Intelligent Electronic Devices Research Articles

시각 동기된 다중 양방향 TMDS 데이터 전송기능을 갖는 IED용 TSMB 버스 시스템의 구현 및 성능분석

In this paper, we propose a novel TSMB bus system with multiple bidirectional data transmission and time synchronization capability for IEDs(Intelligent Electronic Devices). Unlike the legacy unidirectional TMDS(Transition Minimized Differential Signaling) used for transfer digital video signals, the proposed bus system employs dual high-speed serial TMDS link for sending trigger signals from the FPGA of main processor module and receiving the sampled data from submodules such as either current or potential transformers. For simultaneous triggering multiple submdoules, we also employ the precision timing protocol processing capability in the main processor, which generates the wall clock pulse per second(PPS) synchronized to GPS. Adopting PLL for the PPS signal, we can provide the reference clock of 98.304MHz for supporting the data rate of 491.52 Mbps over each TMDS link. The data rate can support eight 24 bits ADCs for PTs or CTs in the single link, each of which requires 4800 samplings per second. An implemented TSMB bus system with FPGA consists of a single main processor with clock expander and eight submodules, in which each submodule is connected with the bidirectional TMDS link to the FPGA of main processor module. The jitter of 1 PPS between the two main processor modules was measured to be less than 102nsec at the maximum, and the jitter of the TSMB transmission data line was measured to be less than or equal to 660ps at the TP3 point of the receiving side, confirming that the TMDS specification was satisfied. Finally, the proposed time- synchronized multi-directional bus system can contribute to the improvement of the reliability and performance of the algorithm of the intelligent protection relay system through the optimal transmission of equivalent and simultaneous sampling data without the involvement of the processor.

Effect of SiO2 microstructure on ionic transport behavior of self-healing composite electrolytes for sodium metal batteries

Batteries matched with flexible intelligent electronic devices are required in the future to supply dense and reliable power security. In addition to energy storage performance, functionalized design of batteries with good mechanical properties and self-healing ability is critical to the development of flexible intelligent electronic devices. The polymer with quadruple hydrogen bonds can give materials the ability to repair mechanical damage and restore the original mechanical properties. The incorporation of inorganic fillers into polymer electrolytes can improve the electrochemical properties and stability of the electrolytes. Optimization of the geometry of inorganic materials could further improve the electrical conductivity of composite electrolytes. In this work, a flexible self-healing polymer electrolyte (Poly (ethylene glycol)-co-ureidopyrimidinone), PEG-UPy) was synthesized. Three different microstructures of SiO2 fillers (solid, mesoporous, and hollow mesoporous) with UPy modified were designed to improve the sodium ion transport performance of the PEG-UPy self-healing polymer electrolyte for sodium ion batteries. The PEG-UPy electrolyte filled with hollow mesoporous SiO2 (PEG-UPy@hSiO2) exhibits an excellent electrochemical performance due to its unique structure among the samples. The PEG-UPy@hSiO2 electrolyte shows the highest ionic conductivity, sodium ion transference number, and appropriate self-healing property. The discharge capacity of NVP/PEG-UPy@hSiO2-NaTFSI (HCPE)/Na cell could reach 110.5 mAh g−1 at 0.1C and the capacity retention rate could reach more than 77.6% after 200 cycles at 60 °C.

Highly compressible and thermal insulative conductive MXene/PEDOT:PSS@melamine foam for promising wearable piezoresistive sensor

With the rapid development of intelligent wearable electronic devices, highly compressible porous piezoresistive sensors are in imperative demand. However, the robustness of conductive coating that affects the stability and durability of porous piezoresistive sensors still needs to be solved urgently. In this work, a flexible conductive MXene/PEDOT:PSS@Melamine foam (MPMF) piezoresistive sensor was designed and prepared by simply dip-coating it in MXene and PEDOT:PSS mixed solution. Here, foam skeleton was first treated with PDA to improve its hydrophilicity and enhance the interfacial interaction with the functional groups of MXene nanosheets. More importantly, the usage of PEDOT:PSS can fix the MXene nanosheets tightly and construct synergistic conductive network between them, obtaining stable, robust, and highly conductive coating. Based on the contact effect between the adjacent conductive skeleton, the prepared MPMF sensor displays excellent piezoresistive sensing performances, which includes a wide working range (up to 80% compression strain, 60 kPa pressure), high sensitivity (0.30 kPa−1 in the pressure range of 12–60 kPa), and stable sensing pattern over 1000 compression cycles. All these merits make the sensor capable of detecting various human motions and pressure/location distribution of different items when assembled into an electronic skin. In addition, excellent thermal insulation property under different temperature conditions was also observed for MPMF due to the existence of special porous structures, providing necessary thermal protection when served as a wearable sensor. This research provides a convenient, simple, and cost-effective method for the manufacture of high-performance porous piezoresistive sensor.

