Aydin Zaboli | University of Michigan (original) (raw)

Journal Papers by Aydin Zaboli

Energies, 2024

Behind the meter (BTM) distributed energy resources (DERs), such as photovoltaic (PV) systems, ba... more Behind the meter (BTM) distributed energy resources (DERs), such as photovoltaic (PV) systems, battery energy storage systems (BESSs), and electric vehicle (EV) charging infrastructures, have experienced significant growth in residential locations. Accurate load forecasting is crucial for the efficient operation and management of these resources. This paper presents a comprehensive survey of the state-of-the-art technologies and models employed in the load forecasting process of BTM DERs in recent years. The review covers a wide range of models, from traditional approaches to machine learning (ML) algorithms, discussing their applicability. A rigorous validation process is essential to ensure the model’s precision and reliability. Cross-validation techniques can be utilized to reduce overfitting risks, while using multiple evaluation metrics offers a comprehensive assessment of the model’s predictive capabilities. Comparing the model’s predictions with real-world data helps identify areas for improvement and further refinement. Additionally, the U.S. Energy Information Administration (EIA) has recently announced its plan to collect electricity consumption data from identified U.S.-based crypto mining companies, which can exhibit abnormal energy consumption patterns due to rapid fluctuations. Hence, some real-world case studies have been presented that focus on irregular energy consumption patterns in residential buildings equipped with BTM DERs. These abnormal activities underscore the importance of implementing robust anomaly detection techniques to identify and address such deviations from typical energy usage profiles. Thus, our proposed framework, presented in residential buildings equipped with BTM DERs, considering smart meters (SMs). Finally, a thorough exploration of potential challenges and emerging models based on artificial intelligence (AI) and large language models (LLMs) is suggested as a promising approach.

IEEE Access, 2023

Autonomous vehicles face challenges in ensuring cyber-physical security due to their reliance on ... more Autonomous vehicles face challenges in ensuring cyber-physical security due to their reliance on image data from cameras processed by machine learning. These algorithms, however, are vulnerable to anomalies in the imagery, leading to decreased recognition accuracy and presenting security concerns. Current machine learning models struggle to predict unexpected vehicular situations, particularly with unpredictable objects and unexpected anomalies. To combat this, scholars are focusing on active inference, a method that can adapt models based on human cognition. This paper aims to incorporate active inference into autonomous vehicle systems. Multiple studies have delved into this approach, showing its potential to address security gaps in this field. Specifically, these frameworks have proven effective in handling unforeseen vehicular anomalies. INDEX TERMS Autonomous vehicles, cyber-physical security, active inference, context awareness, abnormal scenarios.

Sustainability, 2024

Natural disasters pose significant threats to power distribution systems, intensified by the incr... more Natural disasters pose significant threats to power distribution systems, intensified by the increasing impacts of climate changes. Resilience-enhancement strategies are crucial in mitigating the resulting social and economic damages. Hence, this review paper presents a comprehensive exploration of weather management strategies, augmented by recent advancements in machine learning algorithms, to show a sustainable resilience assessment. By addressing the unique challenges posed by diverse weather conditions, we propose flexible and intelligent solutions to navigate disaster complications effectively. This proposition emphasizes sustainable practices that not only address immediate disaster complications, but also prioritize long-term resilience and adaptability. Furthermore, the focus extends to mitigation strategies and microgrid technologies adapted to distribution systems. Through statistical analysis and mathematical formulations, we highlight the critical role of these advancements in mitigating severe weather conditions and ensuring the system reliability.

IEEE Access, 2023

Automated vehicles are a revolutionary step in mobility, providing a safe and convenient riding e... more Automated vehicles are a revolutionary step in mobility, providing a safe and convenient riding experience while keeping the human-driving task minimal to none. Therefore, these intelligent vehicles are equipped with sophisticated perception sensors (e.g., cameras and radars), high-performance computers, artificial intelligence (AI)-driven algorithms, and connectivity with other internet-of-things (IoT) devices. This makes autonomous vehicles (AVs) a special kind of cyber-physical system (CPS) that is moving at speed in highly interactive and dynamic environments (e.g., public roads). Thus, AV is a potential target for cyber attackers to weaponize, compromising safety and mobility on the road. The first step in addressing this problem is to have a robust threat modeling framework that can address the evolving cyber-physical threats, especially to AV applications. In this regard, two areas are studied in this paper: the common practice of threat modeling in automotive and the ISO/SAE 21434 standard, and sensors and machine learning (ML) algorithms for AV perception systems and potential cyber-physical attacks. A comparative threat analysis for an AV perception system with the ISO/SAE 21434 standard and a system-theoretic process analysis for security (STPA-Sec) approach is also demonstrated in this paper. Based on the analysis, this paper proposes a robust threat analysis and risk assessment framework with mathematical modeling to identify cyber-physical threats to AV perception systems that are critical for the driving behaviors and complex interactions of AVs in their operational design domain.

