Review of Hot Topics in the Sustainable Development of Energy, Water, and Environment Systems Conference in 2022

In recent years, the modeling and simulation of lithium-ion batteries have garnered attention due to the rising demand for reliable energy storage. Accurate charge cycle predictions are fundamental for optimizing battery performance and lifespan. This study compares particle swarm optimization (PSO) and grey wolf optimization (GWO) algorithms in modeling a commercial lithium-ion battery, emphasizing the voltage behavior and the current delivered to the battery. Bio-inspired optimization tunes parameters to reduce the root mean square error (RMSE) between simulated and experimental outputs. The model, implemented in MATLAB/Simulink, integrates electrochemical parameters and estimates battery behavior under varied conditions. The assessment of terminal voltage revealed notable enhancements in the model through both the PSO and GWO algorithms compared to the non-optimized model. The GWO-optimized model demonstrated superior performance, with a reduced RMSE of 0.1700 (25 °C; 3.6 C, 455 s) and 0.1705 (25 °C; 3.6 C, 10,654 s) compared to the PSO-optimized model, achieving a 42% average RMSE reduction. Battery current was identified as a key factor influencing the model analysis, with optimized models, particularly the GWO model, exhibiting enhanced predictive capabilities and slightly lower RMSE values than the PSO model. This offers practical implications for battery integration into energy systems. Analyzing the execution time with different population values for PSO and GWO provides insights into computational complexity. PSO exhibited greater-than-linear dynamics, suggesting a polynomial complexity of O(nk), while GWO implied a potential polynomial complexity within the range of O(nk) or O(2n) based on execution times from populations of 10 to 1000.

Section: Proposed Hybrid-electrical Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimizing Lithium-Ion Battery Modeling: A Comparative Analysis of PSO and GWO Algorithms

Camas-Náfate,

Coronado-Mendoza,

Vargas-Salgado

et al. 2024

“…Alkaline electrolysis devices are extensively utilized in commercial plants due to their cost efficiency and relatively extended lifespan. They are stable, do not require precious metal catalysts, and are relatively inexpensive for initial installations, making them suitable for large-scale facilities [17][18][19][20]. Nevertheless, challenges such as low hydrogen productivity, reduced durability, and difficulty in coping with power fluctuations persist [21].…”

Section: Introductionmentioning

confidence: 99%

Design and Optimization of an Alkaline Electrolysis System for Small-Scale Hydropower Integration

Song,

Kim,

Yang

2023

Alkaline electrolysis systems are currently considered to be suitable for large-scale hydrogen production. Previous research has primarily focused on integrating renewable energy sources such as solar and wind into water electrolysis systems. However, intermittent issues stemming from the sporadic nature of renewable energy sources have led to the introduction of energy storage systems (ESSs) to address these intermittent challenges. Extensive research has been conducted on the efficiency and operational aspects of these systems. In contrast to other renewable energy sources, hydropower offers the advantages of stable output and high utilization, making it a promising solution for overcoming intermittent issues. In this study, we propose the design of an optimized alkaline electrolysis system tailored for small-scale hydropower generation. This approach allowed us to confirm the efficiency of a small-scale hydropower-based hydrogen production facility and the analysis of hydrogen production costs under diverse scenarios. Notably, the optimal selling price per kilogram of hydrogen was determined to be USD 15.6 when the operational time exceeded 20 h, albeit indicating a challenging market supply. Under the consideration of various scenarios and government subsidies, this study revealed that a USD 10/kgH2 subsidy or 24 h of continuous operation achieved break-even points in the sixth and eighth years, respectively. Ultimately, the findings underscore the necessity for essential measures, including government backing and technological advancements in small-scale hydropower facilities, to enhance the economic viability of the green hydrogen market in South Korea.

An Analysis of Greenhouse Gas Emissions in Electrolysis for Certifying Clean Hydrogen

Kim,

Min,

Lee

et al. 2024

The drive for carbon neutrality has led to legislative measures targeting reduced greenhouse gas emissions across the transportation, construction, and industry sectors. Renewable energy sources, especially solar and wind power, play a pivotal role in this transition. However, their intermittent nature necessitates effective storage solutions. Green hydrogen and ammonia have gained attention for their potential to store renewable energy while producing minimal emissions. Despite their theoretical promise of zero greenhouse gas emissions during production, real-world emissions vary based on system configurations and lifecycle assessments, highlighting the need for detailed evaluations of their environmental impact. Therefore, in this study, calculations were performed for the actual amount of produced greenhouse gas emissions that are associated with the production of green hydrogen using electrolysis, from raw material extraction and processing to hydrogen production, with these assessed from well-to-gate emission estimates. Emissions were also evaluated based on various types of renewable energy sources in South Korea, as well as hydrogen production volumes, capacities, and types. Using these data, the following factors were examined in this study: carbon dioxide emissions from the manufacturing stage of electrolysis equipment production, the correlation between materials and carbon dioxide emissions, and process emissions. Current grades of clean hydrogen were verified, and the greenhouse gas reduction effects of green hydrogen were confirmed. These findings are significant against the backdrop of a country such as South Korea, where the proportion of renewable energy in total electricity production is very low at 5.51%. Based on the domestic greenhouse gas emission efficiency standard of 55 kWh/kgH2, it was found that producing 1 kg of hydrogen emits 0.076 kg of carbon dioxide for hydropower, 0.283 kg for wind power, and 0.924 kg for solar power. The carbon dioxide emissions for AWE and PEM stacks were 8434 kg CO2 and 3695 kg CO2, respectively, demonstrating that an alkaline water electrolysis (AWE) system emits about 2.3 times more greenhouse gasses than a proton exchange membrane (PEM) system. This indicates that the total carbon dioxide emissions of green hydrogen are significantly influenced by the type of renewable energy and the type of electrolysis used.