Rechargeable Research Articles

Machine learning-assisted DFT-prediction of pristine and endohedral doped (O and Se) Ge12C12 and Si12C12 nanostructures as anode materials for lithium-ion batteries

Nanostructured materials have gained significant attention as anode material in rechargeable lithium-ion batteries due to their large surface-to-volume ratio and efficient lithium-ion intercalation. Herein, we systematically investigated the electronic and electrochemical performance of pristine and endohedral doped (O and Se) Ge12C12 and Si12C12 nanocages as a prospective negative electrode for lithium-ion batteries using high-level density functional theory at the DFT/B3LYP-GD3(BJ)/6-311 + G(d, p)/GEN/LanL2DZ level of theory. Key findings from frontier molecular orbital (FMO) and density of states (DOS) revealed that endohedral doping of the studied nanocages with O and Se tremendously enhances their electrical conductivity. Furthermore, the pristine Si12C12 nanocage brilliantly exhibited the highest Vcell (1.49 V) and theoretical capacity (668.42 mAh g− 1) among the investigated nanocages and, hence, the most suitable negative electrode material for lithium-ion batteries. Moreover, we utilized four machine learning regression algorithms, namely, Linear, Lasso, Ridge, and ElasticNet regression, to predict the Vcell of the nanocages obtained from DFT simulation, achieving R2 scores close to 1 (R2 = 0.99) and lower RMSE values (RMSE < 0.05). Among the regression algorithms, Lasso regression demonstrated the best performance in predicting the Vcell of the nanocages, owing to its L1 regularization technique.

Solar Wireless Electric Vehicle Charging System

This project outlines the design and implementation of a solar-powered electric vehicle charging station that addresses the dual challenges of high gasoline prices and harmful emissions. The number of countries adopting electric vehicles continues to rise, as they not only promote environmental sustainability but also significantly lower transportation costs by substituting expensive fuels with more affordable electricity. In this context, developing an electric vehicle charging infrastructure offers an innovative and effective solution. This system enables electric vehicles to charge while in motion, eliminating the need for stationary charging stops. Powered entirely by solar energy, it requires no additional power supply. The system incorporates solar panels, batteries, transformers, regulator circuits, copper coils, AC/DC converters, Atmega328P controllers, and LCD displays. This technology demonstrates the feasibility of an on-road solar-powered wireless charging system for electric vehicles.

Multi Utility Rover with Metal Detection

Landmines pose a major risk in the battlefield or during operation in remote areas. To reduce the risk of this threat, we have designed a multi-utility rover with metal detection and surveillance. This rover detects the landmine (made of metals) using the principle of electromagnetism and sends a message to a mobile device using ESP32 module. It conveys the level of risk using variable sounds. The rover has 4x4 remote controlled (operated over Wi-Fi) wheels which make it capable of moving in all the directions. It also has an ultra-sonic sensor (for obstacle detection) mounted in front of it to avoid collision with objects. This whole set-up is powered by a 3C 12V rechargeable battery

Hierarchical Optimal Dispatching of Electric Vehicles Based on Photovoltaic-Storage Charging Stations

Electric vehicles, known for their eco-friendliness and rechargeable–dischargeable capabilities, can serve as energy storage batteries to support the operation of the microgrid in certain scenarios. Therefore, photovoltaic-storage electric vehicle charging stations have emerged as an important solution to address the challenges posed by energy interconnection networks. However, electric vehicle charging loads exhibit notable randomness, potentially altering load characteristics during certain periods and posing challenges to the stable operation of microgrids. To address this challenge, this paper proposes a hierarchical optimal dispatching strategy based on photovoltaic-storage charging stations. The strategy utilizes a dynamic electricity pricing model and the adaptive particle swarm optimization algorithm to effectively manage electric vehicle charging loads. By decomposing the dispatching task into multiple layers, the strategy effectively solves the problems of the “curse of dimensionality” and slow convergence associated with large numbers of electric vehicles. Simulation results demonstrate that the strategy can effectively achieve peak shaving and valley filling, reducing the load variance of the microgrid by 24.93%, and significantly reduce electric vehicle charging costs and distribution network losses, with a reduction of 92.29% in electric vehicle charging costs and 32.28% in microgrid losses compared to unorganized charging. Additionally, this strategy can meet the travel demands of electric vehicle owners while providing convenient charging services.

Localized High-Concentration Electrolyte for All-Carbon Rechargeable Dual-Ion Batteries with Durable Interfacial Chemistry.