IEEE Access, 2023

Nowadays, modern technologies in power systems have been attracting more attention, and household... more Nowadays, modern technologies in power systems have been attracting more attention, and households can supply a portion of or all of their electricity based on on-site generation at their location. This can be challenging for utilities in terms of monitoring and recording the data because the households’ facilities can generate or consume the energy without passing it through a meter, increasing the complexity of a distribution network. The speed of transferring data to utilities is another important concern. There is a necessity to send the smart meter (SM) data of each house to a distribution management system (DMS) for more analysis in the shortest possible time. This paper presents a novel deep learning framework collaborating with sequence-to-sequence (seq2seq), long short-term memory (LSTM), and stacked autoencoders (SAEs) to forecast residential load profiles considering the photovoltaic (PV), battery energy storage system (BESS), and electric vehicle (EV) loads with more capability based on pre-defined patterns. Experimental results show that the proposed method achieves outstanding performance in the forecasting process of residential load profiles in comparison with other algorithms. Also, a smart distribution transformer can help utilities to receive the data instantly via wireless communication, which can reduce the transfer duration to every minute and make the prediction and monitoring more manageable considering the different combinations of distributed energy resources (DERs) in residential locations.

Energies, 2022

Power substations are the crucial nodes of an interconnected grid, serving as the points where po... more Power substations are the crucial nodes of an interconnected grid, serving as the points where power is transferred from the transmission/distribution grids to the loads. However, interconnected cyberphysical systems and communication-based operations at substations lead to many cybersecurity vulnerabilities. Therefore, more sophisticated cybersecurity vulnerability analyses and threat modeling are required during productization phases, and system hardening is mandatory for the commercialization of products. This paper shows the design and methods to test the cybersecurity of multicast messages for digital substations. The proposed vulnerability assessment methods are based on the semantics of IEC61850 Generic Object Oriented Substation Event (GOOSE) and Sampled Value (SV), and cybersecurity features from IEC62351-6. Different case scenarios for cyberattacks are considered to check the vulnerabilities of the device under test (DUT) based on the IEC62351-6 standard. In order to discover security vulnerabilities in a digital substation, the proposed cybersecurity tester will generate malicious packets that compromise the regular functionality. The results show that the proposed cybersecurity testing module is able to detect potential vulnerabilities in multicast messages and the authentication methods (e.g., message authentication code) of multicast communications. Both commercial and simulated devices are used for the case studies.

Computers & Industrial Engineering, 2022

In this paper, a mixed-integer linear formulation for optimization multi-stage power system is re... more In this paper, a mixed-integer linear formulation for optimization multi-stage power system is represented. In order to achieve the best results, all facilities should be considered simultaneously due to the interconnection between power network equipment. In this paper, power plant, HV and MV substations and Distributed Generation (DG) are regarded concurrently to create an integrated power system planning. Furthermore, a reliability index called Average Power Not Supplied (APNS) in load point is modelled. Stochastic programming in the Chance-Constrained approach is also utilized to overcome uncertain parameters containing demand in load points, nominal voltages and facility failure rates. The mathematical model is tested on a real life case study in four schemes containing with or without considering DG and in certain or uncertain environment. Using both DG and MV substation in schemes planning leads to the establishment of a parallel system to improve network reliability. Since each scheme has specific requirements, it’s mathematical formulation is discussed in detail. The proposed formulation determines the optimum system configuration, including feeder routing, siting and sizing for power plant, HV/MV substation and DG. The numerical results show that planning in uncertain environment has a higher cost in comparison with certain model, but the results are more close to real world operations. Based on the obtained results a planner can estimate the cost components in different environments. Also in uncertain schemes, the growth in confidence levels increases the grid total cost. Therefore, planners must create an appropriate balance between confidence level and system total cost. Numerical results suggest that using DGs leads to a decrease in the required substations, their power to service load points and APNS cost. Thus using DGs can be an economic alternative to decrease system total cost. The achieved results indicate that the proposed planning for designing a power network has a desirable performance in practice.

