Rechargeable Research Articles

Design and Reaction Mechanism of Rechargeable Lithium-Carbon Fluoride Battery.

Recharging primary batteries is of great importance for increasing the energy density of energy storage systems to power electric aircraft and beyond. Carbon fluoride (CFx) cathodes are characterized by high specific capacity and energy density (865 mAh g-1 and 2180 Wh kg-1, respectively). Preventing the crystallization of LiF with an intermediate and lowering the energy barrier from LiF to CFx is expected to render the Li/CFx battery reversible. In this study, taking the advantage of a high-voltage-stable all-fluorinated electrolyte containing the boron-based anion receptor tris(trimethylsilyl)borate (TMSB), a rechargeable Li/CFx battery was realized with a reversible capacity of 465.9 mAh g-1 and an energy density of 1183.9 Wh kg-1, approximately 53% of that in the first discharge. After the first discharge, the charge-discharge profile featured rechargeable characteristics. In situ X-ray diffraction, ex situ soft X-ray absorption spectroscopy, pair distribution function analysis, and other measurements confirmed the generation and decomposition of Li-F and C-F bonds during cycling. Density functional theory calculations and nuclear magnetic resonance spectroscopy confirmed that TMSB serves as an anion carrier through the generation of a [TMSB-F]- complex, facilitating the conversion reactions during cycling. This study demonstrated a facile and low-cost approach for realizing high-energy-density, reversible Li/CFx batteries.

Synthesizing LiFePO4 by phosphate & iron recovered from sludge-incinerated ash and Li extracted from concentrated brines

Phosphorus (P) recovered from sludge-incinerated ash (SIA) could be applied to synthesize highly added-value products (FePO4 and LiFePO4) with in situ Fe in SIA. Indeed, LiFePO4 is a future of rechargeable batteries, which makes lithium (Li) highly needed. Alternatively, Li could also be extracted from concentrated brines to face a potential crisis of Li depletion on lands. Based on H3PO4 and Fe3+ co-extracted from the acidic leachate of SIA by tributyl phosphate (TBP), FePO4 (31.2 wt% Fe, 17.6 wt% P and the molar ratio of Fe/P = 0.98) was easily formed only adjusting pH of the stripping solution to 1.6. Interestingly, the organic phase from the first-stage co-extraction process of Fe3+ and H3PO4 could be utilized for Li-extraction from salt-lake brine, based on the TBP-FeCl3-kerosene system, and a good performance (78.7%) of Li-extraction and separation factors (β) (186.0–217.4) were obtained. Furthermore, the compounds with Li-extraction are complex, possibly LiFeCl4∙2TBP, in which Li+ could be stripped to form Li2CO3 by 4.0 M HCl (with a stripping rate up to 83%). Besides, Li2CO3 could also be obtained from desalinated brine by adsorption with manganese oxide ion sieve (HMO) and desorption with HCl. In the two cases, almost pure Li2CO3 products were obtained, up to 99.7 and 99.5 wt% Li2CO3 respectively, after further purification and concentration. Finally, recovered FePO4 and extracted Li2CO3 were synthesized for producing LiFePO4 that had a similar electrochemical property (69.5 and 77.8 mAh/g of the initial discharge capacity) to those synthesized from commercial raw materials.

High Performance All‐Solid‐State Lithium Batteries: Interface Regulation Mechanism

AbstractAll‐solid‐state lithium batteries (ASSLBs) can overcome many problems in cathode and lithium anode, and it is a very promising safe secondary battery. However, unstable interface problems between electrolyte and electrode and within the electrolyte still restrict its commercial development. Herein, the interface problems are first revealed in ASSLBs and highlight the need to deeply explore the intrinsic failure mechanisms to solve these problems. Subsequently, the three failure mechanisms of ASSLBs: chemical, electrical, and electrochemical failure are broken down, and focus on the impact of the space charge layer problem on the cathode‐electrolyte interface. The effect of the anode physical contact problem on the anode‐electrolyte interface is discussed. Then, recent advances in ASSLBs, cathode and anode interface optimization strategies, and their corresponding electrochemical properties are discussed. Finally, the interface challenges faced by ASSLBs and feasible interface modification strategies are summarized, which provide references for subsequent studies and insights into the design of interface structures for the new generation of high‐performance ASSLBs.

The structure and interaction of polymers affects secondary cell wall banding patterns in Arabidopsis.