Lithium-based rechargeable dual-ion batteries (DIBs) based on graphite anode-cathode combinations have received much attention due to their high resource abundance and low cost. Currently, the practical realization of the batteries is hindered by easy oxidation of the electrolyte at the cathode interface, and solvent co-intercalation at the anode-electrolyte interface. Configuration of a "solvent-in-salt" electrolyte with a high concentration of Li salt is expected to stabilize the electrolyte chemistry versus both electrodes, yet inevitably reduces the mobility of the solvated working ions and increases the cost of the electrolyte. Herein, we propose to build a localized high-concentration electrolyte by adding hydrofluoroether as the diluent to reduce the salt content while improving the solvation structure, allowing more anions to enter the inner solvation sheath. The new electrolyte helps to form uniform and thin interfaces, with elevated contents of inorganic fluorides, on both electrodes, which effectively suppress electrolyte oxidation at the cathode and optimize electrolyte-electrode compatibility at the anode while facilitating charge transfer across the interface. Consequently, the DIBs with graphite as anode and cathode operate for 3000 cycles and retain a high-capacity retention of 95.7%, highlighting the importance of stable interfacial chemistry in boosting the electrochemical performance of DIBs.

An Arrhenius-Based Simulation Tool for Predicting Aging of Lithium Manganese Dioxide Primary Batteries in Implantable Medical Devices

This article presents a novel aging-coupled predictive thermo-electrical dynamic modeling tool tailored for primary lithium manganese dioxide (Li-MnO2) batteries in active implantable medical devices (AIMDs). The aging mechanisms of rechargeable lithium batteries are well documented using computationally intensive physics-based models, unsuitable for real-time onboard monitoring in AIMDs due to their high demands. There is a critical need for efficient, less demanding modeling tools for accurate battery health monitoring and end-of-life prediction as well as battery safety assessment in these devices. The presented model in this article simulates the battery terminal voltage, remaining capacity, temperature, and aging during active discharge, making it suitable for real-time health monitoring and end-of-life prediction. We incorporate a first-order dynamic for internal resistance growth, influenced by time, temperature, discharge depth, and load current. By adopting Arrhenius-type kinetics and polynomial relationships, this model effectively simulates the combined impact of these variables on battery aging under diverse operational conditions. The simulation handles both the continuous micro-ampere-level demands necessary for device housekeeping and periodic high-rate pulses needed for therapeutic functions, at a constant ambient temperature of 37 °C, mimicking human body conditions. Our findings reveal a gradual, nonlinear increase in internal resistance as the battery ages, rising by an order of magnitude over a period of 5 years. Sensitivity analysis shows that as the battery ages and load current increases, the terminal voltage becomes increasingly sensitive to internal resistance. Specifically, at defibrillation events, the ∂V∂R trajectory dramatically increases from 10−12 to 10−8, indicating a fourth-order-of-magnitude enhancement in sensitivity. A model verification against experimental data shows an R2 value of 0.9506, indicating a high level of accuracy in predicting the Li-MnO2 cell terminal voltage. This modeling tool offers a comprehensive framework for effectively monitoring and optimizing battery life in AIMDs, therefore enhancing patient safety.

Hierarchical Flower Array NiCoOOH@CoLa‐LDH Nanosheets for High‐Performance Supercapacitor and Alkaline Zn Battery

AbstractNickel oxyhydroxide based energy storage materials have been largely confined by insufficient exposure of active sites which results in low energy efficiency and poor stability. In order to resolve the problems, hierarchical flower array heterostructure NiCoOOH@CoLa‐LDH (denoted as NC@CL) nanosheets are designed with NiCo oxyhydroxide (NiCoOOH, denoted as NC) being tightly covered on CoLa layered double hydroxide (CoLa‐LDH, denoted as CL) nanosheet. This rational design creates more active sites, enlarges the electrode‐electrolyte contact area, improves electron conductivity, and prevents agglomeration during the cycling charge–discharge processes. Density functional theory calculations and differential charges concurrently illustrate that heterostructure formation optimizes the reaction kinetics and promotes electron redistribution. Benefiting from the heterogeneous structure and rich electro‐active sites caused by NC, NC@CL displays outstanding reversible specific capacitance (3228 F g−1 at 1 A g−1). The aqueous rechargeable alkaline Zn battery NC@CL//Zn exhibits a high capacity of 381.1 mA h g−1 at 0.5 A g−1 and cycling durability (98% capacity retention after cycling at 5 A g−1 for 2000 cycles). The excellent electrochemical performances indicate that NC@CL has great application potential as electrode material for aqueous energy storage device.