One 3D aerogel wearable pressure sensor with ultrahigh sensitivity, wide working range, low detection limit for voice recognition and physiological signal monitoring

With the rapid development of intelligent electronic devices, there is a growing demand for wearable pressure sensors with ultrahigh sensitivity, a wide working range, and a low detection limit simultaneously. In this paper, we create a piezoresistive pressure sensor with an ultralight (29.5 mg cm−3) and elastic three-dimensional (3D) chitosan/MXene (CS/MXene) composite aerogel. Because of the strong electrostatic attraction between CS and MXene, CS/MXene aerogels with good mechanical properties can be obtained in a single freeze-drying step with no additional chemical treatment. Furthermore, the abundant amino and carboxyl groups in CS form hydrogen bonds with the −O and −F groups on the surface of MXene, significantly improving the mechanical strength of the composite aerogel. As a result, the CS/MXene composite aerogel sensor has a sensitivity of 709.38 kPa−1 in small pressure region (<1 kPa) and 252.37 kPa−1 in large pressure region (1–20 kPa), which are the highest values reported among the same type of aerogel sensors in the same pressure ranges. Furthermore, the sensor has a fast response time (120 ms), an ultralow detection limit of 1.4 Pa, and good stability (10,000 cycles with almost no fatigue). Because of the improved sensitivity, the competitive aerogel sensor can be used in a voice recognition system that can distinguish between different audio components. It also shows promise in detecting human and animal physiological signals ranging from low to high pressure and mapping spatial pressure distributions.

Data-driven topology detector for self-healing strategies in Active Distribution Networks

The integration of distributed energy resources requires the implementation of control and automation functionalities in distribution networks, which allow them to operate in a more flexible, efficient, and reliable way. The operation of these functionalities causes topological changes on the network that must be identified since these affect protection, volt/var control, and state estimation, among others. This paper presents a data-driven topology detector for self-healing strategies in Active Distribution Networks (ADN). This approach uses machine learning (ML) techniques to obtain a trained model as a topology detector. The ML models are integrated into the Intelligent Electronic Device (IED) of ADN so that using the voltage and current signals measured locally determine the network’s topology. A features selection and tuning technique based on a multiverse optimizer are proposed to improve the ML model accuracy. This approach allows it to be implemented in decentralized architectures since each IED detects the system’s topology from local measurements and does not depend on the availability of the communication system. The proposed topology detector was validated on a modified IEEE 123 nodes test feeder considering six topology changes, five DER outages, and five load variations. The results obtained show accuracy values above 96%, which evidences a highlighted potential for real-life applications.

Master-slave strategy based in artificial intelligence for the fault section estimation in active distribution networks and microgrids

Fault location plays an essential role in the integration of self-healing functionalities in active distribution networks and microgrids. However, the fault location methods formulation presents great challenges for these types of networks because the operating changes that occur them, such as changes in topology, DER connection/disconnection and microgrids operating modes. Several fault location solutions have been proposed; nevertheless, these are strongly dependent on robust communication systems. This paper presents an artificial intelligence-based master–slave strategy for the estimation of the fault section in active distribution networks and microgrids using dispersed measurements. The strategy is composed by two stages. The master stage uses a genetic algorithm that determines the location and number of devices which maximize the faulted location e performance. The slave stage uses artificial neural networks to predict the fault section by using local voltage and current measurements trough an intelligent electronic device (IED). This approach is useful because it neglects the need of a robust communication systems and synchronization process between measurements. Here, each IED estimates the faulted section and then sends it through the single communication system to the distribution system operator control center. The presented method is validated on the modified IEEE 34-nodes test feeder where the accuracy of the strategy was 95%. The results obtained and its easy implementation indicate potential for real-life applications.

Ultra-thin freestanding graphene films for efficient thermal insulation and electromagnetic interference shielding.