Xylem tracheary elements synthesize patterned secondary cell walls (SCWs) to reinforce against the negative pressure of water transport. VASCULAR-RELATED NAC-DOMAIN7 (VND7) induces differentiation, accompanied by cellulose, xylan, and lignin deposition into banded domains. To investigate the effect of polymer biosynthesis mutations on SCW patterning, we developed a method to induce tracheary element transdifferentiation of isolated protoplasts, by transient transformation with VND7. Our data showed that proper xylan elongation is necessary for distinct cellulose bands, cellulose-xylan interactions are essential for coincident polymer patterns, and cellulose deposition is needed to override the intracellular organization that yields unique xylan patterns. These data indicate that a properly assembled cell wall network acts as a scaffold to direct polymer deposition into distinctly banded domains. We describe the transdifferentiation of protoplasts into tracheary elements, providing an avenue to study patterned SCW biosynthesis in a tissue-free environment and in various mutant backgrounds.

Structurally optimized rosette-like microspheres carbon with Fe-Ni single atom sites for bifunctional oxygen electrocatalysis in Zinc-Air batteries

Developing a secure and effective bifunctional oxygen catalyst for the ORR and OER is still a significant obstacle in the design of rechargeable zinc-air batteries. Here, a hollow rose-shaped bifunctional electrocatalyst is synthesized with an sacrificial template strategy (FeNi-NC). X-ray absorption fine structure analysis reveals the FeNi-NC catalyst contains FeN4 and NiN4 active sites as well as FeNi3 alloy. This hollow, flower-like structure performs low density, large specific surface area, and high permeability. Its inner cavities not only provide additional triple-phase interfaces to accelerate the reduction and oxidation of O2, but also enhance the diffusion of reactants on the catalyst. By controlling the input of Fe and nickel metal salts, the dispersion of active sites can be effectively tuned. Owing to the large number of exposed active sites on the carbon nanosheets, the synthesized FeNi-NC catalysts exhibit high electrocatalytic activity in both ORR (E1/2 = 0.852 V) and OER (ηj=10 = 359 mV). The construction of rechargeable zinc-air batteries resulted in a high power density of 135.78 mW cm−2, a better specific capacitance of 726.9 Wh kgZn−1 and 210 h enduring durability. More importantly, density functional theory (DFT) calculations indicate that the electronic interactions between Fe/Ni and nitrogen-doped carbon matrices play a pivotal role in enhancing the electrocatalytic performance of functional groups. These interactions effectively disrupt the electronic neutrality of carbon atoms, thereby accelerating the kinetics of the reaction. This research provides a new method for the preparation of single atom catalysts with bifunctional activities.

Experimental validation of fuzzy logic controller based on voltage perturbation algorithm in battery storage photovoltaic system

Introduction. Solar photovoltaic (PV) has recently become very important especially in electrical power applications for countries with high luminosity because it is an effectively unlimited available energy resource. Depending on solar radiation and temperature, the PV generator has a non-linear characteristic with a maximum power point (MPP). The novelty is the efficiency improvement of a PV energy module, it is necessary to track the MPP of the PV array regardless of temperature or irradiation circumstances. Purpose. This paper presents the modeling and the digitally simulation under MATLAB/Simulink of a Fuzzy Logic Controller based on Voltage Perturbation Algorithm (FLC-VPA) applied to PV battery charging system, which consists of PV module, DC-DC boost converter, MPP tracking (MPPT) unit and battery storage. Methods. The DSP1104 is then used to experimentally implement this MPPT algorithm for real-time driving. The obtained results show the high precision of the proposed FLC-VPA MPPT around the optimal point compared to the conventional VPA under stable and changing meteorological conditions. Practical value. The experimental results approve the effectiveness and validity of the proposed total control system in the PV system. References 30, tables 3, figures 17.

Coordination Engineering of Fe-Centered Catalysts for Superior Li-S Battery Performance.

Iron-nitrogen functionalized graphene has emerged as a promising cathode host for rechargeable lithium-sulfur batteries (RLSBs) due to its affordability and enhanced battery performance. To optimize its catalytical efficiency, we propose a novel approach involving coordination engineering. Our investigation spans a plethora of catalysts with varied coordination environments, focusing on elements B, C, N and O. We revealed that Fe-C4 and Fe-B2C2-h are particularly effective for promoting Li2S oxidation, whereas Fe-N4 excels in catalyzing the sulfur reduction reaction (SRR). Importantly, our study identified specific descriptors - namely, the Integrated Crystal Orbital Hamilton Population (ICOHP) and the bond length between Fe and S in Li2S adsorbed state - as the most effective predictive descriptors for Li2S oxidation barriers. Meanwhile, Li2S adsorption energy emerges as a reliable descriptor for assessing the SRR barrier. These identified descriptors are expected to be instrumental in rapidly identifying promising cathode hosts across various metal-centered systems with diverse coordination environments. Our findings not only offer valuable insights into the role of coordination environment, but also present an effective path for rapidly identifying high performance catalysts for RLSBs, enabling the acceleration of advanced RLSBs development.

