Intelligent Electronic Devices Research Articles

Toward Wireless Smart Grid Communications: An Evaluation of Protocol Latencies in an Open-Source 5G Testbed

Fifth-generation networks promise wide availability of wireless communication with inherent security features. The 5G standards also outline access for different applications requiring low latency, machine-to-machine communication, or mobile broadband. These networks can be advantageous to numerous applications that require widespread and diverse communications. One such application is found in smart grids. Smart grid networks, and Operational Technology (OT) networks in general, utilize a variety of communication protocols for low-latency control, data monitoring, and reporting at every level. Transitioning these network communications from wired Wide Area Networks (WANs) to wireless communication through 5G can provide additional benefits to their security and network configurability. However, introducing these wireless capabilities may also result in a degradation of network latency. In this paper, we propose utilizing 5G for smart grid communications, and we evaluate the latency impacts of encapsulating GOOSE, Modbus, and DNP3 for transmission over a 5G network. The OpenAirInterface open-source library is utilized to deploy an in-lab 5G Core Network and gNB for testing with off-the-shelf User Equipment (UE). This creates an effective 5G test platform for experimenting with different OT protocols such as GOOSE. The results are validated by measuring two different Intelligent Electronic Devices’ contact closure times for each network configuration. These tests are also conducted for varying packet sizes in order to isolate different sources of network latency. Our study outlines the latency impact of communication over 5G for time-critical and non-critical applications regarding their transition toward private 5G-based OT network implementations. The conducted experiments illustrate that in the case of GOOSE packets, simple encapsulation may exceed the protocol’s time-critical nature, and, therefore, additional measures must be taken to ensure a viable transition of GOOSE to 5G services. However, non-critical applications are shown to be viable for migration to 5G.

Oriented BN/BNNT heterostructure constructed by interface engineering strategy for polyamide-imide composite film with advanced flexibility and thermally conductive properties

Thermal conductive polymeric materials have aroused increasing attention as thermal management materials in the field of intelligent electronic devices due to their intriguing advantages. However, the discontinuity of phonon transmission path construction represents the bottleneck for thermal conductivity enhancement of composite materials, which limits the practical application of composite materials. Herein, flexible polyamide-imide (PAI) thermally conductive composite films with hierarchical structure composed of synergistically assembled functionalized boron nitride nanosheets (FBN) and polydopamine (PDA)-modified boron nitride nanotubes (FBT) by layer-by-layer assembly strategy are constructed. Benefitting from the optimized interface engineering with the ordered oriented arrangement FBN/FBT filler structure, the obtained composite film with optimized hybrid filler contents exhibits the super high thermal conductivity of 71.1 W·m−1·K−1, prominent thermal conductivity enhancement as high as 3663 % and excellent mechanical flexibility. The introduction of FBT can further expand the thermal contact area attributed to its inherent high thermal conductivity and aspect ratio. Additionally, the consecutive dual-channel phono transmission paths can be constructed in PAI composites under the synergistic action of FBN and FBT, further improving the phonon transmission density and suppressing phonon scattering, which endows PAI composite films with excellent thermal conductivity under low load of filler. The resulting multifunctionalities make the PAI composite films promising for flexible intelligent wearable electronic devices as thermal management materials.

A Network Intrusion Detection System with Broadband WO3–x/WO3–x‐Ag/WO3–x Optoelectronic Memristor

AbstractReal‐time intrusion detection system based on the von Neumann architecture struggle to balance low power consumption and high computing speed. In this work, a strategy for network intrusion detection system based on the WO3–x/WO3–x‐Ag/WO3–x structured optoelectronic memristor overcoming the aforementioned issues is proposed and demonstrated. Through the modulation of electrical signals, the memristor successfully simulates a series of important synaptic functionalities including short‐term/long‐term synaptic plasticity. Meanwhile, when subjected to light stimulus, it demonstrates remarkable synaptic behaviors in terms of long/short‐term memory and “learning‐forgetting‐relearning.” Based on this memristor array, a convolutional neural network is constructed to recognize abnormal network records within the KDDCup‐99 dataset accurately and efficiently. The power consumption (10–6 W) is over seven orders of magnitude lower than that of central processing unit, etc. Subsequently, an intrusion detection system is established to integrate collection, processing, and detection of real‐time network data, successfully classifying various types of network records. Hence, this work is expected to promote the development of high‐density storage and neuromorphic computing technology, and provides an application idea for intelligent electronic devices.