The preparation of freestanding graphene films by convenient and environmentally friendly preparation methods is still the focus of attention in various industrial fields. Here, we first select electrical conductivity, yield and defectivity as evaluation indicators and systematically explore the factors affecting the preparation of high-performance graphene by electrochemical exfoliation, then further post-process it under volume-limited conditions by microwave reduction. Finally, we obtained a self-supporting graphene film with an irregular interlayer structure but excellent performance. It is found that the electrolyte is ammonium sulfate, the concentration is 0.2 M, the voltage is 8 V, and the pH is 11, which were the optimal conditions for preparing low-oxidation graphene. The square resistance of the EG was 1.6 Ω sq-1, and the yield could be 65%. In addition, electrical conductivity and joule heat were significantly improved after microwave post-processing, especially its electromagnetic shielding performance with a shielding coefficient of 53 dB able to be achieved. At the same time, the thermal conductivity is as low as 0.05 W m-1 K-1. The mechanism for the improvement of electromagnetic shielding performance is that (1) microwave reduction effectively enhances the conductivity of the graphene sheet overlapping network; (2) the gas generated by the instantaneous high temperature causes a large number of void structures between the graphene layers, and the irregular interlayer stacking structure makes the reflective surface more disordered, thereby prolonging the reflection path of electromagnetic waves among layers. In summary, this simple and environmentally friendly preparation strategy has good practical application prospects for graphene film products in flexible wearables, intelligent electronic devices, and electromagnetic wave protection.

International Electrotechnical Commission 61850 Routable Generic Object-Oriented Substation Event Messages: A Secure Data-Centric Communication Approach

The necessity of critical communication between intelligent electronic devices (IEDs) in different substations led to expanding the Generic Object-Oriented Substation Event protocol (GOOSE) from the local area network (LAN) to the wide area network (WAN). International Electrotechnical Commission (IEC) 61850-90-5 has extended GOOSE messages as routable GOOSE (R-GOOSE) messages by adding network and transport layers. Therefore, the communication’s end-to-end latency and reliability against cyberattacks should be addressed.

High-performance asymmetric electrode structured light-stimulated synaptic transistor for artificial neural networks.

Photonics neuromorphic computing shows great prospects due to the advantages of low latency, low power consumption and high bandwidth. Transistors with asymmetric electrode structures are receiving increasing attention due to their low power consumption, high optical response, and simple preparation technology. However, intelligent optical synapses constructed by asymmetric electrodes are still lacking systematic research and mechanism analysis. Herein, we present an asymmetric electrode structure of the light-stimulated synaptic transistor (As-LSST) with a bulk heterojunction as the semiconductor layer. The As-LSST exhibits superior electrical properties, photosensitivity and multiple biological synaptic functions, including excitatory postsynaptic currents, paired-pulse facilitation, and long-term memory. Benefitting from the asymmetric electrode configuration, the devices can operate under a very low drain voltage of 1 × 10-7 V, and achieve an ultra-low energy consumption of 2.14 × 10-18 J per light stimulus event. Subsequently, As-LSST implemented the optical logic function and associative learning. Utilizing As-LSST, an artificial neural network (ANN) with ultra-high recognition rate (over 97.5%) of handwritten numbers was constructed. This work presents an easily-accessible concept for future neuromorphic computing and intelligent electronic devices.

Protection of the Future Harbor Area AC Microgrids Containing Renewable Energy Sources and Batteries

A significant share of global carbon emissions is related to marine vessels running solely on fossil fuels. The hybrid or fully electrified marine vessels using battery energy storage systems (BESS) both for onboard propulsion system and for cold-ironing during docking at harbor areas will significantly reduce marine related carbon emissions. However, the transformation of marine vessels’ operations from diesel engines to BESS will necessarily require charging stations and other electric power infrastructure at harbor areas. The sustainable and cheap energy of renewable energy sources like wind turbine generators (WTGs), photovoltaic (PV) systems and related BESS could be used at harbor areas for charging depleted vessel-BESS and supplying power to cold-ironing loads. For this purpose, two new harbor area smart grid or AC microgrid models have been developed by our research group. This paper presents a comprehensive analysis of three-phase short-circuit faults for one of the proposed AC microgrid models using PSCAD/EMTDC simulations. The fault study of harbor area AC microgrid-1 is done for both grid-connected and islanded modes. The main purpose of the fault study is to check if grid-connected mode overcurrent settings of intelligent electronic devices (IEDs) will also be valid for different islanded mode fault cases with different fault current contributions from converter-based distributed energy resources (DERs) including WTG, PV and BESS. The extent of fault current contribution from DERs and BESS to avoid adaptive protection settings and to ensure definite-time protection coordination and fast fuse operations during different islanded modes is investigated.