Engineering Science and Technology, an International Journal, 2019

Wind energy source has a complex control situation because of dependence of its torque and output... more Wind energy source has a complex control situation because of dependence of its torque and output power on wind speed and its fluctuations. Based on this, in order to improve its control condition and dynamic efficiency, when connecting to the microgrid, ultra-capacitor which has a fast charging and discharging speed is used. Furthermore, the maximum energy derived from wind turbine and ultra-capacitor by the microgrid is of high importance which must be considered besides decreasing output power fluctuations. In this paper, for increasing the harvested energy, the Wind Speed Forecasting (WSF) model is used. So, the control method is applied by using WSF. In the proposed method, the gained energy is more than the lost energy. In fact, we increased harvested energy using a predictive control method. The considered predictive control is applied to the induction generator rotational speed variations. The considered wind turbine model in this paper produces an active power of 50 kW and is a variable speed induction generator (VSIG) with an apparent power of 50 kVA. All of the simulations are performed in MATLAB/SIMULINK software.

IEEE Transactions on Vehicular Technology, 2017

In urban electric railway transit systems, rails are used to navigate trains, as well as to provi... more In urban electric railway transit systems, rails are used to navigate trains, as well as to provide the returning path of the train's electric current to the traction power substation (TPS). Due to electrical resistance of rails and the rail-to-ground conductivity, a part of the train's returning current to the TPS flows into the ground, which is called stray current, which causes different problems such as an increase of rail potential. In this regard, a model of an electric train with a TPS, running rail, and third rail is simulated in MATLAB/Simulink. In the simulated model, the amounts of stray currents in different soil types, with and without collection mats, are compared. Afterward, to calculate the amount of stray current in the presence of the stray current control method considering different soil types through finite-element (FE) method (FEM), a UIC54 rail with insulated fastening equipment is modeled in FEMM 4.2 and analyzed with 2-D FEM. Finally, a comparison of efficiency of stray current collection mats in different soil models for both simulation in MATLAB/Simulink and FEM is also presented. The obtained results verify the accuracy of the simulated and modeled system in real conditions of electric railways.

Turkish Journal Of Electrical Engineering & Computer Sciences, 2017

In this paper, a novel protection method based on time-time (TT) transform for thyristor-controll... more In this paper, a novel protection method based on time-time (TT) transform for thyristor-controlled series-compensated lines is presented. First, current signals at both sides of the sending and receiving ends are retrieved and processed through time-time domain transform (TT-transform), and a TT-matrix is produced. A proposed index is then compared with a defined threshold (THD) in order to determine fault occurrence and faulted phases. Within less than three cycles of the fault inception, a tripping signal can be sent that is acceptable for the speed of digital relays. After faulted phase selection, considering the TT-matrix of the faulted phases of both the sending and receiving ends, another index is introduced for estimation of the fault section. Simulation results show that this approach determines fault occurrence, faulted phase, and fault section under different fault conditions such as fault type, fault location, fault resistance, fault inception angle, source impedance, reverse power flow, different levels of compensation, and different locations of the compensator in the line. The test results in the presence of high noise (with SNR up to 15 dB) confirm the effectiveness of the proposed method. The results also indicate that the proposed method is more robust to fault resistance compared to previous studies.

AUT Journal of Electrical Engineering, 2017

Thyristor rectifiers are widely used in electric railways in order to control the speed. As a con... more Thyristor rectifiers are widely used in electric railways in order to control the speed. As a consequence of their usage in addition to substantial input lead current, an enormous amount of harmonics is injected into the grid. To avoid such harmonics as well as reactive power compensation, reactive power hybrid filters consisting of active and passive filters are utilized. Regarding different passive and active filters connection in a hybrid filter, various configurations of hybrid filters are possible. Each of these configurations has different functionality in harmonic elimination and reactive power compensation. Since electric railway has a non-linear and variable nature, a novel hybrid filter structure is designed that compensates reactive power and eliminates harmonics to attain desired harmonic level regarding the conventional allowable harmonics level standards. The designed filter model is simulated in MATLAB/SIMULINK and then applied to a harmonic model of an electric railway. Since electric railways are single phase loads, specific three-phase to two-phase transformers are required to feed the load. To attain such purpose, an adaptive transformer is utilized in this paper. The proposed model has properly overcome the deficiencies of active and passive filters as well as demonstrating an appropriate performance in the reduction of total harmonic distortion (THD).