Interoperability Challenges in Multivendor IEC 61850 Devices for Parallel Power Transformer Differential Protection

Interoperability of GOOSE messages is essential for the proper operation of protection schemes such as the parallel power transformer (PTRF) differential protection scheme, especially when using multivendor IEC 61850 devices. GOOSE messages allow for fast and reliable communication between intelligent electronic devices (IEDs) and are based on Ethernet communication. To ensure the interoperability of GOOSE messages between multivendor devices, adherence to the IEC 61850 standard specifications is crucial. The standard defines the format and content of GOOSE messages, including the data object model, data types, and communication protocols. Third-party testing and certification programs can also ensure compliance with the standard and help guarantee interoperability between different vendors. Device conformance with these standards does not ensure interoperability when devices from various manufacturers are utilized. Interoperability is necessary between the relevant devices from various vendors to provide system power stability and protection. If multivendor device interoperability is achieved, power utilities will be able to utilize multivendor devices in substations. The study investigates and provides comprehensive methods for achieving IEC 61850 standard-based interoperability problems in parallel with PTRF’s current differential protection schemes between IEDs (SEL-487E and MiCOM-P645) produced by different vendors under fault conditions. In a lab-scale environment with RTDS for real-time simulation in Hardware-in-the-Loop (HIL), the designed technique is simulated and tested.

A new triboelectric nanogenerator based on a multi-material stacking structure achieves efficient power conversion from discrete mechanical movement.

Due to its invaluable potential in discrete mechanical energy collection, TENG (triboelectric nanogenerator) is considered to satisfy the power requirements of intelligent electronic devices and drive the development of the Internet of Things (IoT). Nowadays, the promotion of TENGs has been hindered due to the limitation of their output performance and service life. Herein, a brand new triboelectric nanogenerator based on a multi-material stacking structure is proposed. By stacking various triboelectric materials in a specific order, a special charge balance state could be achieved inside the system such that the conductive layer generates more induced charges, and the output performance is significantly enhanced. Besides, due to the usage of the electropositive elastomer PU (polyurethane sponge), the design also effectively alleviates abrasion on the contact surface and adjusts its own output according to different compression environments. The experimental results show that the stacked PTFE/FKM/PU TENG (PFP-TENG) presents a more than 50% increase in transferred charge and almost 5 times the current output compared with the general contact-separation type TENG. When connected to the application circuit, the maximum output power reached 10.2 W m-2 and 145.2 W m-3, and more than 1400 LEDs could be easily lit. Finally, the PFP-TENG was also used to collect mechanical energy from simple motion and realize considerable power generation. This study not only provides new ideas for the design of TENGs by reasoning the theoretical model but also presents improved output performance, thus exemplifying the strong potential of this design in developing a power-generation device that can collect discrete mechanical energy.

Implementation of a Trust-Based Framework for Substation Defense in the Smart Grid

The Smart Grid is a cyber-integrated power grid that manages electricity generation, transmission, and distribution to consumers and central to its functioning is the substation. However, integrating cyber-infrastructure into the substation has increased its attack surface. Notably, sophisticated attacks such as the PipeDream APT exploit multiple device protocols, such as Modbus, DNP3, and IEC61850. The substation’s constraints pose challenges for implementing security measures such as encryption and intrusion detection systems. To address this, we propose a comprehensive trust-based framework aimed at enhancing substation security. The framework comprises a trust model, a risk posture model, and a trust transferability model. The trust model detects protocol-based attacks on Intelligent Electronic Devices and SCADA HMI systems, while the risk posture model dynamically assesses the substation’s risk posture. The trust transferability model evaluates the feasibility of transferring and integrating a device and its trust capabilities into a different substation. The practical substation emulation involves a Docker-based testbed, employing a multi-agent architecture with a real-time Security Operations Center-influenced dashboard. Assessment involves testing against attacks guided by the MITRE ICS ATT&CK framework. Our framework displays resilience against diverse attacks, identifies malicious behavior, and rewards trustworthy devices.