A Rechargeable Urea-Assisted Zn-Air Battery With High Energy Efficiency and Fast-Charging Enabled by Engineering High-Energy Interfacial Structures.

Electrochemical urea oxidation reaction (UOR) offers a promising alternative to the oxygen evolution reaction (OER) in clean energy conversion and storage systems. Nickel-based catalysts are regarded as highly promising electrocatalysts for the UOR. However, their effectiveness is significantly hindered by the unavoidable self-oxidation reaction of nickel species during UOR. To address this challenge, we proposed an interface chemistry modulation strategy to boost UOR kinetics by creating a high-energy interfacial heterostructure. This heterostructure incorporates Ag at the CoOOH@NiOOH heterojunction interface, where strong interactions significantly promote the electron exchanges at the heterojunction interface between -OH and -O groups. Consequently, the improved electron delocalization leads to the formation of stronger bonds between Co sites and urea CO(NH2)2, promoting a preference for urea to occupy Co active sites over OH*. The resulting catalyst, Ag-CoOOH@NiOOH, demonstrates ultrahigh UOR activity with a low potential of 1.33 V at 100 mA cm-2. The fabricated catalyst exhibits a mass activity over 11.9 times greater than the initial cobalt oxyhydroxide. The rechargeable urea-assisted zinc-air batteries (ZABs) achieve a record-breaking energy efficiency of 74.56 % at 1 mA cm-2, remarkable durability (1000 hours at a current density of 50 mA cm-2), and quick charge performances.

Microporous Polyethylene and Cellulose Composite Separators for Reversible Lithium Electrode in Lithium Rechargeable Batteries

AbstractThe lithium metal anode is the best candidate for high energy density batteries because of its high specific capacity and low negative potential. Rechargeable lithium metal batteries (RLMB) have not yet been commercialized. The key factors that limit the practical use of RLMB are the formation and growth of lithium dendrites during the lithium deposition process and the reaction of the lithium anode with the organic solvent of the electrolyte, quantified by the Columbic efficiency (CE). To suppress the lithium dendrite formation and to improve CE, many approaches such as the formation of a protective layer on the lithium electrode and the use of additives to the electrolyte have been proposed. In this study, the effect of a thin cellulose film to improve CE of lithium deposition and stripping on the lithium electrode was examined. The cycle performance of a Li/Li symmetrical cell with a cellulose and polyethylene composite separator was examined for a carbonate electrolyte and an ether electrolyte. The improvements of CE were observed for both electrolytes with the cellulose film separator. The improvement could be explained by the good wettability of the cellulose film separator with the electrolyte.

Mechanistic Understanding of Long Duration Fast Charge Aqueous Zinc Batteries Using Physically Adsorbed Oligomers as Interphases.

Polymers have been used as additives in the liquid electrolytes typically used for secondary batteries that utilize metals as anode. Such additives are conventionally argued to improve long-term anode performance by suppressing morphological and hydrodynamic instabilities thought to be responsible for out-of-plane and dendritic metal deposition during battery charging. More recent studies have reported that the polymer additives provide even more fundamental mechanisms for stabilizing metal electrodeposition through their ability to regulate metal electrodeposit crystallography and, thereby, morphology. Few studies explore how polymers carried in a liquid electrolyte achieve these functions, and fewer still provide rules for choosing among the various polymer types, the additive polymer molecular weight (Mw), and concentration in the electrolyte. Here, we investigate how these generally easy-to-control variables influence electrochemical interphase formation inside battery cells and their impact on the morphology and reversibility of Zn electrodes in aqueous electrolytes. We focus on aqueous Zn-iodine electrochemical cells containing linear polyethylene glycol (PEG) chains as additives and find that in electrolytes where the polymer concentration is maintained in the dilute solution regime there is an optimum polymer molecular weight (Mw ≈ 1000 Da), above which beneficial effects of polymers on Zn electrode reversibility and Zn-I2 battery lifetime are progressively lost. By means of optical ellipsometry and theoretical calculations, we show that the optimal Mw is associated with saturation of the thickness of a physiosorbed PEG coating on the Zn metal electrode. Electron microscopy and X-ray photoelectron spectroscopy analysis of Zn electrodeposits formed in such electrolytes reveal that the physiosorbed polymer coating has two primary effects─it regulates the deposit morphology and suppresses parasitic reactions between the electrode and electrolyte components. The parasitic reactions produce species like ZnO, which are known to passivate the Zn electrode and promote nonuniform deposition. Galvanostatic cycling measurements in aqueous Zn-I2 cells containing the PEG additives at the optimal Mw show that the cells maintain very high Coulombic efficiencies (≥99%) at current densities as high as 50 mA/cm2─close to the maximum values permissible across the Celgard separator membranes used in our studies.