The Flipped Classroom Approach via the M-Learning Model: Impact on Student Learning and Motivation

Over the past decade, there has been a growing emphasis on integrating modern technology into educational systems, particularly in the form of new information and communication technologies (NICT), including mobile technologies. Mobile learning (M-Learning) is an advanced form of e-learning that allows learners to access educational materials and knowledge sources through intelligent digital electronic devices in a flexible mobile environment. This study explores the impact of applying the flipped classroom pedagogical approach via the M-Learning model on learners' motivation. To investigate this, an experiment was conducted on a group of 86 learners in the Operating System and Local Area Network course, where M-Learning was adopted as the teaching model. The experimental group was compared with a control group, and the obtained results showed that the experimental group had a significant improvement in learning outcomes and remarkable motivation according to the ARCS model. The findings indicate that the experimental group demonstrated improved learning and remarkable motivation according to the ARCS model. This suggests that incorporating M-Learning into the flipped classroom approach can be an effective way to enhance learners' motivation and engagement in the learning process. Keywords : flipped classroom, m-learning, ARCS model, motivation. https://doi.org/10.55463/issn.1674-2974.50.4.18

Cyber Security in Power Systems Using Meta-Heuristic and Deep Learning Algorithms

Supervisory Control and Data Acquisition system linked to Intelligent Electronic Devices over a communication network keeps an eye on smart grids’ performance and safety. The lack of algorithms protecting the power system communication protocols makes them vulnerable to cyberattacks, which can result in a hacker introducing false data into the operational network. This can result in delayed attack detection, which might harm the infrastructure, cause financial loss, or even result in fatalities. Similarly, attackers may be able to feed the system with fake information to hoax the operator and the algorithm into making bad decisions at crucial moments. This paper attempts to identify and classify such cyber-attacks by using numerous deep learning algorithms and optimizing the data features with a metaheuristic algorithm. We proposed a Restricted Boltzmann Machine-based nature-inspired artificial root foraging optimization algorithm. Using a publicly available dataset produced in Mississippi State University’s Oak Ridge National Laboratory, simulations are run on the Jupiter Notebook. Traditional supervised machine learning algorithms like Artificial Neural Networks, Convolutional Neural Networks, and Support Vector Machines are measured with the proposed algorithm to demonstrate the effectiveness of the algorithms. Simulations show that the proposed algorithm produced superior results, with an accuracy of 97.8% for binary classification, 95.6% for three-class classification, and 94.3% for multi-class classification. Thereby outperforming its counterpart algorithms in terms of accuracy, precision, recall, and f1 score.

Directly Growing Graphdiyne Nanoarray Cathode to Integrate an Intelligent Solid Mg-Moisture Battery

A continuous humidity and solar-light dual responsive intelligent solid Mg-moisture battery (SMB) with a graphdiyne nanosheets array was fabricated. The integrated battery works based on a new concept of chemical bond conversion on the surface of the graphdiyne nanosheets array that is grown in situ on a 3D melamine sponge (GDY/MS). The unique structure, excellent catalytic, and semiconductor performance of GDY endows the GDY/MS with some outstanding characteristics on trapping and transferring water molecules, catalyzing HER, and utilizing solar energy, making the GDY/MS a new generation cathode for a high-performance intelligent SMB. The performance of the GDY/MS-based smart SMB (GSMB) can be continuously tuned by humidity and solar-light. The GSMB shows a significant positive correlation between open circuit potential (OCP) and humidity, while the natural band gap of GDY makes it further act as a photoelectrode to capture light and generate photoelectrons. The GSMB can be applied as a self-power humidity monitor with an ultrafast response time of <0.24 s, a recovery time of <0.16 s, and a sensitive (36,600%) respiratory sensing performance. This simple and efficient battery-made strategy represents the future development direction of self-power supply equipment, intelligent electronic devices, and intelligent battery integration.

