Mobile Storage Research Articles

Effect of Electromagnetic-Radiofrequency Devices on Male Infertility at Urban Private Infertility Clinics in East Java

Background: As technology becomes increasingly integrated into urban lifestyles, the use of mobile phones, laptops/computers, and WiFi has surged, reshaping habits and routines. However, this reliance on devices raises concerns about potential health impacts, including male infertility rates. This study explores how lifestyle factors, particularly mobile phone usage and exposure to electromagnetic radiation (EMR) and radio frequencies (RF), influence male infertility. Methods: Conducted in Surabaya, Indonesia, this study analyzed sperm analysis data from 260 husbands attending private infertility clinics. Data spanning 2018 to 2023 were collected, with interviews conducted to assess EMR-RF exposure. Statistical analysis using the Mann-Whitney test evaluated differences in sperm analysis results between groups exposed to EMR-RF and controls. Results: A notable prevalence of EMR-RF exposure was observed among men aged 31-40, particularly those working indoors. Significant associations were found between EMR-RF exposure and sperm analysis results, with key factors such as mobile phone usage duration, storage practices, and WiFi exposure showing statistically significant correlations (p < 0.05). Conclusion: This study highlights the impact of EMR-RF exposure on male fertility, particularly concerning mobile phone use and WiFi exposure. These findings underscore the importance of further research and potential interventions to mitigate the health risks associated with EMR-RF exposure in urban populations.

A two-layer economic resilience model for distribution network restoration after natural disasters

Improving the resilience of energy networks and minimizing outages is crucial, making the development of self-healing strategies essential for ensuring a continuous power supply and boosting resilience. As decentralized prosumers become more integrated into smart grids, innovative coordination methods are required to fully leverage their potential and improve the system's self-healing capabilities. Hence, in this paper, we present a decentralized two-layer model for active distribution networks (ADNs) incorporating commercial energy hubs, Parking lots (PLs), hydrogen refueling stations, and mobile units (MUs). This model aims to maximize the flexible capacities of flexible prosumers under emergencies and includes a dynamic mechanism for transporting hydrogen to refueling stations via trucks. In the first layer of the model, the AND operator provides the required services to flexible prosumers, including commercial energy hubs, PLs and hydrogen refueling stations. During this layer, the movement paths of mobile units, such as battery-based mobile storage units (MSUs) and mobile hydrogen units (MHUs), are determined. In the second layer, prosumers independently plan and decide the extent of their service contributions. Subsequently, with the actual service capacities established, the AND operator re-optimizes the initial planning to finalize the system schedule and precise movement paths of the mobile units. The proposed model was tested on a modified 83-bus distribution network using the CPLEX solver in GAMS. Simulation results demonstrate a 54.9 % reduction in forced load shedding (FLS) due to the dispatch of mobile units and a further 84.4 %% reduction in FLS from leveraging the flexible capacities of commercial energy hubs and PLs.

Adsorption‐Based Thermal Energy Storage Using Zeolites for Mobile Heat Transfer

ABSTRACTThe utilization of the water–zeolite pair as an adsorbate–adsorbent system has garnered significant attention in the realm of thermochemical energy storage, offering great potential for various applications. Despite promising results in laboratory settings, widespread implementation of this technology has yet to be realized. Recent advancements in mobile thermal energy storage (m‐TES) employing thermochemical materials have opened new avenues for enhancing the practicality and cost‐effectiveness of solar thermal energy harnessing and waste heat recovery. This experimental study investigates the feasibility of storing thermal energy in zeolites, charged externally to the heat recovery reactor, and discusses the potential applications of externally charged zeolites for m‐TES over short distances, shedding light on their practicality and significance in advancing the field of mobile thermal energy storage. Our findings reveal that zeolites charged at 200°C and subsequently stored outside the discharging unit exhibit an impressive energy storage density (ESD) exceeding 110 kWhth/m3 under conditions of 0.45 m/s air velocity and 60% relative humidity during zeolite discharging. These ESD values are comparable to previously reported figures in the literature. Moreover, ESD values of 30.6 kWhth/m3 were achieved by charging zeolite beads contained within packed transportable tubes constructed from stainless‐steel mesh.

