Advances in performance degradation mechanism and safety assessment of LiFePO4for energy storage.

In the context of 'energy shortage', developing a novel energy-based power system is essential for advancing the current power system towards low-carbon solutions. As the usage duration of lithium-ion batteries for energy storage increases, the nonlinear changes in their aging process pose challenges to accurately assess their performance. This paper focuses on the study LiFeO4(LFP), used for energy storage, and explores their performance degradation mechanisms. Furthermore, it introduces common battery models and data structures and algorithms, which used for predicting the correlation between electrode materials and physical parameters, applying to state of health assessment and thermal warning. This paper also discusses the establishment of digital management system. Compared to conventional battery networks, dynamically reconfigurable battery networks can realize real-time monitoring of lithium-ion batteries, and reduce the probability of fault occurrence to an acceptably low level.

Metal Phosphorous Chalcogenide: A Promising Material for Advanced Energy Storage Systems.

The development of efficient and affordable electrode materials is crucial for clean energy storage systems, which are considered a promising strategy for addressing energy crises and environmental issues. Metal phosphorous chalcogenides (MPX3 ) are a fascinating class of two-dimensional materials with a tunable layered structure and high ion conductivity, making them particularly attractive for energy storage applications. This review article aims to comprehensively summarize the latest research progress on MPX3 materials, with a focus on their preparation methods and modulation strategies. Additionally, the diverse applications of these novel materials in alkali metal ion batteries, metal-air batteries, and all-solid-state batteries are highlighted. Finally, the challenges and opportunities of MPX3 materials are presented to inspire their better potential in energy storage applications. This review provides valuable insights into the promising future of MPX3 materials in clean energy storage systems.

Hydrogel Electrolyte Enabled High-Performance Flexible Aqueous Zinc Ion Energy Storage Systems toward Wearable Electronics.

To cater to the swift advance of flexible wearable electronics, there is growing demand for flexible energy storage system (ESS). Aqueous zinc ion energy storage systems (AZIESSs), characterizing safety and low cost, are competitive candidates for flexible energy storage. Hydrogels, as quasi-solid substances, are the appropriate and burgeoning electrolytes that enable high-performance flexible AZIESSs. However, challenges still remain in designing suitable and comprehensive hydrogel electrolyte, which provides flexible AZIESSs with high reversibility and versatility. Hence, the application of hydrogel electrolyte-based AZIESSs in wearable electronics is restricted. A thorough review is required for hydrogel electrolyte design to pave the way for high-performance flexible AZIESSs. This review delves into the engineering of desirable hydrogel electrolytes for flexible AZIESSs from the perspective of electrolyte designers. Detailed descriptions of hydrogel electrolytes in basic characteristics, Zn anode, and cathode stabilization effects as well as their functional properties are provided. Moreover, the application of hydrogel electrolyte-based flexible AZIESSs in wearable electronics is discussed, expecting to accelerate their strides toward lives. Finally, the corresponding challenges and future development trends are also presented, with the hope of inspiring readers.

Construction Building Materials as a Potential for Structural Supercapacitor Applications.

Emerging demands to achieve zero carbon emissions and develop renewable energy resources necessitate the development of appropriate energy storage systems. To achieve this, several alternatives to conventional energy storage devices, such as Li-ion batteries or capacitors to more sustainable and scalable energy storage systems, are being explored. Supercapacitors, possess unique characteristics that include high power, long life, and environmental-friendly design. They may be used to bridge the energy-power gap between typical capacitors and fuel cells/batteries. Recently, structural supercapacitors being capable of storing electrochemical energy besides bearing mechanical load have caught the attention of researchers. As such, efforts have been made worldwide to study both the fundamental and applied aspects of structural supercapacitors. Further, the possibility of using construction materials for interdisciplinary applications is being studied because they are relatively cheap and easily available. Thus, construction materials can be considered as potential candidates for the development of structural supercapacitors. Herein an overview on the use of construction materials, such as Portland cement concrete, geopolymer concrete, and bricks, as a component of structural supercapacitors has been presented.