Power System Fault Detection and Analysis Using Numerical Relay in Power grid Corporation Limited, Shoolagiri

The faults in a power system may be of various nature and they may affect the stability of the power system by causing outage of the line, there by overloading other connected lines and also causing cascading effect in the system. In order to access the nature of fault and analyze the impact of the same in a power system, fault analysis is required to be carried out as the same will be useful for the system operation and to take quick decisions in securing the system. In this paper we discuss the various types of faults in EHV system that may occur in line or substation. These faults are identified by Numerical relays which use IEDs [Intelligent Electronic Device]. The faults identified includes symmetrical and unsymmetrical faults in power system. Further in this project, we have taken into consideration the theoretical and practical study of the fault analysis through Numerical relays. In case of occurrence of Transient faults, Auto re-closure works with dead time of 1 sec. Current, voltage, Breaker status (open, close) are graphically represented by Disturbance Recorder. Events are recorded by Event logger. The above mentioned project for faults and analysis of faults in line or substation were carried out at Power grid Corporation Limited, 400 / 230kv Sub-Station Shoolagiri.

Automated fault location scheme for low voltage smart distribution systems

AbstractIntegrating the self‐healing capability realizes the automated protection of smart distribution systems. This article presents a fault location scheme for low voltage (LV) distribution systems based on the information collected from the smart meters. First, a fault condition is detected and classified by processing the current signal at the secondary side of the distribution transformer by an intelligent electronic device. Then, the faulty feeder and section are determined by calculating the fault‐imposed component of nodal voltages. The reliable performance of the proposed scheme is verified through several case studies using a real semi‐rural distribution system.

Fault Detection in a Single-Bus DC Microgrid Connected to EV/PV Systems and Hybrid Energy Storage Using the DMD-IF Method

Variations in fault currents, short times to clear the fault, and a lack of a natural current zero-crossing point are the most important challenges that DC microgrid protection faces. This challenge becomes more complicated with the presence of electric vehicles and energy storage systems due to their uncertainties. For this reason, in this paper, a new method for fault detection in DC microgrids with the presence of electric vehicles and energy storage systems is proposed. The new proposed method uses the combination of dynamic mode decomposition and instantaneous frequency for fault detection. In this method, first, a reference signal is made using the voltage and current signal sampled from the DC microgrid using the dynamic mode decomposition method. Next, in order to detect the fault, the instantaneous frequency value of the reference signal is calculated by the Hilbert transform. The simultaneous use of voltage and current signals reduces the transient effects of the control system on the proposed protection method. In order to measure voltage and current signals, only one intelligent electronic device unit is used in this paper. The proposed new method has been tested on a single-bus DC microgrid with the presence of electric vehicles and energy storage systems in MATLAB 2019b software. The results show that this method can detect all types of faults in DC microgrids, electric vehicles, and photovoltaics. Also, this method is immune to the uncertainties of the generation of distributed generation resources and the existence of noise distortions in the measured signals.

Predictive Fraud Detection: An Intelligent Method for Internet of Smart Grid Things Systems

Today, grid resilience as a feature has become non-negotiable, significantly when power interruptions can impact the economy. The widespread popularity of Intelligent Electronic Devices (IED) operating as smart meters enables an immense amount of fine-grained electricity consumption data to be collected. However, risk can still exist in the Smart Grid (SG), as valuable data are exchanged among SG systems; theft or alteration of this data could violate consumer privacy. The Internet of Things for Smart Grid (IoSGT) is a promising ecosystem of different technologies that coordinate with each other to pave the way for new SG applications and services. As a use case of IoSGT for future SG applications and services, fraud detection, ıNon-technical losses (NTL), emerges as an important application for Smart Grid (SG) scenarios. A substantial amount of electrical energy is lost throughout the distribution system, and these losses are divided into two types: technical and non-technical. Non-technical losses (NTL) are any electrical energy consumed and not invoiced. They may occur due to illegal connections, issues with energy meters such as delay in the installation or reading errors, contaminated, defective, or non-adapted measuring equipment, very low valid consumption estimates, faulty connections, and disregarded customers. Non-technical losses are the primary cause of revenue loss in the SG. According to a recent study, electrical utilities lose $89.3 Billion per year due to non-technical losses. This article proposes ensemble predictor-based time series classifiers for NTL detection. The proposed predictor ministers the user’s energy consumption as a data input for classification, from splitting the data to executing the classifier.It encompasses the temporal aspects of energy consumption data during preprocessing, training, testing, and validation stages. The suggested predictor is Time Series (TS) oriented, from data splitting to the classifier’s performance. Overall, our best results have been recorded in the fraud detection-based time series classifiers (TSC) model scoring an improvement in the empirical performance metrics by 10% or more over the other developed models.