Distributed battery energy storage systems for deferring distribution network reinforcements under sustained load growth scenarios

Energy storage systems can be leveraged in electricity distribution network planning as mitigation alternatives to traditional grid reinforcements if they are strategically installed and operated to reduce congestion and voltage limit violations. This paper examines the technical and economic viability of distributed battery energy storage systems owned by the system operator as an alternative to distribution network reinforcements. The case study analyzes the installation of battery energy storage systems in a real 500-bus Spanish medium voltage grid under sustained load growth scenarios. The results show that, in general, dedicated battery energy storage systems are only a cost-efficient alternative in distribution system planning under very specific conditions, such as when low load growth rates are expected. Nevertheless, they are only required for peak shaving a few days per year. For the analyzed case study, the recoverable portion of their total cost through deferral of distribution system upgrades is higher than the fraction of cycles required for peak shaving under all sustained load growth scenarios. Therefore, it is also explored if mobile battery energy storage systems, capital grants, and revenue stacking can enable battery energy storage systems to become an efficient distribution system planning alternative.

Strategic investments in mobile and stationary energy storage for low-carbon power systems

The main feature and trend of the distribution system is the integration of renewable energy with high penetration rates. The variability and zero marginal cost characteristics of renewable energy will lead to drastically fluctuating locational marginal prices. In the deregulated electricity market, merchants have incentives to utilize energy storage and price arbitrage. Mobile energy storage has a short capital payback period and is widely recognized for transferring energy in the temporal and spatial dimensions. This paper analyses the interaction between merchants and distribution system operators and presents a hybrid energy storage strategic investment framework using bi-level programming. In the upper-level problem, the merchant formulates the capacity, location, and operation strategy of different energy storage to maximize the market revenue of hybrid energy storage, which is paid for by the locational marginal price. In the lower-level problem, the distribution system operator develops an optimal dispatch strategy considering renewable energy and merchant investments. A joint energy and reserve market clearing procedure is performed to derive the locational marginal prices. In the lower-level problem, a data-driven solution strategy based on machine learning is introduced. It uses deep neural networks to approximate the mapping relationship between distribution system states and locational marginal prices. The presented methodology is implemented in an IEEE-33 node system. The results demonstrate that, compared to the basic case, the hybrid energy storage investment strategy has led to an 8.1 % increase in merchant profits and a 12.9 % reduction in the operational costs of the distribution network. The deep neural network approximator fully avoids the lower-level problem with less than 5 % optimality loss.

Collaborative deployment of multiple reinforcement methods for network‐loss reduction in distribution system with seasonal loads

AbstractThe integration of seasonal loads, such as cereal baking and aquatic‐product processing loads, often leads to significant voltage deviations and severe peak loads of the distribution system during specific periods, resulting in increased network losses. Traditional approaches for reducing network losses are becoming less effective and cost‐efficient due to the spatiotemporally uneven distribution characteristics of seasonal loads. To address this issue, this study proposes an optimisation model that collaboratively integrates mobile energy storage, switching capacitors, and tie lines to minimise annual network losses in special planning scenarios affected by seasonal loads. The deployment strategies of multiple reinforcement methods are thoroughly analysed, greatly enhancing the explainability and feasibility of the collaborative deployment model. Then, the proposed model is reformulated to a mixed‐integer linear programming model using the inscribed regular dodecagon approximation approach, thereby making it trackable for state‐of‐the‐art solvers. To illustrate the effectiveness of the model, case studies are conducted on a unique 55‐bus distribution system located in East China, which contains feeders with substantial seasonal variation aquaculture loads and with general loads. The effectiveness of multiple reinforcement methods is thoroughly analysed through detailed numerical results. Furthermore, a sensitivity analysis of the investment budget is conducted.