Fluorine-Free Cycloaliphatic Epoxy-Based Siloxane Nanohybrid Binder with High Polar Hydroxyl Group Content Enabling LiFePO4-Type Battery with High Electrochemical Performance and Stability.

LiFePO4-type (LFP) batteries have attracted significant attention in most battery manufacturing industries due to their long lifespan, high-temperature safety, and low cost of raw materials. However, as an active material, LFP still suffers from several intrinsic drawbacks, including poor conductivity, a low Li+ diffusion coefficient, low capacity, and a lack of electrochemical stability, primarily due to conventional fluorine-based binders. Here, we report a simple yet effective approach to developing a fluorine-free binder based on a robust cycloaliphatic epoxy-based siloxane nanohybrid material (CES) to achieve high electrochemical stability in LFP batteries. The high content of silanol moieties in CES induces a strong affinity for the active material and conductive agent, significantly improving rheological (thixotropy) and mechanical (adhesion and cohesion) properties, which enable the formation of a uniformly coated electrode. As a result, we achieved superior electrochemical performance and stability in CES-applied electrodes compared to those with conventional fluorine-based binders. We investigate the reasons behind the contribution of CES to the electrochemical stability of LFP batteries through various analyses. The high thermal and oxidation stability of CES effectively prevents degradation of LFP-based active materials. Our binder development strategy offers a significant breakthrough in replacing conventional fluorine-based binders, advancing the development of high-performance and stable secondary batteries.

La1-xSrxF3-x: A Solid-State Electrolyte for Fluoride Ion Battery with High Ionic Conductivity and Wide Electrochemical Potential Window

Abstract Fluoride ion conductors are developed for use as solid-state electrolytes in fluoride ion batteries which are one of promising candidates for next-generation storage batteries. Ba-doped LaF3 (La0.9Ba0.1F2.9: LBF) is mainly used as a solid-state electrolyte in fluoride ion batteries. However, room temperature conductivity of LBF is considerably low, on the order of 10-6 S cm-1 and it is still unclear the optimal elements to be doped to LaF3. In this study, we have explored La0.9SrxBa0.1-xF2.9 system (x = 0, 0.01, 0.025, 0.05, 0.1), in which Ba in LBF is substituted for Sr and investigated the composition dependence of ionic conductivity. We elucidate that the higher concentration of Sr without Ba can significantly improve the ionic conductivity, and the maximum ionic conductivity of La0.9Sr0.1F2.9 is 1.5 × 10-5 S cm-1 at room temperature, which is one order of magnitude larger than that of LBF. The higher ionic conductivity of LSF is due to the larger grain size and higher sintering density of LSF compared to LBF, which results in lower grain boundary resistance. The LSF total ionic conductivity of 10-4 S cm-1 can be achieved at 350 K, which significantly lowers operating temperature of fluoride ion batteries down to 350 K.

Retraction Note: Genome-wide identification and characterization of TALE superfamily genes in cotton reveals their functions in regulating secondary cell wall biosynthesis

Retraction Note: Genome-wide identification and characterization of TALE superfamily genes in cotton reveals their functions in regulating secondary cell wall biosynthesis

Powering the circular future: Climate change and economic perspectives on second‐life batteries in the Belgian context

AbstractThis paper calculates the future levelized cost of storage (LCOS) and conducts a prospective life cycle assessment (PLCA) for second‐life batteries (SLB) in Flanders, Belgium. A cradle‐to‐grave approach is chosen for climate change (CC) and economic impacts of SLB. Impacts of processes related to the first and the second life are allocated according to the delivered electricity. Furthermore, impacts are determined according to their temporal occurrence. For LCOS, activities are time adjusted by discounting. For PLCA, new background databases are generated and changed based on the activities occurrence in time. Additionally, future CC impact of three Belgian energy paths is modeled, introducing user‐defined scenarios of PLCA. To conceptualize impacts, three use cases are defined: (a) residential, (b) industrial and (c) utility use case (UTI). The residential and industrial use cases (INDs) represent photovoltaic (PV) installations with battery storage, the UTI is a large‐scale battery participating in the Belgian secondary reserve market. Lowest LCOS of the SLB in 2050 are found in the IND, namely 39.66 €/MWh, and are below the benchmark batteries. CC impact of SLB in the residential is 58.7 /kWh and below the benchmark batteries. The CC impact of SLB is 75.2 and 78.5 /kWh in the industrial and UTI and thus higher than the benchmark batteries. Crucial for both assessments are increased dismantling and repurposing facility throughput, fair charging tariffs, the manufacturing, the charging electricity generated by PV installations, and power electronics. On the contrary, changing the background does not lead to major changes in CC.