Majlesi Journal of Energy Management, 2015

Electric trains inject a large amount of harmonics to the power network and consume high reactive... more Electric trains inject a large amount of harmonics to the power network and consume high reactive power which makes them one of the worst loads kinds to be used in the power systems. These loads have non-linear characteristics and cause harmonic distortion. Filtering is one of the common ways utilized to eliminate harmonics and compensate reactive power. Filters are categorized in three types: passive, active and hybrid. Both passive and active filters have their own deficiencies while hybrid filters benefit from advantages of both former filters while overcoming their deficiencies. In this paper, active, passive and hybrid filters are discussed and then a suitable hybrid structure is introduced. Thereupon a harmonic model of an intercity electric train is presented and application of the proposed hybrid filter structure to the train is simulated using MATLAB/SIMULINK. The obtained results demonstrate the effectiveness of utilization of such hybrid filter structure in elimination of harmonic components and reactive power compensation.

Conference Papers by Aydin Zaboli

2024 IEEE Transportation Electrification Conference and Expo (ITEC)

One of the primary motivations for autonomous vehicle (AV) technology is to reduce road accidents... more One of the primary motivations for autonomous vehicle (AV) technology is to reduce road accidents compared to human-driven cars. This necessitates having robust perception systems to detect and classify objects correctly in real-time environments. Various factors, including the complexity of the scene, the type of object, the capability of the perception sensors, and the performance of AI-based algorithms, can affect its robustness. Furthermore, vulnerabilities in these factors can be exploited as cyber-physical attacks. Hence, this paper presents a novel mathematical model for system-level risk evaluation of AV perception systems that incorporates the relevant objects for AV applications and the machine learning (ML) algorithms used to detect and classify them. This model is adapted from the ISO/SAE 21434 threat analysis and risk assessment (TARA) model with an enhancement in impact rating and attack feasibility assessment. Additionally, a case study for impact rating is demonstrated with real data from traffic crashes where the most important objects are impacted. Also, the effect of the robustness of the detection algorithm on attack feasibility assessment is illustrated with some AI/ML-based state-of-the-art detection algorithms used in AVs.

2024 IEEE Transportation Electrification Conference and Expo (ITEC), 2024

Autonomous vehicle, which must trust the judgment of the entire system without human participatio... more Autonomous vehicle, which must trust the judgment of the entire system without human participation, have many disadvantages. Traffic sign classification is one of those disadvantages and a challenge to overcome. Cybersecurity breaches or changes in the surrounding environment are critical obstacles to the traffic sign classification function. Therefore, this paper proposes an image reconstruction method based on mask autoencoder to improve classification performance. Additionally, classification accuracy is also improved by extracting characters from traffic signs. A case study proves that image classification accuracy improves even when various abnormalities are added to the input of traffic sign classification performance.

arXiv, 2024

Cybersecurity breaches targeting electrical substations constitute a significant threat to the in... more Cybersecurity breaches targeting electrical substations constitute a significant threat to the integrity of the power grid, necessitating comprehensive defense and mitigation strategies. Any anomaly in information and communication technology (ICT) should be detected for secure communications between devices in digital substations. This paper proposes large language models (LLMs), e.g., ChatGPT, for the cybersecurity of IEC 61850-based communications. Multi-cast messages such as generic object oriented system events (GOOSE) and sampled values (SV) are used for case studies. The proposed LLM-based cybersecurity framework includes, for the first time, data pre-processing of communication systems and human-in-the-loop (HITL) training (considering the cybersecurity guidelines recommended by humans). The results show a comparative analysis of detected anomaly data carried out based on the performance evaluation metrics for different LLMs. A hardware-in-the-loop (HIL) testbed is used to generate and extract dataset of IEC 61850 communications. Index Terms-Cybersecurity, generic object oriented system event (GOOSE), ChatGPT, human-in-the-loop (HITL), large language model (LLM), sampled value (SV), substations.

2023 IEEE Power & Energy Society General Meeting (PESGM), 2023

Due to recent advancements in the power industry, residential sites could provide part of or even... more Due to recent advancements in the power industry, residential sites could provide part of or even their entire energy using on-site generation. However, because their equipment might consume or generate energy without going through a meter, the data recording and monitoring could be challenging for electric utilities. A more complex distribution system is the result of this issue, and utilities cannot detect the events between 15-minute intervals, resulting in an inaccurate forecasting process. This paper presents a technique based on a two-layer long short-term memory (LSTM) framework to forecast the load profile of the residents regarding the different combinations of distributed energy resources (DERs). The data for training the model is considered every minute instead of conventional 15-minute intervals, so it can make a more accurate forecasting process and preserve households’ privacy better.