Co/CoSe heterojunction as bifunctional oxygen electrocatalysts for rechargeable Zinc–Air batteries

The construction of suitable heterostructures in materials can tune the Fermi energy levels and electron transport rates of materials to achieve attractive oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) properties. In this study, a catalyst anchored in nitrogen-doped carbon nanowires (NCNW) with a heterogeneous interface of Co and CoSe is constructed to realize high-performance ORR and OER bifunctional catalysis. These Co and CoSe heterostructure interfaces can optimize the adsorption of intermediates. The Co/CoSe@NCNW catalyst performs excellent ORR catalytic activity (E1/2 = 0.89 V), and good OER activity (potential at 10 mA/cm2, Ej = 10 = 1.55 V). More importantly, the material shows excellent performance in rechargeable zinc-air batteries (ZABs). The open-circuit voltages of 1.47 and 1.50 V and the peak power densities of 122.56 and 74.49 mW/cm2 in liquid and solid electrolytes, respectively, are superior to those of the ZABs prepared from noble metals. Consequently, the construction of heterogeneous structures can convincingly boost the commercialization of rechargeable ZABs, and be extended to other fields involving ORR and OER.

New Mn Electrochemistry for Rechargeable Aqueous Batteries: Promising Directions Based on Preliminary Results

Aqueous batteries with metal anodes exhibit robust anodic capacities, but their energy densities are low because of the limited potential stabilities of aqueous electrolyte solutions. Current metal options, such as Zn and Al, pose a dilemma: Zn lacks a sufficiently low redox potential, whereas Al tends to be strongly oxidized in aqueous environments. Our investigation introduces a novel rechargeable aqueous battery system based on Mn as the anode. We examine the effects of anions, electrolyte concentration, and diverse cathode chemistries. Notably, the ClO4‐based electrolyte solution exhibits improved deposition and dissolution efficiencies. Although stainless steel (SS 316 L) and Ni are stable current collectors for cathodes, they display limitations as anodes. However, using Ti as the anode resulted in increased Mn deposition and dissolution efficiencies. Moreover, we evaluate this system using various cathode materials, including Mn‐intercalation‐based inorganic (Ag0.33V2O5) and organic (perylenetetracarboxylic dianhydride) cathodes and an anion‐intercalation‐chemistry (coronene)‐based cathode. These configurations yield markedly higher output potentials compared to those of Zn metal batteries, highlighting the potential for an augmented energy density when using an Mn anode. This study outlines a systematic approach for use in optimizing metal anodes in Mn metal batteries, unlocking novel prospects for Mn‐based batteries with diverse cathode chemistries.

Ionic Covalent Organic Framework Solid-State Electrolytes.

Rechargeable secondary batteries, widely used in modern technology, are essential for mobile and consumer electronic devices and energy storage applications. Lithium (Li)-ion batteries are currently the most popular choice due to their decent energy density. However, the increasing demand for higher energy density has led to the development of Li metal batteries (LMBs). Despite their potential, the commonly used liquid electrolyte-based LMBs present serious safety concerns, such as dendrite growth and the risk of fire and explosion. To address these issues, using solid-state electrolytes in batteries has emerged as a promising solution. In this Perspective, recent advancements are discussed in ionic covalent organic framework (ICOFs)-based solid-state electrolytes, identify current challenges in the field, and propose future research directions. Highly crystalline ion conductors with polymeric versatility show promise as the next-generation solid-state electrolytes. Specifically, the use of anionic or cationic COFs is examined for Li-based batteries, highlight the high interfacial resistance caused by the intrinsic brittleness of crystalline ICOFs as the main limitation, and presents innovative ideas for developing all- and quasi-solid-state batteries using ICOF-based solid-state electrolytes. With these considerations and further developments, the potential for ICOFs is optimistic about enabling the realization of high-energy-density all-solid-state LMBs.