Reviving Multivalent‐Metal Anodes in Simple Salt Electrolytes via Component Modifier Design

AbstractUsing combinatory electrolyte blends represents an imperative avenue to achieve good magnesium (Mg)‐metal anode compatibility and commercial feasibility in fields of promising rechargeable Mg batteries. However, fundamental challenges of how to manipulate component modifier reactivity on molecule level still remain to be solved. Here, molecular structure design concepts towards seeking bromophenyl complex‐based component modifiers has been proposed according to implications of electron‐donating and/or electron‐withdrawing substituents on Br−C bond dissociation reactivity. Exceptional Mg electro‐plating/stripping properties (a stable cycle life of 250 days in Mg//Cu asymmetric cells) have been firstly achieved in a simple salt electrolyte with 1‐(3‐bromophenyl)‐N,N‐dimethylmethanamine (BPDMA) as optimal component modifier. Comprehensive analyses disclose the unique electrochemically‐active Br‐containing ion‐pairs formation, such as [(Mg2+)2(TFSI−)Br−]2+ and [(Mg2+)2(TFSI−)(Br−)(G2)2]2+, which results in the much thinner Br− containing and organic–inorganic mixed interphases on Mg‐metal anodes. Furthermore, conventional MgSO4‐based electrolytes and even calcium (Ca)‐ion electrolytes can also be revived by similar strategy, demonstrating its generality and superiority.

Rigid Ligand Confined Synthesis of Carbon Supported Dimeric Fe Sites with High-Performance Oxygen Reduction Reaction Activity for Quasi-Solid-State Rechargeable Zn-Air Batteries.

Dimeric metal sites (DiMSs) in carbon-based single atom catalysts (SACs) offer distinct advantages in optimizing the adsorption energies of the catalytic intermediates and reaction pathways over single atom sites, which inspires the investigations on the rational design of DiMSs-based SACs and the accurate discernment of catalytic mechanisms. Here, dimeric Fe sites on carbon blacks (DiFe-N/CBs) are prepared using the precursor of metal-organic complex with a controlled structure, and the rigid ligand confinement secures the preservation of dimeric Fe sites during the thermal treatment. DiFe-N/CBs shows excellent electrocatalytic performance for oxygen reduction reaction (ORR) with a high half-wave potential of 0.917 V, and excellent durability with negligible activity decay. Theoretical studies reveal that the dimeric Fe sites have an optimal adsorption of OOH* with the Yeager-type binding, illustrating the advantages of DiMSs over SAs in catalyzing ORR. The rechargeable aqueous and quasi-solid-state Zn-air batteries assembled using DiFe-N/CBs-based air cathodes achieve small voltage gaps after long term charge/discharge test, showing great promises for practical applications. This synthetic strategy serves a novel platform to produce a scope of catalysts incorporating multimeric metal sites, and studies on the catalytic mechanism lay the foundation for establishing cooperative effect for multidentate adsorption reactions.

Regulating Electric Double Layer via Self‐Assembled Monolayer for Stable Solid/Electrolyte Interphase on Mg Metal Anode

Modulating the cationic solvation structure with high donor‐number (DN) additive is an effective strategy to construct a stable solid electrolyte interphase (SEI) on the Mg anode, which necessitates meticulous consideration of electrolyte chemistry and substantial quantities of additives. Notably, the electric double layer (EDL) adjacent to anode is pivotal role in SEI formation yet remains understudied. In this study, we propose a novel self‐assembled monolayer (SAM) strategy by utilizing (trifluoromethyl)trimethylsilane (TFTMS, only 2 vol%, 1.4 mol%, 0.135 mol L‐1), a low DN but strong Mg metal absorbability through electron‐withdrawing groups(−CF3), to modulate the complex structure of the Helmholtz absorption plane. Through dipole−dipole interaction between the electronegative fluorine (−CF3 of TFTMS) and electropositive hydrogen (−CH3/−CH2 of solvents), TFTMS weakens solvent−Mg2+ coordination and thus enhances anion−Mg2+ interaction, inducing a stable and dense SEI with superior electronic insulation to realize horizontal Mg plating/stripping. Consequently, the designed electrolytes enable the symmetric cells to cycle stable for up to 1000 hours and reversible Mg plating/stripping under 5 mA cm‐2, they show favorable compatibility with various cathodes. More importantly, the SAM strategy has good generality in other electrolyte systems, demonstrating a simple and effective route to promote the practical application of rechargeable magnesium battery.