Active and reactive power coordination optimization for active distribution network considering mobile energy storage system and dynamic network reconfiguration

The active distribution network (ADN) can face with challenges due to the increasing renewable distributed generation (RDG), which may result in elevated network losses and voltage fluctuations. To address these issues, a novel operation strategy is proposed which integrates the mobile energy storage system (MESS) and dynamic network reconfiguration (DNR) to adjust the active and reactive power of the ADN. The transportation network (TN) is modeled considering the traffic congestion, and the path movement of MESS in TN is converted to the switching of virtual switch (VS) in ADN. A coordinated optimal model is formulated for DNR and MESS, furthermore, which can be transformed into a mixed-integer second-order cone programming (MISOCP) model. The penalty alternating direction method (PADM) is employed to enhance the computational efficiency. Then the proposed strategy is tested by the IEEE 33-bus system coupled with the 15-node transportation systems, and the stability of the proposed strategy was validated in a larger scale expansion system. The simulation results demonstrate that the coordinated optimal strategy considering MESS and DNR can effectively reduce network loss and transportation cost, enhance the voltage quality of the ADN and promote the consumption of renewable energy.

Enhance hydrogen storage in lightweight solid-state systems based on Poly(vinylnaphthalene)

This article highlights the potential of poly(2-vinylnaphthalene) (PVN) as a novel light-weight solid-state hydrogen storage system for various applications. With an impressive theoretical gravimetric hydrogen capacity of 5.2 wt.-%, PVN stands out for its attractiveness as a hydrogen carrier. The material possesses advantageous characteristics, including moldability, low toxicity, and ease of storage, making it a promising candidate for both stationary and mobile hydrogen storage applications. Experimental findings demonstrate that PVN can be hydrogenated by up to 76 % utilizing an Ru/Al2O3 catalyst at 250 °C for 24 h. Confirmation of the hydrogenation reaction, which results in poly(2-vinyldecalin), was achieved through characterization techniques such as FTIR, 1H NMR, and spectroscopic ellipsometry. The study of the effects of hydrogen pressure and reaction time identified moderate conditions as favorable, though a further exploration of different catalysts is suggested for optimal conversion. A palladium-based catalyst was employed to release hydrogen from the hydrogenated polymer, demonstrating almost complete reversibility of the hydrogenation of poly(2-vinylnaphthalene) with a dehydrogenation yield of 90 %.

Vehicle To Building (V2b) Peak Load Shaving and Tariff Analysis

Abstract Commercial buildings are essentially important energy consumers for national electricity grid provider as it’s owned by businesses owners that directly keep up the national gross domestic product (GDP). Soaring load demand from commercial buildings usually occurs within few hours on peak business hour. Electricity grid infrastructure designed to support maximum demand of the system but underutilize most of the time outside the peak session. Growing number of EV penetration in local market can serve as mobile energy storage for Vehicle to Building (V2B) energy integration thus enable peak load shaving to minimize maximum demand during peak period. This study presents a feasible methodology approach on determining the suitable V2B tariff on several peak load shaving scenarios to provide attractive return to building owner and discounted off-peak tariff to accommodate lower EV owner’s charging cost. By having the combination of attractive V2B and off-peak tariff that benefits both sides, subsequently increase EV penetration for V2B. It may also charm EV markets as it minimizes the total cost of EV ownership and reduce maximum demand from electricity grid. Hence it reduces the transportation CO2 emissions and contribution toward optimization of grid network electrical infrastructure of transmission and distribution systems design with lower maximum design system requirement.

Some aspects of reliability prediction of chemical industry and hydrogen energy facilities (vessels, machinery and equipment) operated in emergency situations and extreme conditions