Future assessment of the impact of the COVID-19 pandemic on the electricity market based on a stochastic socioeconomic model.

This paper proposes a time-series stochastic socioeconomic model for analyzing the impact of the pandemic on the regulated distribution electricity market. The proposed methodology combines the optimized tariff model (socioeconomic market model) and the random walk concept (risk assessment technique) to ensure robustness/accuracy. The model enables both a past and future analysis of the impact of the pandemic, which is essential to prepare regulatory agencies beforehand and allow enough time for the development of efficient public policies. By applying it to six Brazilian concession areas, results demonstrate that consumers have been/will be heavily affected in general, mainly due to the high electricity tariffs that took place with the pandemic, overcoming the natural trend of the market. In contrast, the model demonstrates that the pandemic did not/will not significantly harm power distribution companies in general, mainly due to the loan granted by the regulator agency, named COVID-account. Socioeconomic welfare losses averaging 500 (MR$/month) are estimated for the equivalent concession area, i.e., the sum of the six analyzed concession areas. Furthermore, this paper proposes a stochastic optimization problem to mitigate the impact of the pandemic on the electricity market over time, considering the interests of consumers, power distribution companies, and the government. Results demonstrate that it is successful as the tariffs provided by the algorithm compensate for the reduction in demand while increasing the socioeconomic welfare of the market.

Designing Nanostructured Metal Chalcogenides as Cathode Materials for Rechargeable Magnesium Batteries.

Rechargeable magnesium batteries (RMBs) are regarded as promising candidates for beyond-lithium-ion batteries owing to their high energy density. Moreover, as Mg metal is earth-abundant and has low propensity for dendritic growth, RMBs have the advantages of being more affordable and safer than the currently used lithium-ion batteries. However, the commercial viability of RMBs has been negatively impacted by slow diffusion kinetics in most cathode materials due to the high charge density and strongly polarizing nature of the Mg2+ ion. Nanostructuring of potential cathode materials such as metal chalcogenides offers an effective means of addressing these challenges by providing larger surface area and shorter migration routes. In this article, a review of recent research on the design of metal chalcogenide nanostructures for RMBs' cathode materials is provided. The different types and structures of metal chalcogenide cathodes are discussed, and the synthetic strategies through which nanostructuring of these materials can be achieved are described. An organized summary of their electrochemical performance is also presented, along with an analysis of the current challenges and future directions. Although particular focus is placed on RMBs, many of the nanostructuring concepts that are discussed here can be carried forward to other next-generation energy storage systems.

A rare-event study of frequency regulation and contingency services from grid-scale batteries.

We perform a rare-event study on a simulated power system in which grid-scale batteries provide both regulation and emergency frequency control ancillary services. Using a model of random power disturbances at each bus, we employ the skipping sampler, a Markov Chain Monte Carlo algorithm for rare-event sampling, to build conditional distributions of the power disturbances leading to two kinds of instability: frequency excursions outside the normal operating band, and load shedding. Potential saturation in the benefits, and competition between the two services, are explored as the battery maximum power output increases. This article is part of the theme issue 'The mathematics of energy systems'.

High-capacity anode materials for sodium-ion batteries.

Na-ion batteries are an attractive alternative to Li-ion batteries for large-scale energy storage systems because of their low cost and the abundant Na resources. This Review provides a comprehensive overview of selected anode materials with high reversible capacities that can increase the energy density of Na-ion batteries. Moreover, we discuss the reaction and failure mechanisms of those anode materials with a view to suggesting promising strategies for improving their electrochemical performance.

Comprehensive decision-making considerations in the transition to electrification transportation system in a developing country.