Phonon transport in two-dimensional carbon-boron material and heterointerfaces

Developing semiconducting materials with suitable band gap has attracted increasing attention for next-generation intelligent electronic devices. Recently, the newly synthesized monolayer carbon boron (C3B) material exhibits outstanding electronic properties and processes with indirect bandgap, which is considered as the promising alternatives of graphene. The heat conduction capability plays a critical role in the performance of C3B-based electronic devices and thermocatalysis applications. Herein, the thermal conductivity of monolayer C3B and graphene, and interfacial phonon transport across heterointerface are systematically investigated utilizing non-equilibrium molecular dynamics simulation. Compared with graphene, the reduced thermal conductivity of C3B sheet mainly stems from the decreased phonon group velocity and phonon relaxation time when the periodical boron atoms are introduced in C3B sheet based on the lattice dynamics and spectral phonon transmission analysis. Meanwhile, the influences of temperature and strain on the thermal conductivity of C3B are also discussed. Moreover, the thermal transport across the graphene|C3B heterointerface with different temperatures is analyzed. Interestingly, it is found that the larger interfacial thermal conductance of zigzag heterointerfaces mainly originates from the stronger phonon-phonon coupling between the out-of-plane vibrational modes of C3B and graphene. Our work would provide more insights for fundamental understanding the thermal transport properties of two-dimensional materials and be beneficial to the design of thermal management and thermoelectric materials.

Resilience enhancement of Islanded Microgrid by diversification, reconfiguration, and DER placement/sizing

Motivated by recent wide-scale deployment of Microgrids (MGs), this paper proposes an innovative framework for resilience enhancement of Islanded Microgrids (IMGs) against potential cyberattacks targeting IMG’s critical load curtailment. The proposed framework provides solutions for resilience enhancement in pre-attack (normal situation) and post-detection stages benefiting from three techniques, i.e., (i) ODPS: Optimal Distributed Energy Resources (DER) Placement and Sizing, (ii) OID: Optimal Intelligent Electronic Devices (IED) Diversification, and (iii) OPNR: Optimal Power Network Reconfiguration. The proposed approach improves all the phases of the resilience curve for an IMG, i.e., survive, sustain, and recovery. To improve the survive and sustain resilience phases, ODPS and OID techniques are used to optimally design the power and cyber configurations in pre-attack stage. In the operation phase, an OPNR technique is employed in both pre-attack and post-detection stages to effectively enhance the system resilience in survive and recovery phases. The effectiveness of the proposed approach is evaluated using IEEE 17- and 69-bus test systems operating as IMGs. The obtained results demonstrate significant improvements in the overall resilience of the underlying IMG.

Towards Software-Defined Protection, Automation, and Control in Power Systems: Concepts, State of the Art, and Future Challenges

Nowadays, power systems’ Protection, Automation, and Control (PAC) functionalities are often deployed in different constrained devices (Intelligent Electronic Devices) following a coupled hardware/software design. However, with the increase in distributed energy resources, more customized controllers will be required. These devices have high operational and deployment costs with long development, testing, and complex upgrade cycles. Addressing these challenges requires that a ’revolution’ in power system PAC design takes place. Decoupling from hardware-dependent implementations by virtualizing the functionalities facilitates the transition from a traditional power grid into a software-defined smart grid. This article presents a survey of recent literature on software-defined PAC for power systems, covering the concepts, main academic works, industrial proof of concepts, and the latest standardization efforts in this rising area. Finally, we summarize the expected future technical, industrial, and standardization challenges and open research problems. It was observed that software-defined PAC systems have a promising potential that can be leveraged for future PAC and smart grid developments. Moreover, standardizations in virtual IED software development and deployments, configuration tools, performance benchmarking, and compliance testing using a dynamic, agile approach assuring interoperability are critical enablers.

Large-Scale Distributed System and Design Methodology for Real-Time Cluster Services and Environments

The demand for a large-scale distributed system, such as a smart grid, which includes real-time interconnection, is rapidly increasing. To provide a seamless connected environment, real-time communication and optimal resource allocation of cluster microgrid platforms (CMPs) are essential. In this paper, we propose two techniques for real-time interconnection and optimal resource allocation for a large-scale distributed system. In particular, to configure a CMP, we analyze the data transfer rate and utilization rate from the intelligent electronic device (IED), collecting the power production data to the individual controller. The details provided in this paper are used to design a sample value, i.e., raw data transfer, on the basis of the IEC 61850 protocol for mapping. The choice of sampled values is to attain the critical time requirement, data transmission of current transformers, voltage transformers, and protective relaying of less than 1 s without complicating the real-time implementation. Furthermore, in this paper, a way to determine the optimal number of physical resources (i.e., CPU, memory, and network) for a given system is discussed. CPU ranged from 0.9 to 0.98 while each cluster increased from 10 to 1000. With the same condition, memory utilized almost 100% utilization from 0.98 to 1. Lastly, the network utilization rate was 0.96 and peaked at 1 at most. Based on the results, we confirm that a large-scale distributed system can provide a seamless monitoring service to distribute messages for each IED, and this can provide a configuration for CMP without exceeding 100% utilization.