This work is aimed at a comprehensive solution to the problem of reliable and safe operation of a transport energy system with a high energy concentration based on a universal energy carrier - cryogenic liquid hydrogen.The article discusses the possibility of using various methods and techniques to assess the reliability of machines and equipment operated in emergency situations and extreme conditions. The obtained results are analyzed.Currently, the oil and gas complex pays great attention to the development of hydrogen technologies, as well as hydrogen energy in connection with the relevance of the Climate Agenda. In this regard, hydrogen energy facilities are of the greatest interest: cryogenic hydrogen reservoirs, cryogenic hydrogen pipelines, cryogenic oxygen reservoirs and cryogenic oxygen pipelines, as well as cryogenic reservoirs and pipelines for storing process nitrogen gas. An important role for global energy exchange is played by LH2 tankers for transporting cryogenic hydrogen. For example, Australia and Japan built the first LH2 tanker to transport hydrogen from Australia to Japan. In addition, another 85 LH2 tankers are expected to be built.After transportation, cryogenic hydrogen is stored in cryogenic hydrogen storages, usually also representing cryogenic hydrogen tanks with piping in the form of cryogenic pipelines, as well as cryogenic nitrogen tanks for storing process nitrogen gas. Further, hydrogen is used in road transport, aviation, ship fleet, industry, and energy. The main elements of mobile, stationary and airborne hydrogen storage systems are under critical loads and are in the area of increased study and attention.In this regard, we considered the functions of changing the main operational characteristics, made proposals on the possibility of predicting the development of accumulated faults and proposals for ensuring safety and extending the life of objects, taking into account the determination of local and integral damage to cryogenic tanks and pipelines.

How to choose mobile energy storage or fixed energy storage in high proportion renewable energy scenarios: Evidence in China

With the large-scale integration of renewable energy and changes in load characteristics, the power system is facing challenges of volatility and instability. Therefore, enhancing the safe and stable operation capability of the power system is an urgent problem that needs to be solved. Mobile energy storage can improve system flexibility, stability, and regional connectivity, and has the potential to serve as a supplement or even substitute for fixed energy storage in the future. However, there are few studies that comprehensively evaluate the operational performance and economy of fixed and mobile energy storage systems. To comprehensively evaluate the economic benefits of large-scale mobile energy storage systems, this paper constructs an overall horizontal cost model for energy storage systems that considers the power system and train transportation system. This model not only introduces the traditional concept of lifecycle cost of energy storage systems, but also considers the costs of traditional transmission lines and battery transportation. Secondly, to achieve simulation of large-scale mobile energy storage system planning and operation, this paper establishes a multi-region power planning and operation simulation (MPO) model and a battery transportation and logistics (BTL) model to accurately reflect the operation mode of fixed energy storage and mobile energy storage in the power system. Finally, taking the actual power grids and railway networks in Northeast and North China as case studies, this article provides an in-depth analysis of the technical, economic, and environmental performance of large fixed and mobile energy storage systems, and conducts a detailed comparison. The research results indicate that under high grid connection ratios (using 75% and 66% as examples), the overall cost of mobile energy storage systems continues to decrease to 1.42 CNY/kWh and 0.98 CNY/kWh. Compared to fixed energy storage at 5.45 CNY/kWh and 4.79 CNY/kWh, it has an absolute economic advantage and shows significant carbon reduction capabilities, reaching 241,800 to 1,394,600 tons. This discovery fully confirms the enormous potential and application value of mobile energy storage in high proportion renewable energy scenarios, providing strong technical support and economic analysis basis for the sustainable development of the power system.

Strategic operation of electric vehicle in residential microgrid with vehicle-to-home features

The urgent need for innovative energy solutions to facilitate the transition to renewable energy and electric vehicles (EVs) is particularly critical in developing countries, where high emissions and grid reliability challenges persist. This study investigates an off-grid residential renewable energy system with stationary storage like battery and hydrogen, alongside an EV as mobile storage. A bi-level optimization framework is established considering stationary and mobile energy storage options and a strategy is proposed to implement Vehicle-to-Home (V2H) in off-gird settings. Three cases are studied, with optimal component sizing determined using an optimization tool integrated with MATLAB. Firstly, to determine the most cost-effective stationary storage alternative, Case 1 uses hydrogen and Case 2 employs a battery as storage. Then Case 3 integrates the optimal stationary storage with mobile storage using V2H technology enabling the EV to support household energy needs during peak times. Results highlight that combining stationary and mobile storage (Case 3) offers a 15.92% reduction in Total Net Present Cost (TNPC) and a 13.9% reduction in Levelized Cost of Energy (LCOE) compared with stationary storage alone. This off-grid system (Case 3) also outperforms the conventional grid economically and environmentally, offering 2.13× TNPC reduction and 7,813 kg/yr carbon emissions mitigation.