2023 IEEE Kansas Power and Energy Conference (KPEC), 2023

Considering all components in a power network brings some challenges due to the mathematical mode... more Considering all components in a power network brings some challenges due to the mathematical model’s complexity. In this paper, an integrated mathematical formulation aiming at power system cost minimization is suggested. A novel reliability index is introduced for improving system reliability to control average power not supplied (APNS) at load points. Furthermore, a chance-constrained technique is adjusted throughout planning to cope with uncertainty. The performance is evaluated based on some scenarios, and the findings are analyzed and compared. It can be seen that scenarios with uncertain parameters can strongly affect on system total costs. However, they are more reliable at showing the real world. Also, APNS costs and total system costs decrease in scenarios with DGs. Therefore, DGs can be suitable resources to cut down on total cost and improve system reliability.

The 9th Power Systems Protection and Control Conference (PSPC2015), 2015

In electric railways, thyristor rectifiers are used in order to control the speed. As a consequen... more In electric railways, thyristor rectifiers are used in order to control the speed. As a consequence in addition to substantial input lead current, an enormous amount of harmonics is injected into the grid. To avoid such harmonics as well as reactive power compensation, reactive power hybrid filters consisting of active and passive filters are utilized. Hybrid filters have several different structures. Since electric railway has a non-linear and variable nature, a novel hybrid filter structure is designed that compensates reactive power and eliminates harmonics to attain desired harmonic level regarding the conventional allowable harmonics level standards. The designed filter model is simulated in MATLAB/SIMULINK and then applied to a harmonic model of an electric railway.

4th International Conference on Recent Advances in Railway Engineering, 2015

In DC-electrified railway systems, rails are used to navigate trains as well as providing the ret... more In DC-electrified railway systems, rails are used to navigate trains as well as providing the returning path of train's electric current to the traction power substation (TPS). Due to electrical resistance of rails and the conductivity between rail and ground, a part of train returning current to the TPS permeate in the ground which causes different problems like increasing of rails potential that increase of rails potential leads to death hazards for the train station personnel and stray current increment causes metal's corrosion and decrease of their lifetime. Therefore, surveying electric railway system in order to know the unfavorable effects of rails potential and stray currents is an essential matter. In this paper, effect of control methods on stray current and rail potential amount and analysis of this current with Finite Element Method (FEM) is presented.

Energies, 2024

IEEE Access, 2023

Sustainability, 2024

IEEE Access, 2023

Energies, 2022

Computers & Industrial Engineering, 2022

Engineering Science and Technology, an International Journal, 2019

IEEE Transactions on Vehicular Technology, 2017

Turkish Journal Of Electrical Engineering & Computer Sciences, 2017

AUT Journal of Electrical Engineering, 2017

Majlesi Journal of Energy Management, 2015

2024 IEEE Transportation Electrification Conference and Expo (ITEC)

2024 IEEE Transportation Electrification Conference and Expo (ITEC), 2024

arXiv, 2024

2023 IEEE Power & Energy Society General Meeting (PESGM), 2023

2023 IEEE Kansas Power and Energy Conference (KPEC), 2023

The 9th Power Systems Protection and Control Conference (PSPC2015), 2015

4th International Conference on Recent Advances in Railway Engineering, 2015

2015 20th Conference on Electrical Power Distribution Networks Conference (EPDC), 2015

Nowadays power quality is one of the crucial issues in power systems. Among power quality issues,... more Nowadays power quality is one of the crucial issues in power systems. Among power quality issues, harmonics caused by nonlinear loads are of great importance as causing great problems in power systems such as malfunction of electrical devices, efficiency reduction as well as reduction of effective lifetime of electrical devices. Electric railways utilizing thyristor rectifiers in order to control speed consume enormous lead current and inject huge harmonic to the grid. In order to eliminate harmonic and compensate reactive power in electric railways, it is proper to use hybrid filters. Hybrid filters are a combination of active and passive filters. Regarding the way active and passive filters are connected in hybrid filters, they have different structures. In this paper, harmonic model of electric railway as well as some of the hybrid filters configurations are evaluated and their performance in electric railways are simulated in MATLAB/SIMULINK. Finally, performances of different configurations are compared to demonstrate their advantages and disadvantages in reducing current total harmonic distortion (THD).