Introducing suitable alternatives to the existing fossil fuels can provide insightful aspects of the expected benefits. In the energy sector, the transportation system is one of the key contributors to fossil fuel consumption and greenhouse gas productions. To elaborate on the performance of each introduced alternative, two perspectives are considered; short-term and long-term evaluations. In the short outlook, the PROMETHEE method is used for evaluation. Six scenarios are introduced based on the technical, economic, social, and policy criteria and each scenario benefits from different weights. In this scheme, the impacts of evolutions in the battery applications in the vehicles are investigated. Based on the short-term study, CNG and gasoline are considered the best options for the fuels of vehicles in Iran by taking into consideration the current situation. By viewing the technical and economic criteria, it was concluded that the Li-Ion battery provides better performance in comparison with gasoline in the long run. By 2040, the number of EVs will reach 10% of the overall vehicle production. It is obtained that the benefits of the electrical vehicles' presence as the alternative to the internal combustion vehicles can provide growing interest in this outlook from 2.02 × 106 US$ in 2025 to 17.55 × 108 US$ in 2040.

A two-step identification approach for an extended nonlinear double-capacitor model.

Equivalent circuits are one of the most used models for Li-ion cells in the automotive area. However, it is a challenge to these models to be able to capture the cell discharge capacity under different loads, while still being accurate on both continuous charge and dynamic tests, fast to compute, and easy to parametrize from non-specialized data. To tackle this challenge, this paper proposes an extension of the nonlinear double capacitor model by increasing its order, parameter dependency with C-rate, and an identification procedure that exploits the pseudo-linear nature of the problem to find the parameter maps. An analogy between the parts of the circuit and the single particle model is also presented to reduce the search space of the identification algorithm and to enhance model interpretability. The performance of the proposed model extension is analyzed and compared to a state-of-the-art model on a challenging LiFePO4 dataset with different characteristics and validated on a realistic drive cycle, obtaining a mean absolute average error of around 20 mV for both training and validation tests.

An ultra-high gain boost converter with low switching stress for integrated multi-energy storage systems.

In this paper, a high-gain low-switching-stress coupled-inductor with high voltage step-up voltage multiplier cells quadratic boost converter (VMC-QBC) is proposed. The turn ratio of the coupled inductors and the switch duty cycle increase the dynamic gain, and the two degrees of freedom adjustment and modularity of the voltage multiplier cells (VMC) make the structure more flexible. The use of the same drive signal for both switches makes control easier. While achieving multi-stage boosting and multiplication boosting from low to medium duty cycle, the passive clamping circuit absorbs the energy leaked by the coupled inductor, thus reducing the stress on the switching tube and alleviating the diode reverse recovery problem. A non-ideal model with parasitic parameters is developed to analyse the real voltage gain and the converter losses to give design guidelines. A 300 W prototype is designed and tested. The state space model of the converter is established and the working principle is analysed. Compared to other high-gain quadratic boost converters, the proposed converter has continuous input current, common ground characteristics, and high voltage gain at low to medium duty cycles to accommodate integrated multi-energy storage systems.

Sustainable synthesis of spongy-like porous carbon for supercapacitive energy storage systems towards pollution control.

In this study, the fruit of Terminalia chebula, commonly known as chebulic myrobalan, is used as the precursor for carbon for its application in supercapacitors. The Terminalia chebula biomass-derived sponge-like porous carbon (TC-SPC) is synthesized using a facile and economical method of pyrolysis. TC-SPC thus obtained is subjected to XRD, FESEM, TEM, HRTEM, XPS, Raman spectroscopy, ATR-FTIR, and nitrogen adsorption-desorption analyses for their structural and chemical composition. The examination revealed that TC-SPC has a crystalline nature and a mesoporous and microporous structure accompanied by a disordered carbon framework that is doped with heteroatoms such as nitrogen and sulfur. Electrochemical studies are performed on TC-SPC using cyclic voltammetry, galvanostatic charge-discharge, and electrochemical impedance spectroscopy. TC-SPC contributed a maximum specific capacitance of 145 F g-1 obtained at 1 A g-1. The cyclic stability of TC-SPC is significant with 10,000 cycles, maintaining the capacitance retention value of 96%. The results demonstrated that by turning the fruit of Terminalia chebula into an opulent product, a supercapacitor, TC-SPC generated from biomass has proven to be a potential candidate for energy storage application.