Forecasting battery degradation trajectory under domain shift with domain generalization

Rechargeable batteries play a pivotal role in the carbon-neutral green environment by electrifying transportation and mitigating the intermittency of renewable energies. Forecasting the degradation of batteries is crucial for the optimal usage of batteries, while predicting battery degradation is not trivial due to diverse working conditions and complex failure mechanisms. To address this challenge, we develop a deep learning model that treats differences in operating conditions as domain shifts and utilizes meta-learning-based and task-driven domain generalization techniques to attack the domain shifts. The model effectiveness is demonstrated on three datasets comprising 203 cells of various operating conditions and chemistries, with improvements in prediction accuracy ranging from 18.1% to 30.0% (23.8% on average). Moreover, the model has gained some generalization capability via learning the correlation between domain gaps in the model and the degradation modes behind various operating conditions. Collectively, our work not only showcases the promise of the high-reliability data-driven model for diverse conditions and chemistries by exploiting domain generalization, but also spotlights the potential interplay between artificial intelligence and domain knowledge.

Novel joint algorithm for state-of-charge estimation of rechargeable batteries based on the back propagation neural network combining ultrasonic inspection method

State of Charge (SoC) is an essential indicator for energy storage distribution in lithium-ion batteries, which prevents overcharge and over-discharge of the battery by integrating it into the Battery Management System. Common estimation approaches are Extended Kalman Filtering (EKF), Coulomb counting, open-circuit-voltage (OCV), and neural networks (NN). While these methods are able to estimate SoC more accurately, they lack real-time monitoring capability for internal and external battery damage such as air bubbles and foreign objects. This study is the first to propose a novel joint algorithm for real-time monitoring of battery SoC and health with high accuracy, integrating ultrasonic non-destructive testing (NDT). The proposed algorithm predicts the battery overcharge based on the ultrasonic signal and reveals structural changes in commercial batteries during charging/discharging. Experimental results demonstrate that ultrasonic inspection cannot only enhance the SoC estimation accuracy of the backpropagation (BP) neural network, but also detects damaged conditions of the battery.

An enhanced energy management system for coordinated energy storage and exchange in grid-connected photovoltaic-based community microgrids

This paper introduces an enhanced coordinated community energy management system (CEMS) for a community microgrid. It is designed to optimize residential energy consumption and facilitate energy sharing among smart homes. The proposed solution integrates constrained mixed-integer programming (CMIP) approach along with advanced optimization technique and cooperative game theory-based pricing mechanism to address critical challenges in existing energy management strategies, including load scheduling and efficient peer-to-peer energy trading. The CEMS approach is adopted for grid-connected community power systems that incorporate local energy sources such as photovoltaic and battery storage systems. This solution is implemented under a time-of-use dynamic pricing model for energy transfer from the main grid to the community peers, a modified mid-market pricing mechanism for the P2P energy exchange, and feed-in tariff for energy transfer from the community peers to the main grid. Besides, seagull optimization algorithm is applied to relax the CMIP problem to get the optimal rational solution of the scheduling problem which is subjected to a rounding process to obtain the best feasible solution. The obtained results indicate a substantial reduction in electricity costs, achieving daily savings of 72.21 % and reducing grid dependency by 41.95 %. Moreover, 82.2 % of the community's energy demand was met through locally generated resources with 18.39 % enhancement of the overall CMG self-consumption ratio comparing to the reference operating scenario. Ultimately, the study demonstrates the effectiveness of the management system in improving load profiles, maximizing the use of local renewable energy sources, and reducing electricity expenses, thereby providing a sustainable and economically viable model for future smart grids.

Research on the Configuration of a 100% Green Electricity Supplied Zero-Carbon Integrated Energy Station

In the context of rapid growth in renewable energy installations and increasingly severe consumption issues, this paper designs a 100% green electricity supplied zero-carbon integrated energy station. It aims to analyze its configuration focusing on the following three core features: zero carbon emissions, 100% green electricity supply, and a centralized–distributed system structure. It discusses equipment selection and provides models for configuring upstream green electricity resources, power generation, energy storage, transformer, and energy conversion. The study examines the synergy between lithium-ion battery storage and modular molten salt thermal storage, along with the virtual energy storage characteristics formed by thermal load inertia, supported by mathematical models. Based on the data from a green electricity system in an Eastern Chinese city and typical load profiles, the paper validates a specific configuration for a 100% green electricity supplied zero-carbon integrated energy station, confirming model accuracy and calculating the required scale of upstream green electricity resources. It proves that establishing an electro-thermal storage synergy system is crucial for addressing the significant fluctuations in renewable energy output. It also argues that leveraging thermal load inertia to create virtual storage can reduce the investment in energy storage system construction.