An Adaptive Energy Orchestrator for Cyberphysical Systems Using Multiagent Reinforcement Learning

Reducing carbon emissions is a critical issue for the near future as climate change is an imminent reality. To reduce our carbon footprint, society must change its habits and behaviours to optimise energy consumption, and the current progress in embedded systems and artificial intelligence has the potential to make this easier. The smart building concept and intelligent energy management are key points to increase the use of renewable sources of energy as opposed to fossil fuels. In addition, cyber-physical systems (CPSs) provide an abstraction of the management of services that allows the integration of both virtual and physical systems in a seamless control architecture. In this paper, we propose to use multiagent reinforcement learning (MARL) to model the CPS services control plane in a smart house, with the purpose of minimising, by shifting or shutdown services, the use of non-renewable energy (fuel generator) by exploiting solar production and batteries. Furthermore, our proposal dynamically adapts its behaviour in real time according to current and historic energy production, thus being able to handle occasional changes in energy production due to meteorological phenomena or unexpected energy consumption. In order to evaluate our proposal, we have developed an open-source smart building energy simulator and deployed our use case. Finally, several simulations with different configurations are evaluated to verify the performance. The simulation results show that the reinforcement learning solution outperformed the priority-based and the heuristic-based solutions in both power consumption and adaptability in all configurations.

Hybrid sine cosine and spotted Hyena based chimp optimization for PI controller tuning in microgrids

In this paper, a novel hybrid sine-cosine and spotted Hyena-based chimp optimization algorithm (hybrid SSC) is adopted for the precise tuning of proportional-integral (PI) controllers in a microgrid system. The microgrid integrates multiple renewable energy sources, including photovoltaic (PV) panels, wind turbines, a fuel cell, and a battery storage system, all connected to a common DC bus. This DC bus interfaces with the main grid through a voltage source converter (VSC). The microgrid comprises a total of eight PI controllers distributed across various components: the boost converter in the wind system, the fuel cell system, the battery energy storage device, and the VSC controller. The hybrid SSC optimization algorithm effectively combines the exploration capabilities of the sine-cosine algorithm (SCA) with the exploitation strengths of the spotted Hyena optimizer (SHO) and Chimp optimization algorithm (ChOA), aiming to achieve optimal tuning of the PI controllers. This hybrid approach ensures an enhanced dynamic response and overall system performance by minimizing the integral of the time-weighted squared error (ITSE) for each controller. The simulation results, directed in a MATLAB/SIMULINK environment, demonstrate the efficacy of the hybrid SSC algorithm in improving the stability, response time and efficacy of the microgrid. The proposed technique significantly outperforms traditional tuning techniques, ensuring robust operation and seamless addition of renewable energy sources with the main grid. This study contributes to the advancement of intelligent control strategies for modern microgrids, emphasizing the importance of hybrid optimization algorithms in achieving optimal performance in complex energy systems.

Enhancing the Reliability of Weak-Grid-Tied Residential Communities Using Risk-Based Home Energy Management Systems under Market Price Uncertainty

This paper evaluates the reliability of smart home energy management systems (SHEMSs) in a residential community with an unreliable power grid and power shortages. Unlike the previous works, which mainly focused on cost analysis, this research assesses the reliability of SHEMSs for different backup power sources, including photovoltaic systems (PVs), battery storage systems (BSSs), electric vehicles (EVs), and diesel generators (DGs). The impact of these changes on the daily cost and the balance of energy source contribution in providing electrical energy to household loads, particularly during power outage hours, is also evaluated. To address the uncertainty of electricity market prices, a risk management approach based on conditional value at risk is applied. Additionally, the study highlights the impact of community size on energy costs and reliability. The proposed model is formulated as a mixed-integer nonlinear programming problem and is solved using GAMS. The effectiveness of the proposed risk-based optimization approach is demonstrated through comprehensive cost and reliability analysis. The results reveal that when electric vehicles are used as backup power sources, the energy index of reliability (EIR) is not affected by market price variations and shows significant improvement, reaching approximately 99.9% across all scenarios.