Optimal techno-economic assessment of isolated microgrid integrated with fast charging stations using radial basis deep learning.

The global transportation electrification commerce sector is now booming. Stakeholders are paying an increased attention to the integration of electric vehicles and electric buses into  the transportation networks. As a result, there is an urgent need to invest in public charging infrastructure, particularly for fast charging facilities. Consequently, and to complete the portfolio of the green environment, these fast-charging stations (FCSs) are designed using 100% of renewable energy sources (RESs). Thus, this paper proposes an optimization model for the techno-economic assessment of FCSs comprising photovoltaic and wind turbines with various energy storage devices (ESDs). In this regard, the FCS performance is evaluated using flywheels and super capacitors due to their high-power density and charging/discharging cycles and rates. Then, optimal sizing of these distributed generators is attained considering diverse technical and economical key performance indicators. Afterwards, the problem gets more sophisticated by investigating the effect of RES's uncertainties on the selection criterion of the FCS's components, design and capacity. Eventually, as an effort dedicated to an online energy management approach, a deep learning methodology based on radial basis network (RBN) is implemented, validated, and carried out. In stark contrast to conventional optimization approaches, RBN demonstrates its superiority by obtaining the optimum solutions in a relatively short amount of time.

Advancing Anode Performance in Aqueous Zinc-Ion Batteries: A Review of Metal-Organic Framework-Based Strategies.

Aqueous zinc-ion batteries (AZIBs) are garnering substantial research interest in electric vehicles, energy storage systems, and portable electronics, primarily for the reason that the inexpensive cost, high theoretical specific capacity, and environmental sustainability of zinc metal anodes, which are an essential component to their design. Nonetheless, the progress of AZIBs is hindered by significant obstacles, such as the occurrence of anodic side reactions (SR) and the formation of zinc dendrites. Metal-organic framework (MOF)-based materials are being explored as promising alternatives owing to homogeneous porous structure and large specific surface areas. There has been a rare overview and discussion on strategies for protecting anodes using MOF-based materials. This review specifically aims to investigate cutting-edge strategies for the design of highly stable MOF-based anodes in AZIBs. Firstly, the mechanisms of dendrites and SR are summarized. Secondly, the recent advances in MOF-based anodic protection including those of pristine MOFs, MOF composites, and MOF derivatives are reviewed. Furthermore, the strategies involving MOF-based materials for zinc anode stabilization are presented, including the engineering of surface coatings, three-dimensional zinc structures, artificial solid electrolyte interfaces, separators, and electrolytes. Finally, the ongoing challenges and prospective directions for further enhancement of MOF-based anodic protection technologies in AZIBs are highlighted.

Carbonyl Chemistry for Advanced Electrochemical Energy Storage Systems.

On the basis of the sustainable concept, organic compounds and carbon materials both mainly composed of light C element have been regarded as powerful candidates for advanced electrochemical energy storage (EES) systems, due to theie merits of low cost, eco-friendliness, renewability, and structural versatility. It is investigated that the carbonyl functionality as the most common constituent part serves a crucial role, which manifests respective different mechanisms in the various aspects of EES systems. Notably, a systematical review about the concept and progress for carbonyl chemistry is beneficial for ensuring in-depth comprehending of carbonyl functionality. Hence, a comprehensive review about carbonyl chemistry has been summarized based on state-of-the-art developments. Moreover, the working principles and fundamental properties of the carbonyl unit have been discussed, which has been generalized in three aspects, including redox activity, the interaction effect, and compensation characteristic. Meanwhile, the pivotal characterization technologies have also been illustrated for purposefully studying the related structure, redox mechanism, and electrochemical performance to profitably understand the carbonyl chemistry. Finally, the current challenges and promising directions are concluded, aiming to afford significant guidance for the optimal utilization of carbonyl moiety and propel practicality in EES systems.