Co-Expression Network Analysis and Introgressive Gene Identification for Fiber Length and Strength Reveal Transcriptional Differences in 15 Cotton Chromosome Substitution Segment Lines and Their Upland and Sea Island Parents.

Fiber length (FL) and strength (FS) are the core indicators for evaluating cotton fiber quality. The corresponding stages of fiber elongation and secondary wall thickening are of great significance in determining FL and FS formation, respectively. QTL mapping and high-throughput sequencing technology have been applied to dissect the molecular mechanism of fiber development. In this study, 15 cotton chromosome segment substitution lines (CSSLs) with significant differences in FL and FS, together with their recurrent parental Gossypium hirsutum line CCRI45 and donor parent G. barbadense line Hai1, were chosen to conduct RNA-seq on developing fiber samples at 10 days post anthesis (DPA) and 20 DPA. Differentially expressed genes (DEGs) were obtained via pairwise comparisons among all 24 samples (each one with three biological repeats). A total of 969 DEGs related to FL-high, 1285 DEGs to FS-high, and 997 DEGs to FQ-high were identified. The functional enrichment analyses of them indicated that the GO terms of cell wall structure and ROS, carbohydrate, and phenylpropanoid metabolism were significantly enriched, while the GO terms of glucose and polysaccharide biosynthesis, and brassinosteroid and glycosylphosphatidylinositol metabolism could make great contributions to FL and FS formation, respectively. Weighted gene co-expressed network analyses (WGCNA) were separately conducted for analyzing FL and FS traits, and their corresponding hub DEGs were screened in significantly correlated expression modules, such as EXPA8, XTH, and HMA in the fiber elongation and WRKY, TDT, and RAC-like 2 during secondary wall thickening. An integrated analysis of these hub DEGs with previous QTL identification results successfully identified a total of 33 candidate introgressive DEGs with non-synonymous mutations between the Gh and Gb species. A common DEG encoding receptor-like protein kinase 1 was reported to likely participate in fiber secondary cell thickening regulation by brassionsteroid signaling. Such valuable information was conducive to enlightening the developing mechanism of cotton fiber and also provided an abundant gene pool for further molecular breeding.

Organometallic Polymer Constructed by Active Fe-C12N8 Centers for Boosting Sodium-ion Storage.

Organic-metal coordination materials with rich structural diversity are considered as promising electrode materials for rechargeable sodium-ion batteries. However, the electrochemical performance can be constrained by the limited number of active sites and structural instability under the discharge/charge process. Herein, organometallic polymer microspheres (Fe-PDA-220) with a unique d-π conjugated structure was designed and successfully constructed through a simple synchronous polymerization and coordination reactions. Polymerization of phenylenediamine was initiated by Fe3+ and Fe2+ ions generated synchronously during the polymerization integrated with poly-aminoquinone chains to form Fe-C12N8 active centers. Used as electrode materials for sodium-ion batteries, the distinctive Fe-C bond significantly boosts the structural stability, and the π-d conjugation system could facilitate electron transfer. A high reversible capacity of 345 mAh g-1 was delivered at 0.1 A g-1 and a capacity of 106 mAh g-1 was maintained even after discharged/charged at 1.0 A g-1 for 5000 cycles, outperforming most reported coordination materials. Spectroscopic and electronic analyses revealed that a two-electron reaction occurred per active unit, accompanied by the reversible redox evolution of the C=N groups and Fe ions during sodiation/desodiation. This work provides a promising and efficient strategy for boosting the electrochemical performance of organic electrode materials by the design of organometallic polymers.

