framework suitable for policymakers and re...
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In the face of the burgeoning electricity demands and the imperative for sustainable development amidst rapid industrialization, this study introduces a dynamic and adaptable framework suitable for policymakers and renewable energy experts working on integrating and optimizing renewable energy solutions. While using a case study representative model for Sub-Saharan Africa (SSA) to demonstrate the challenges and opportunities present in introducing optimization methods to bridge power supply deficits and the scalability of the model to other regions, this study presents an agile multi-criteria decision tool that pivots on four key development phases, advancing established methodologies and pioneering refined computationaltechniques, to select optimal configurations from a set of Policy Decision-Making Metrics (PDM-DPS). Central to this investigation lies a rigorous comparative analysis of variants of three advanced algorithmic approaches: Swarm-Based Multi-objective Particle Swarm Optimization (MOPSO), Decomposition-Based Multi-objective Evolutionary Algorithm (MOEA/D), and Evolutionary-Based Strength Pareto Evolutionary Algorithm (SPEA2). These are applied to a grid-connected hybrid system, evaluated through a comprehensive 8760-hour simulation over a 20-year planning horizon. The evaluation is further enhanced by a set of refined Algorithm Performance Evaluation Metrics (AL-PEM) tailored to the specific constraints. The findings not only underscore the robustness and consistency of the SPEA2 variant over 15 runs of 200 generations each, which ranks first on the AL-PEM scale, but the findings also validate the strategic merit of combining multiple technologies and empowering policymakers with a versatile toolkit for informed decision-making.
Solid-state lithium batteries (SSLBs) based on solid-state electrolytes (SSEs) are considered ideal candidates to overcome the energy density limitations and safety hazards of traditional Li-ion batteries. However, fe...
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Solid-state lithium batteries (SSLBs) based on solid-state electrolytes (SSEs) are considered ideal candidates to overcome the energy density limitations and safety hazards of traditional Li-ion batteries. However, few individual SSEs fulfill the standard requirements for practical applications owing to their poor performance. Hybrid electrolytes, which rationally integrate the benefits of single inorganic solid electrolytes (ISEs) and solid polymer electrolytes (SPEs) as well as achieve sufficiently high ionic conductivity, low interfacial impedance, and high electrode stability, have attracted significant interest for use in SSLBs. In this review, we describe the chronological progress of solid electrolytes as well as the properties of and challenges associated with single ISEs, SPEs, and hybrid electrolytes. State-of-the-art strategies for overcoming the inherent challenges of hybrid electrolytes, including insufficient ionic conductivity;undesirable electrochemical, thermal, and mechanical properties;and large electrolyte-electrode interfacial impedances, are also summarized. Finally, advanced computational techniques, including density functional theory calculations, ab initio molecular dynamics simulations, and machine-learning-assisted simulation strategies, which complement experimental systems, are discussed. The challenges and future technological perspectives associated with hybrid electrolytes for practical energy-storage systems are also highlighted.
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