Increasing flexibility in vulnerable power grids using electrochemical storage.

Developing a reliable power grid and investing in non-conventional renewable energy resources pose problems for low- and medium-income countries. Frequently, maintaining a robust power grid infrastructure can present challenges in terms of reliability, resilience, and flexibility. This article presents a methodology for improving power flexibility in susceptible power systems through the utilization of Battery Energy Storage Systems (BESS). The methodology entails the examination of power stability, operating conditions, and security criteria in order to identify suitable locations for storage allocation. A study was conducted utilizing the Electrical Transient and Analysis Program (ETAP®) software to simulate the Central American power transmission grid. The results of the study indicate that including storage systems to offer virtual inertia and backup during emergency situations is a recommended strategy for mitigating potential challenges. The study suggests that applying specific criteria for allocation and sizing at critical points in sensitive systems can enhance power transfer flexibility, eliminating potential constraints. The Central American electrical Power System, which faces power transfer limitations, is well-suited for BESS. In severe contingencies, such as when the system frequency drops to 58.75 Hz and power transfer between Mexico and Central America exceeds 300 MW with voltage levels below 0.97 pu, BESS can help mitigate these issues. The solution involves deploying BESS both centrally and distributively. Results show decreased instability, with power increases not exceeding 300 MW for more than 11 study cycles in all scenarios. The approach includes a BESS with an installed capacity of 1,060 MWh/160 MW and a virtual inertia of H=6s.

Recent Progress on Rechargeable Zn-X (X=S, Se, Te, I2, Br2) Batteries.

Recently, aqueous Zn-X (X=S, Se, Te, I2, Br2) batteries (ZXBs) have attracted extensive attention in large-scale energy storage techniques due to their ultrahigh theoretical capacity and environmental friendliness. To date, despite tremendous research efforts, achieving high energy density in ZXBs remains challenging and requires a synergy of multiple factors including cathode materials, reaction mechanisms, electrodes and electrolytes. In this review, we comprehensively summarize the various reaction conversion mechanism of zinc-sulfur (Zn-S) batteries, zinc-selenium (Zn-Se) batteries, zinc-tellurium (Zn-Te) batteries, zinc-iodine (Zn-I2) batteries, and zinc-bromine (Zn-Br2) batteries, along with recent important progress in the design and electrolyte of advanced cathode (S, Se, Te, I2, Br2) materials. Additionally, we investigate the fundamental questions of ZXBs and highlight the correlation between electrolyte design and battery performance. This review will stimulate an in-deep understanding of ZXBs and guide the design of conversion batteries.

EnergyShare AI: Transforming P2P energy trading through advanced deep learning.

Peer-to-peer (P2P) energy trading is an innovative concept poised to transform energy demand management and utilization. EnergyShare AI is a powerful peer-to-peer energy exchange system that operates on a P2P model that integrates advanced machine learning with distributed energy sharing. This paper presents EnergyShare AI, a technology that connects consumers and prosumers through solar arrays, energy storage systems (ESS), and electric vehicles (EVs). Using Deep Reinforcement Learning (DRL) algorithms, Energy Share AI significantly improves energy management efficiency and substantially reduces costs. Our approach offers several advantages over traditional linear integer programming models, particularly in optimizing bidirectional energy transfer involving EVs and highlighting the critical role of ESS and photovoltaic (PV) systems in facilitating efficient P2P energy trading. Our research results show that successful P2P exchange can lead to significant cost savings and improved sustainability, thereby increasing the amount of energy transferred between different household profiles and stages of human development.

Multi-objective evolutionary method for multi-area dynamic emission/economic dispatch considering energy storage and renewable energy units.