Microgrid, 2024

This chapter explores the feasibility and cost-benefit analysis of large-scale integrated photovo... more This chapter explores the feasibility and cost-benefit analysis of large-scale integrated photovoltaic-battery energy storage system (PV-BESS) installations or upgrading/building a distribution substation for substation overload reduction. PV systems generate electricity from sunlight using solar panels, while BESS stores excess energy for later use. Combining these technologies creates a PV-BESS installation, allowing for improved energy management and increased self-consumption of solar energy. Also, the high penetration of new electric vehicle (EV) chargers is another reason for substation overload. These chargers provide the necessary electrical energy to recharge the battery packs of electric cars, motorcycles, buses, and other EVs. The chargers draw a significant amount of power from the electrical grid, especially during peak charging times. If a large number of EVs are charging simultaneously in an area with limited substation capacity, it can lead to an increased load on the substation. Substation overload can be reduced by employing the proposed approach, the grid planning and optimization tool (GPOT), to aid in grid planning and decision-making in regard to PV-BESS adoption. The optimization tool determines the PV-BESS installation and substation upgrade that maximizes net present value (NPV) under the criteria specified by the user using time-series data for distribution grid load and solar power output along with the BESS characteristics. The best-case outcomes and CO2 emissions are compared in a cost-benefit analysis. Case study data from a residential building’s load are employed to illustrate the capabilities of GPOT.

Modernization of Electric Power Systems: Energy Efficiency and Power Quality, 2023

Short circuit fault currents are increasing due to growing demand for electricity and high comple... more Short circuit fault currents are increasing due to growing demand for electricity and high complexity in power systems. Because the fault currents reach the highest value, which the breakers are unable to restrict, the electrical grid’s security is in jeopardy. By entering a limiting impedance into a transmission line in series, these impedances restrict the rising amounts of fault currents to levels that are acceptable. Saturated core fault current limiters (SCFCLs) are a pivotal tool for limiting fault currents rise in power networks that have good performance characteristics. In a normal condition, these limiters have slight effects on the system and can effectively limit short-circuit currents when they occur. In this chapter, various structures of SCFCLs with different arrangements of ac windings and dc windings are presented, and the currents passing through the FCLs under the normal and faulty system conditions are assessed and compared. The flux density in various regions of the core in different arrangements has been investigated as well, and the desired analyses have been performed. Simulation will be presented based on COMSOL Multiphysics 5.4, a finite element software package which can provide a precious assessment to compare these protective devices with different configurations.

John Wiley & Sons, 2022

Nowadays, electric railways play a pivotal role in public transportation in terms of speed, time,... more Nowadays, electric railways play a pivotal role in public transportation in terms of speed, time, less pollution, etc. However, because of weak insulation of the running rails, a small amount of traction current can leak into the earth and underground infrastructures, which are called stray currents. These currents can be hazardous for electric railway systems, and it is a necessity to pay precise attention to them as an unfavorable current flow. They can impose several million dollars’ loss on governments if there will not be workable solutions to reduce negative consequences. Annually, they cause irreparable damage to underground infrastructures such as computer sites, pipelines, and cables. Hence, suggesting control methods for stray currents, mitigation will be indispensable either for the governments and rail stations’ personnel because of electric shocks. This chapter presents a review of control strategies for mitigating these hazardous currents, which can lead to pipelines or other infrastructures’ corrosion.

arXiv (Cornell University), Jun 8, 2024

Cybersecurity breaches in digital substations can pose significant challenges to the stability an... more Cybersecurity breaches in digital substations can pose significant challenges to the stability and reliability of power system operations. To address these challenges, defense and mitigation techniques are required. Identifying and detecting anomalies in information and communication technology (ICT) is crucial to ensure secure device interactions within digital substations. This paper proposes a task-oriented dialogue (ToD) system for anomaly detection (AD) in datasets of multicast messages e.g., generic object oriented substation event (GOOSE) and sampled value (SV) in digital substations using large language models (LLMs). This model has a lower potential error and better scalability and adaptability than a process that considers the cybersecurity guidelines recommended by humans, known as the human-in-the-loop (HITL) process. Also, this methodology significantly reduces the effort required when addressing new cyber threats or anomalies compared with machine learning (ML) techniques, since it leaves the model's complexity and precision unaffected and offers a faster implementation. These findings present a comparative assessment, conducted utilizing standard and advanced performance evaluation metrics for the proposed AD framework and the HITL process. To generate and extract datasets of IEC 61850 communications, a hardware-inthe-loop (HIL) testbed was employed.