Multi-Scale Modeling and Simulation of All-Solid-State Sodium-Ion Batteries with Polymer-Ceramic Hybrid Electrolytes

Lithium-ion batteries (LIBs) have been widely considered as the most promising power source for mobile devices. However, LIBs cannot meet the increasing global demand for electrochemical energy storage in the foreseeable future. Sodium ion-batteries (SIBs) are based on more ecofriendly and earth-abandoned materials. Commonly researched SIBs are based on liquid electrolytes. They pose leakage and thermal runaway risks. Solid polymer electrolytes solve these problems but need to operate at temperatures between 60-80°C to compensate insufficient ionic conductivity of polymer electrolytes at ambient temperatures.We present a polymer-ceramic hybrid electrolyte which overcomes the necessity to operate at high temperatures. It combines the advantages of high ion-conducting solid ceramic particles and flexible polymers. Sodium metal serves as the anode and PEO with inorganic fillers is used as cathode electrolyte. Due to their sustainability and high efficiency —comparable to LIBs— sodium-ion batteries are a promising candidate for small scale stationary energy storage applications or mobile energy storage applications with less constrains regarding energy density (e.g. trains, ships, submarines etc.). This contribution highlights a modeling approach for simulations of a single battery cell to develop an optimal cell design of the aforementioned battery system. A newly developed multiscale modeling method for hybrid polymer-ceramic sodium ion batteries reflects the different length scales of the active particle level and the electrode level. We precisely describe the spatially resolved mass and charge transport as well as electrochemical reactions in the active particle and the surrounding electrolyte employing a finite volume method [1]. Both domains are resolved in 3D and the model framework was validated against experimental data. The model output is incorporated in the connected pseudo-two-dimensional battery model for fast simulations of the overall battery cell considering mass and charge transport. The results support the importance of particle (active particle and ceramic filler particle) properties and configurations as well as electrolyte composition. Based on this, we exploit an evolutionary algorithm to suggest optimized battery designs for different use cases. In Addition, we present the evaluation of electrolyte properties with solid-state NMR spectroscopy and their model implementation [2]. μCT imaging experimentally investigates the cathode half-cell morphology. The derived virtual reconstructions enable realistic microstructure simulations of the battery cells. In this presentation, we will suggest two cell designs: The high-energy cell optimizes material efficiency and energy density. The high-power cell opts for high power densities (fast charging).In summary, we present a novel all-solid-state polymer-ceramic hybrid sodium-ion battery type for small stationary or large mobile energy storage units. Our contribution outlines a simulation approach that sheds light on macroscopic and microscopic processes inside the battery-cell using a multiscale modeling method. As a result, a high-energy and a high-power design is derived. Gerbig, M. Holzapfel and H. Nirschl, J. Electrochem. Soc., 170(4), 40517 (2023).Moradipour, A. Markert, T. Rudszuck, N. Röttgen, G. Dück, M. Finsterbusch, F. Gerbig, H. Nirschl and G. Guthausen, J Energ Power Technol, 05(04), 1–21 (2023).

Energy management in integrated energy system with electric vehicles as mobile energy storage: An approach using bi-level deep reinforcement learning

The integrated energy system with electric vehicle charging station via vehicle-to-grid aims to offer a proactive solution for low-carbon development of both energy and transportation sectors. However, achieving optimal energy efficiency with minimal operational costs in such a complex system is challenging due to the high randomness of electric vehicle travel patterns. This work proposes a reinforcement learning-based energy management framework to optimize the coordinated scheduling of integrated energy and vehicle-to-grid. The problem is modeled as a Markov Decision Process and optimized using the bi-level soft actor-critic algorithm, where the upper-level agent supervises the scheduling of the integrated energy system, and lower-level agent sets the electric vehicles’ charging and discharging strategies based on upper-level decision. Numerical simulations demonstrated that by adopting a bi-level reinforcement learning approach, the proposed algorithm effectively enhances energy exchange between integrated energy and electric vehicle charging station, reducing operational costs by 8 % compared to other multi-agent algorithms. Furthermore, when compared to the Mixed-Integer Linear Programming model, the proposed algorithm achieves similar optimality with significantly less computation time, maintaining a margin of error of approximately 4 %. Additionally, integrating electric vehicles as mobile energy storage within this framework can lead to a further 10 % reduction in operating costs.