Reducing thermal unit operating costs and emissions is the goal of the multi-objective issue known as multi-area economic/emission dispatch (MAEED) in smart grids. Using renewable energy (RE) have significantly lowered greenhouse gas emissions and ensured the sustainability of the environment. With regard to constraints such as prohibited operating zones (POZs), valve point effect (VPE), transmission losses in the network, ramp restrictions, tie-line capacity, this study aims to minimize operating costs and emission objectives by solving the multi-area dynamic economic/emission dispatch (MADEED) problem in the presence of RE units and energy storage (ES) systems. The conventional economic dispatch (ED) optimization approach has the following shortcomings: It is only designed to solve the single-objective optimization problem with a cost objective, in addition, it also does not have high calculation accuracy and speed. Therefore, to address this multi-objective MADEED problem with non-linear constraints, this paper introduces hybrid particle swarm optimization (PSO)-whale optimization algorithms (WOA). The reason for combining two algorithms is to use the advantages of both algorithms in solving the desired optimization problem. The introduced method is tested in two separate scenarios on a test network of 10 generators. Using the suggested hybrid methodology in this study, the MADED and MADEED problems are resolved and contrasted with other evolutionary techniques, such as original WOA, and PSO methods. Examining the results of the proposed method shows the efficiency and better performance of the proposed method compared to other methods. Finally, the results obtained by simulations indicate that integrating the necessary system restrictions gives the system legitimacy and produces dependable output. With regard to the results obtained from the introduced approach, the value of the overall cost function has clearly decreased by about 3 % compared to other methods.

Robust load-frequency control of islanded urban microgrid using 1PD-3DOF-PID controller including mobile EV energy storage.

Electricity generation in Islanded Urban Microgrids (IUMG) now relies heavily on a diverse range of Renewable Energy Sources (RES). However, the dependable utilization of these sources hinges upon efficient Electrical Energy Storage Systems (EESs). As the intermittent nature of RES output and the low inertia of IUMGs often lead to significant frequency fluctuations, the role of EESs becomes pivotal. While these storage systems effectively mitigate frequency deviations, their high costs and elevated power density requirements necessitate alternative strategies to balance power supply and demand. In recent years, substantial attention has turned towards harnessing Electric Vehicle (EV) batteries as Mobile EV Energy Storage (MEVES) units to counteract frequency variations in IUMGs. Integrating MEVES into the IUMG infrastructure introduces complexity and demands a robust control mechanism for optimal operation. Therefore, this paper introduces a robust, high-order degree of freedom cascade controller known as the 1PD-3DOF-PID (1 + Proportional + Derivative-Three Degrees Of Freedom Proportional-Integral-Derivative) controller for Load Frequency Control (LFC) in IUMGs integrated with MEVES. The controller's parameters are meticulously optimized using the Coati Optimization Algorithm (COA) which mimics coati behavior in nature, marking its debut in LFC of IUMG applications. Comparative evaluations against classical controllers and algorithms, such as 3DOF-PID, PID, Reptile Search Algorithm, and White Shark Optimizer, are conducted under diverse IUMG operating scenarios. The testbed comprises various renewable energy sources, including wind turbines, photovoltaics, Diesel Engine Generators (DEGs), Fuel Cells (FCs), and both Mobile and Fixed energy storage units. Managing power balance in this entirely renewable environment presents a formidable challenge, prompting an examination of the influence of MEVES, DEG, and FC as controllable units to mitigate active power imbalances. Metaheuristic algorithms in MATLAB-SIMULINK platforms are employed to identify the controller's gains across all case studies, ensuring the maintenance of IUMG system frequency within predefined limits. Simulation results convincingly establish the superiority of the proposed controller over other counterparts. Furthermore, the controller's robustness is rigorously tested under ± 25% variations in specific IUMG parameters, affirming its resilience. Statistical analyses reinforce the robust performance of the COA-based 1PD-3DOF-PID control method. This work highlights the potential of the COA Technique-optimized 1PD-3DOF-PID controller for IUMG control, marking its debut application in the LFC domain for IUMGs. This comprehensive study contributes valuable insights into enhancing the reliability and stability of Islanded Urban Microgrids while integrating Mobile EV Energy Storage, marking a significant advancement in the field of Load-Frequency Control.