Nanocone-shaped Ni-electroplated carbon fiber composite films for electromagnetic shielding applications

This study developed a series of lightweight composite films with adjustable reflectivity and superior mechanical properties. Carbon fiber (CF) was electroplated with both conventional and nanocone-shaped Ni coatings to create Ni-plated carbon fiber (CF@Ni), which was then further classified into conventional Ni carbon fiber (CF@CN) and nanocone-shaped Ni carbon fiber (CF@NN). CF@Ni fibers were sheared and filtered to produce Ni-plated carbon fiber fabric (CFF@Ni), which was then encapsulated in polyimide resin (PI) to form the final thin film materials (CF@Ni/PI). The shielding performance and mechanical properties of these CF@Ni/PI thin films have been comprehensively investigated. The study found that the nanocone-shaped Ni-plated samples exhibited superior performance. Absorption loss was dominant when a relatively low amount of Ni-plated carbon fiber was added, while reflection loss dominated when a relatively high amount was added. Adding 0.3 g of nanocone-shaped Ni carbon fiber created a 1.2 mm thin film with a shielding effectiveness of 71 dB and a tensile strength of 22.4 MPa. Additionally, the thin film demonstrated excellent flexibility and durability. Due to its exceptional mechanical properties and flexibility, this composite film holds significant potential in the fields of microelectronics and intelligent electronic devices.

ECS-Grid: Data-Oriented Real-Time Simulation Platform for Cyber-Physical Power Systems

ECS-Grid is the first data-oriented real-time electromagnetic transient simulation platform for cyber-physical power systems (CPPS). Traditional simulation tools are constrained by object-oriented programming (OOP) architecture, which is now a significant obstruction to creating a comprehensive cyber-physical simulation. Therefore, the proposed ECS-Grid platform follows a new data-oriented paradigm based on an Entity-Component-System (ECS) framework, which delivers higher flexibility, extensibility, scalability, and performance to support cyber-physical system research. ECS-Grid proposes a layer of virtual intelligent electronic devices (vIEDs) to model IEDs in CPPSs. The vIEDs directly talk to physical components and communicate asynchronously with cyber services via the proposed high-performance JSON-like binary protocol. Tests with the islanding and the man-in-the-middle cyber attack scenarios on a 711-node AC-DC microgrid cluster based on a modified CIGRE 15-Bus system are performed and give accurate results. A faster-than-real-time performance is achieved on the 10th Gen Intel <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> Core <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TM</sup> i7 computer, and real-time performance is achieved on distributed embedded NVIDIA <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> Jetson platform. The ECS-Grid design and test results demonstrate the potential of the ECS data-oriented paradigm and may inspire the renovation of industrial simulation software.

Portable self-charging power unit with integrated flexible supercapacitor and triboelectric nanogenerator

In recent years, with the rapid growth of intelligent electronic devices, there is a growing need for portable and sustainable energy sources. Self-charging power storage devices, owing to their green and environmentally friendly nature, simple structure, low cost, and maintenance-free characteristics, have emerged as the most promising solution. To this work, we perform an integrated self-charging motive power unit with silver nanowires (AgNW) doped silicon rubber based triboelectric nanogenerator (TENG) and carbon cloth (CC) based solid-state supercapacitor. The assembled NiMn-LDH@CC//PVA-KOH//Fe2O3@CC asymmetric supercapacitor (ASC), exhibits good capacity and stability as an energy storage component. In terms of the TENG, it effectively captures the energy from human body movements by single electrode structure, and demonstrates remarkable stability even during continuous operation for 2000 s. By integrating the self-charging energy storage device with the combined capabilities of the ASC and the TENG, this technology offers a one-stop solution for energy harvesting and storage. Therefore, this novel integrated self-charging power unit holds good promise to offer a practical and reliable power supply option for electronic systems.