Modulation of electron transfer behavior on Fe2P-Co2P/NPC oxygen electrocatalyst by lattice cation substitution engineering and charge transport network design for rechargeable Zn-air batteries

Crystal structure modulation engineering on the lattice scale and charge transport network design on the micro/nano scale work together to endow oxygen electrocatalysts with high reactivity to fully release the capacity of Zn-air batteries (ZABs) as the next-generation green energy storage devices. Metal phosphide-based oxygen reduction reaction (ORR)/oxygen evolution reaction (OER) electrocatalysts with tunable electronic structures, variable valence states, and moderate overpotentials are recognized as the most promising and ideal candidates for air cathodes. The cation substitution strategy overcomes the drawback that single metal phosphides with fewer active sites and high adsorption barriers are not sufficient to achieve satisfactory electrocatalytic performance. In this paper, the Fe2P-Co2P/NPC oxygen electrocatalyst employing lattice cation site substitution engineering and three-dimensional (3D) conductive network encapsulation strategies are constructed to successfully ensure fast electron transfer behavior and safe charge/discharge energy storage. Noteworthy, the presence of Schottky barriers at the interface of the two materials hinders the electron reflux, which promotes a unidirectional flow of electrons, and increases the electron condensation in the OER and ORR processes. Relying on these features, the Fe2P-Co2P/NPC-assembled liquid ZABs achieved power densities, specific capacities, and energy densities of 175.18 mW cm-2, 805.75 mAh gZn-1, and 958.84 Wh kg-1, respectively, and importantly good rate performances and stability were exhibited even under high-current-density operation. The corresponding flexible solid-state ZABs also possesses superior electrochemical activity and mechanical flexibility. This work paves the way for the construction of bifunctional oxygen electrocatalysts with high-speed electron transfer channels, thus advancing the development of wearable electronic devices.

Suppression of Zinc Dendrite Growth by Enhanced Polyacrylamide Gel Electrolytes in Zinc-ion Battery.

Aqueous zinc-ion batteries have become a promising energy storage battery due to high theoretical specific capacity, abundant zinc resources and low cost. However, zinc dendrite growth and hydrogen evolution reaction limit their application. This study aims to improve the cycling performance and stability of aqueous zinc-ion batteries by improving the gel electrolyte. Polyacrylamide (PAM) is selected as the base material of the gel electrolyte, which has good stability and safety, but the water retention capacity, Zn2+ migration number, and ionic conductivity of PAM are low, which affects the long-term stability of the battery. In response to these problems, we optimized PAM by chemical cross-linking method, and formed an enhanced PAM gel by adding disodium citrate dihydrate (SC). Experimental results show that the introduction of an appropriate amount of SC in the enhanced PAM gel electrolyte can significantly improve its electrochemical performance. The zinc-ion symmetric battery achieved a stable cycle of more than 2100 hours at a current density of 0.5 mA cm-2, which is mainly attributed to the inhibitory effect of the enhanced PAM gel on zinc dendrite growth and hydrogen evolution reaction. This study provides a new direction for the development and application of flexible zinc-ion batteries.

Supervision and performance optimization of rechargeable battery SoC based on lightweight neural network

A state-of-charge (SoC) monitoring scheme for rechargeable batteries that can predict and filter the voltage dip time period, effectively reduce abnormal fluctuations in SoC data, and improve battery SoC evaluation stability is proposed. This scheme, which is based on the Kalman filtering algorithm and a lightweight neural network, can be applied to evaluate battery SoCs for wearable and portable devices. This method outperforms the Gaussian naive Bayes (GNB) and the support vector machine (SVM) algorithms in terms of predicting voltage dip time periods, with an accuracy of 95.27 %. The experimental results show that the method can be implemented on real hardware systems and used for SoC evaluation of several kinds of rechargeable batteries, demonstrating the scheme's generality.

Evaluating alternative technologies to diesel generation in India using multi-criteria decision analysis

Diesel generators (DGs) are widely used in India by business and domestic consumers to provide resilience against unreliable power supplies, but have serious adverse environmental and health impacts. Low carbon alternatives to DGs are becoming more widely available and affordable, though technical and non-technical barriers remain to their widespread adoption. Targeted policy and financial interventions would help accelerate the deployment of these alternatives, where such interventions should be based on local needs. To this end, we use a Multi-Criteria Decision Analysis (MCDA) approach to identify appropriate technology alternatives for DGs in residential, industrial and agricultural applications in India. Within this study, the MCDA framework facilitates evidence-based decision-making through structured discussions with local stakeholders and for evaluating the most suitable option from a variety of available alternatives. Overall, our analysis concluded that a hybrid system combining solar PV and battery storage system are considered most suitable for residential, agricultural as well as industrial applications. This study sets out a pragmatic approach for decision makers considering how to minimise the adverse impacts of DGs while recognising the intricacies of requirements of different applications at a local level. Additionally, our approach showcases how co-creation of potential solutions, and ‘transparency’ in the process, can be accomplished in policy-making, which is critical for wider acceptance of interventions.