Distributionally robust CVaR optimization for resilient distribution system planning with consideration for long-term and short-term uncertainties

Climate change is exerting excessive strain on the environment, leading to an ever-increasing frequency of extreme weather events that negatively impact distribution systems. To mitigate these impacts, this paper presents a distributionally robust conditional value-at-risk (DR-CVaR) optimization approach for resilience-oriented distribution system planning. Firstly, a resilience-oriented distribution system planning model is developed, which incorporates flexible operational resources, such as mobile energy storage prepositioning and demand response program, in the emergency response phase. Then, the uncertainties associated with extreme weather events are addressed using a DR-CVaR optimization approach, where the short-term uncertainty in the occurrence of outages caused by specific extreme weather events is addressed through a distributionally robust optimization approach, while the long-term uncertainty regarding the risk of potential extreme weather events is addressed by a conditional value-at-risk optimization approach. The DR-CVaR model is eventually transformed into an equivalent three-level model and solved using a customized nested column-and-constraint generation algorithm. Finally, case studies are conducted based on the IEEE 33-bus distribution system under several extreme weather events. The numerical results show that the proposed model can reduce the load shedding cost as well as investment cost, which confirms the effectiveness and superiority of the proposed model.

Aggregator-supported strategy for electric bus fleet charging: A hierarchical optimisation approach

The increasing adoption of electric buses in cities presents an opportunity for these vehicles to serve as mobile energy storage systems, providing valuable grid services through their substantial battery capacity. However, the complex interplay of fleet management and energy market participation requires that public transportation operators (PTOs) use adequate optimisation models and algorithms to make the best operational decisions. To address these issues, our research proposes an aggregator-supported charging strategy using a bi-level optimisation framework for electric bus fleets. The main goal is to achieve a balance between reducing PTO operational costs and maximising aggregator revenues, while ensuring reliable bus system operation. The results indicate that a coordinated charging strategy, including energy arbitrage and reserve provision, can significantly reduce operational costs, although potential limitations arise from associated battery degradation costs. Furthermore, managing fleets for reserve services appears to be more lucrative than engaging in energy arbitrage schemes. In this context, this study emphasizes the role of aggregator entities in managing the energy flexibility of electric bus fleets and enhancing the sustainability and cost-effectiveness of urban public transportation.

Sizing of storage‐based renewable off‐grid system according to supply of electrical and thermal energies considering unscented transformation‐based stochastic optimization: A case study

AbstractThe paper presents the planning (sizing) of a hybrid islanded system containing only renewable sources including wind turbines, photovoltaics, and bio‐waste energy units for the simultaneous supply of electrical and thermal energy. The mentioned renewable sources are used to supply electrical energy. The bio‐waste unit (BEU) is equipped with combined electrical and thermal technology. It is used along with heat pumps to supply thermal energy. Electrical and thermal storage are employed to make the renewable power output as close as possible to the demand level. Electric storage can be either stationary (e.g., battery) or mobile (e.g., electric vehicles), but thermal storage is as stationary type of storage. In the following, the proposed scheme minimizes construction and maintenance costs imposed by power sources, storage devices, and power electronic converters, and expected storage degradation cost. This plan is bound to the model of operation of sources, storage devices, and power electronic converters. In this model, renewables are the main source of power to supply consumers, where storage is adopted to increase the generation level to make it as close as possible to the demand curve. The uncertain parameters are imposed by the load, renewable phenomena, and mobile storage parameters. To model these uncertainties, stochastic optimization based on unscented transformation is used. Finally, the findings of the paper demonstrate that the suggested scheme succeeds in the economic planning of the system with a simultaneous supply of electrical and thermal energy. The BEU equipped with a combined electricity and heat system along with thermal storage and a heat pump to supply thermal load besides providing electric energy can reduce the planning cost by 2.9% compared with the case with only electrical energy. Also, the mobile storage presence in the hybrid system can reduce the number of stationary storage devices, which alone results in a 7.7% decrease in the planning cost of the hybrid system.