A subsystem‐based fault location method in distribution grids by sparse measurement

AbstractWith the development of smart meters and other intelligent electronic devices, more and more data‐driven fault location methods based on wide area measurement are emerging. However, these diagnostic methods for dealing with the whole tested system often appear complex. This paper presents an innovative subsystems‐based fault location strategy in distribution grid by the sparsity promoted Bayesian learning algorithm. To avoid taking measurement for the whole distribution system, the fault‐included subsystem is selected according to the distribution characteristics of negative sequence voltage. Then the data for fault location is measured by allocating meters in subsystem, which can reduce the number of required meters. For accurately estimating the fault location, a sparse prior is proposed for the Bayesian learning, which could improve the accuracy of the fault location algorithm by about 4%. The performance is tested on a 12.66‐kV, 69‐bus distribution system in response to various fault scenarios. The results show that the accuracy of the proposed method for the fault section location can reach 90%. It also verifies the robustness and accuracy for fault line location, faced different fault types, fault resistance, noise, etc.

Mechanically robust and functional anisotropic conductive polymer composites with alternating microlayers

Anisotropic conductive polymer composites (ACPCs) are of great significance in electrical interconnection, miniaturized sensing devices and thermal management. The conductivity of ACPCs and conductivity ratio in different directions are the key to realize their applications. Actually, electrical properties are of significance, furthermore the mechanical properties of materials should attract more concern because conductive networks in ACPCs are commonly constructed by high volume of fillers with sacrificing mechanical properties of the final composites. Therefore, this study aims to improve significantly electrical properties of ACPCs while breaking limitation of the conductive fillers to damage the mechanical properties. In this work, ACPCs with alternative microlayers of biaxially oriented polypropylene (BOPP) and polypropylene (PP) filled carbon nanotubes (CNTs) are fabricated by low-temperature welding strategy. The electrical conductivity in X-direction reaches up to 10.1 S/m exhibiting a value 9.5 orders of magnitude higher than the value in Z-direction, while the products show super-high impact toughness of 12.3 kJ/m2 and tensile strength of 62.5 MPa, which is by far the most remarkable mechanical properties compared with the reported conductive PP-based composites. The integration of excellent electrical properties and high mechanical properties enables the materials to be applied to complex intelligent electronic device showing great applications value. Moreover, this ACPCs fabricating strategy is able to be scaled up due to simple, environmentally-friendly preparation process and low-cost raw materials, promoting ACPCs to be implemented in a variety of applications.

Multicolored microwave absorbers with dynamic frequency modulation

Microwave-absorbing materials are extensively used in intelligent electronic devices and stealth technologies where the ability to dynamically adjust microwave-absorbing capacity in response to specific requirements is vitally important. Herein, we report a new approach for constructing dynamically tunable microwave absorbers with ultrawide tunable frequency ranges that are simultaneously endowed with vibrant structural colors. The methodology produces structural colors and adjusts absorption properties by constructing ZnO coatings with precisely adjustable thicknesses on a polypyrrole/melamine foam (PPy/MF) surface by atomic layer deposition (ALD) in conjunction with a pressure-driven strategy that regulates the compression ratio. The electrical conductivity, electromagnetic parameters, thickness, and pore size of the ZnO-coated PPy/MF (ZnO/PPy/MF) are effectively adjusted, and simply applying external pressure widens the tunable frequency range and the effective absorption bandwidth. As a result, the effective absorption frequency of ZnO/PPy/MF is dynamically adjustable from the S band to the Ku band, thereby covering 94.3% of the entire microwave spectrum. Moreover, the brilliant and uniform structural colors of ZnO/PPy/MF, which span various color categories, are precisely regulated by tuning the thickness of the ZnO coating by adjusting the number of ALD cycles. ZnO/PPy/MF is strongly hydrophobic, which endows it with remarkable self-cleaning properties. Therefore, ZnO/PPy/MF provides a conceptually novel platform for the development of next-generation smart microwave-absorbing materials due to its integrated dynamic frequency-regulating ability, brilliant structural coloration, and self-cleaning features.