Review of Methods for Addressing Challenging Issues in the Operation of Protection Devices in Microgrids with Voltages of up to 1 kV That Integrates Distributed Energy Resources

With the large-scale integration of distributed energy resources (DER) into passive distribution networks with voltages of up to 1 kV, these networks are being converted into microgrids. When the topology and operating conditions change, several challenging issues arise related to the functioning of the protection devices (PD) that are in operation. Most DERs, including renewable generators, are integrated into microgrids by means of inverters. In the event of short circuits (SC) in microgrids, these DERs provide a fault current contribution of no more than 1.2–2.0 Irated at the fault location. This makes it difficult to identify the fault location and to carry out the selective disconnection of the faulty element by means of conventional PDs. This article provides an overview of engineering solutions for improving conventional protection schemes that have been historically used in passive distribution networks, as well as for creating modern protection schemes based on innovative principles and new methods. The use of adaptive protections built on decentralized and centralized principles in most cases ensures the reliable protection of microgrids. Modern intelligent electronic devices (IEDs), where protection functions are implemented, rank higher with respect to their technical perfection in terms of reliability, sensitivity, selectivity, and speed performance. The use of multi-agent systems in the implementation of modern protection schemes requires the availability of broadband communication channels, which hinders their use because of the high cost. The combined use of fault current limiters (FCL) and energy storage systems (ESS) allows for the reliable operation of microgrid protections. The use of modern PDs ensures the reliable operation of DERs and power supply to consumers in microgrids, both in the case of grid-connected and islanded operation modes. Since there is no unified concept of designing protection schemes for microgrids with DERs, the choice of specific approaches to the design of protection schemes should be based on the results of a comparative technical and economic analysis of different options.

Heterogeneous Structural Color Conductive Photonic Organohydrogel Fibers with Alternating Single and Dual Networks.

Intelligent interactive electronic devices can dynamically respond to and visualize various stimuli, promoting the rapid development of flexible electronics. In this paper, an alternating single- and dual-network design strategy was developed for ingeniously constructing an interactive electronic fiber sensor with heterogeneous structural color (HSCEF sensor). The resulting sensor can rapidly output the synchronous electrical and optical dual signals under strain by adjusting the transport distance of conductive ions and the lattice spacing of the photonic crystal (∼200 ms). Meanwhile, the addition of low-freezing-point glycerol endowed the HSCEF sensor with excellent low-temperature tolerance (-25 °C) and cyclic stability. Notably, benefiting from the alternating single- and dual-network structure, the HSCEF sensor exhibits attractive heterogeneous structural color, which achieves colorimetric changes in the full visible light region with high mechanochromic sensitivity (2.25 nm %-1) and large wavelength shift (Δλ ∼ 225 nm). An intelligent wearable interactive sensor is finally used for real-time dynamic detection of joint movements, realizing precise resolution of different amplitudes. This work provides a general strategy to transform conventional photonic gels into heterogeneous structural color ones, and the developed new interactive sensor with rich optical information could be further used for visual health and exercise monitoring, intelligent soft robotics, wearable sensors, etc.

Recent progress in the development of smart supercapacitors

AbstractRecently, with the continuous development of human society and the continuous innovation of technologies, the intelligence era has arrived. Various intelligent electronic devices continue to be developed, in which flexible wearable electronic devices are highly favored by people. To meet the requirements of the normal operation of intelligent devices, the key point lies in the development of new smart energy storage devices. Accordingly, smart supercapacitors have been widely focused on and studied by researchers recently with the introduction of intelligent functions, such as electrochromism, self‐healing, and shape memory, into supercapacitors to broaden their application fields and promote their smart development. This can meet not only people's energy needs but also people's diverse personality needs and make our life more convenient, fast, and more intelligent than ever. Therefore, it is very important to summarize related work on smart supercapacitors. Although researchers have performed much research on smart supercapacitors, there is still little literature summary on the related work of different smart supercapacitors. Accordingly, this paper mainly introduces the research progress on electrochromic, self‐healing, shape memory, and self‐charging smart supercapacitors in recent years and discusses the development prospects and challenges of smart supercapacitors.