Quantifying the decarbonization potential of mobile heat battery in low-temperature district heating

This research assesses the potential of a mobile thermochemical storage system, the mobile heat battery (M-HB), for decarbonizing a low-temperature district heating (DH) system in the Netherlands. The assessment is built on a case study where the M-HB is used to transport waste heat from different sources to a neighborhood interface of a DH system. This case study utilizes a simulation-based methodology to calculate the emissions from grid electricity, DH, and M-HB transport and charging. Building performance simulation is used as the main experimental method in combination with both empirical data and theoretical assumptions. Various system operational strategies and uncertain factors are explored, and waste heat sources are screened by different decarbonization targets. Findings indicate that using the M-HB can reduce the operational carbon emissions by up to 80 %, from approximately 60–70 KgCO2/GJ of the system without M-HB to around 13 KgCO2/GJ in optimal scenarios. Emissions from M-HB transport and charging are identified as more influential to the decarbonization potential than other considered factors, which addresses the significance of choosing proper waste heat sources. Despite some limitations from data availability and assumptions, this work identifies both opportunities and challenges for using M-HB to decarbonize DH systems.

Assumption on the optimization direction of positive electrode materials and new methods for recycling electrode materials in lithium-ion batteries

Abstract With the increasing scarcity of non-recyclable resources such as international fossil energy and coal industries, representatives from various countries at the Paris Summit advocated the strategy of “carbon neutrality, carbon peaking” and promoted the use of recyclable resources, namely electricity. There are many ways to generate electricity, such as solar power, hydroelectric power, thermal power, tidal power and wind power. However, the method of mobile storage of electricity is relatively single - using batteries. The most widely used mobile battery currently is lithium-ion battery. This research will focus on the different choices of cathode materials for lithium-ion batteries, analysing and comparing their performance, functional stability, lifespan, capacity, price, and working conditions under extreme temperatures. At the same time, in-depth analysis will be conducted on existing electrode material recycling methods. Finally, the development direction of electrode materials with economic benefits and promising development prospects, as well as recycling methods that are more in line with economic benefits and increase resource utilization, are proposed.

Magnesium-Based Hydrogen Storage Alloys: Advances, Strategies, and Future Outlook for Clean Energy Applications.

Magnesium-based hydrogen storage alloys have attracted significant attention as promising materials for solid-state hydrogen storage due to their high hydrogen storage capacity, abundant reserves, low cost, and reversibility. However, the widespread application of these alloys is hindered by several challenges, including slow hydrogen absorption/desorption kinetics, high thermodynamic stability of magnesium hydride, and limited cycle life. This comprehensive review provides an in-depth overview of the recent advances in magnesium-based hydrogen storage alloys, covering their fundamental properties, synthesis methods, modification strategies, hydrogen storage performance, and potential applications. The review discusses the thermodynamic and kinetic properties of magnesium-based alloys, as well as the effects of alloying, nanostructuring, and surface modification on their hydrogen storage performance. The hydrogen absorption/desorption properties of different magnesium-based alloy systems are compared, and the influence of various modification strategies on these properties is examined. The review also explores the potential applications of magnesium-based hydrogen storage alloys, including mobile and stationary hydrogen storage, rechargeable batteries, and thermal energy storage. Finally, the current challenges and future research directions in this field are discussed, highlighting the need for fundamental understanding of hydrogen storage mechanisms, development of novel alloy compositions, optimization of modification strategies, integration of magnesium-based alloys into hydrogen storage systems, and collaboration between academia and industry.