NN‐based method for regulating electrical impulse firing behavior of semiconductor low‐dimensional nanomaterials

AbstractIn the process of regulating the electrical pulse emission behavior of polyoxide‐semiconductor low‐vinamethylene material neural network (NN) by adsorption of oxidation/reduction molecules, the electrical pulse behavior in the NN is uncontrollable. In order to develop a new method to solve this problem, we analyze a regulatory method to study the emission behavior of electrical pulses by regulating the charge transfer of oxidation/reduction molecules between polymetalate semiconductors and low‐vinamethylene materials. In this paper, BP neural network is used to process and model the electrical pulse discharge behavior of semiconductor low‐vinamil materials. By establishing the neural network model, the precise control of the electrical pulse emission behavior is realized, and experiments are carried out. The experimental results in this paper show that after using the BP NN to calculate the regulation of the electrical pulse discharge behavior of low‐dimensional nanomaterials, it can be seen that the charge threshold am is 6 when no redox molecules are added. When NH3 is adsorbed, the charge threshold am is 13 according to the change ratio of the corresponding charge barrier height. Through the simulation results of pulse emission recorded by the NN, it can be seen that the amplitude and frequency of electric pulse in a molecular NN are reduced. This research provides new methodological and theoretical support for the development of novel neural networks and intelligent electronic devices based on semiconductor low‐dimensional nanomaterials.

Template-Free and Stretchable Conductive Fiber with a Built-In Helical Structure for Strain-Insensitive Signal Transmission.

With the rapid development of intelligent electronic devices, conductive fibers have become very critical to signal transmission devices. However, metal-based rigid conductive wires, such as high-modulus copper and silver wires, are prone to signal failure owing to tensile breakage under large strain conditions. Therefore, strain-insensitive stretchable conductive fibers for signal transmission are critical for next-generation wearable devices. Herein, a stretchable conductive fiber with a built-in helical structure is constructed by a "speed discrepancy" fiber-coating strategy with mass scalable production (60 cm/min). Such a "speed discrepancy" strategy is the key mechanism to template-free fabricate a built-in helical structure of the stretchable conductive fiber. The resultant fiber exhibits high conductivity (873 S/cm), stable insensitive signal transmission with a high quality factor (47.4), and a low relative resistance change (∼6%) under large strain. The built-in helical structure inspired by loofah whiskers endows the fiber with excellent strain insensitivity, and it can withstand large strains. On the proof of concept, our fiber can be seamlessly knitted, woven, and braided into smart textiles as an ideal signal transmission device under large strains, which will undoubtedly promote the development of intelligent electronic textiles and next-generation wearable devices.

Prioritizing protection communication in a 5G slice: Evaluating HTB traffic shaping and UL bitrate adaptation for enhanced reliability

Abstract5G network slicing is promising in prioritizing time‐critical protection communication in wireless networks of smart grids. However, network slicing offered by telecommunication providers encompasses all smart grid applications, lacking granularity. Smart grid automation standards provide recommendations on prioritization of protection communication to improve reliability but only for wired connections. Therefore, this paper investigates hierarchical token bucket (HTB) traffic shaping and uplink (UL) bitrate adaptation of a live video stream for prioritizing protection communication within a 5G slice. An experimental setup combines controller‐hardware‐in‐the‐loop (CHIL) with a quality of service (QoS) measurement system for validation. The system under test consists of commercial 5G networks, intelligent electronic devices (IEDs), and merging units for validation with three smart grid applications: fault location, line differential, and intertrip protection. HTB traffic shaping improves protected faults by 47.57% in congested and 1.16% in non‐congested scenarios. UL bitrate of the video stream adaptation by 2 Mbps increases protected faults by 3.69%. HTB traffic shaping even improves prioritization with a wired connection without introducing additional delays. HTB traffic shaping must be deployed in routers to maintain good QoS for critical applications. Collaboration between utilities and telecommunication providers is essential to effectively deploy 5G network slicing on smart grids.

The use of multi-agent systems in an automated restoration process for power distribution networks

The capacity of future smart grids to automatically detect problems, isolate them, and restore service is a key feature. Traditional mathematical programming techniques and heuristic approaches become computationally highly expensive when used for the restoration issue, which is a comprehensive nonlinear optimization challenge. Distributed control must offer comfortable and safe power system operation and improve consumer supply quality. In this article, we suggest the multi-agent system (MAS) as the creative process that applies to the existing power distribution network. The MAS agents are installed in "Intelligent electronic devices (IEDs)" and interact with one another using open protocols from the "Foundation for Intelligent Physical Agents (FIAP)." A Java-based distribution system simulator was built to test how well MAS works. In-lab experiments were conducted with the simulator connected to the MAS. The test findings demonstrated that the MAS effectively restored healthy divides by changing them to their original configuration following a predetermined sequence, notwithstanding the system's operating limits. The suggested MAS has shown the efficacy of a distributed control method that uses in the absence of the technologies currently employed in IEDs for control and protection.