Power System Analysis Research Articles

Scaling Graph Neural Networks for Large-Scale Power Systems Analysis: Empirical Laws for Emergent Abilities

Scaling Graph Neural Networks for Large-Scale Power Systems Analysis: Empirical Laws for Emergent Abilities

Dynamic stability analysis of the aircraft electrical power system in the more electric aircraft concept

This paper presents the modelling and analysis process of the electrical power management system on board an electrified aircraft conforming to the More/All Electric Aircraft concept. The main objective of the study is to assess the stability of the Electric Power Distribution System under different operational conditions, including the aspect of constant power loads. The paper describes the structure of the system, in which the key role is played by a synchronous generator and a three-phase rectifier converting alternating current AC into direct current DC. To solve the problem, modeling methods in the Matlab/Simulink environment were used, which enabled the analysis of the dynamic properties of the system and the assessment of stability under various types of loads. The obtained test results show that the presence of constant power loads can lead to instability in the EPDS system, manifested by voltage and current oscillations exceeding the standards specified in the MIL-STD-704E standard. The paper also provides tools for predicting system stability without the need to conduct full stability tests, which is important for the design of modern aviation power systems. The final section of the work presents the research results obtained and the resulting significant insights and practical conclusions.

Operation Analysis of Power Systems with HVDC Interconnections Using a Transient Stability Aware OPF Method

High-voltage direct current (HVDC) transmission systems are widely used today due to their several advantages over high-voltage alternative current (HVAC) systems. They are primarily utilized in connecting different large grids or smaller independent networks, especially in submarine interconnections. Many studies have been conducted globally on the optimal planning, operation, and control of these power systems. Understanding the transient stability of these systems during significant disturbances is also of great importance. This paper specifically focuses on power systems with HVDC connections and high penetration of renewable energy sources. Analytical models were developed for power system components like HVDC converters, DC lines, and full converter wind generators. A simulation of a test-case power system was conducted, including various significant disturbances such as HVDC line trips, short circuits, power unit failures, and major changes in load. The voltage and frequency stability of the system under specific operational scenarios was also examined. The results obtained indicate technical limitations and operating guidelines to avoid undesirable conditions and system failure. In conclusion, adopting short-term stability tests the optimal operation point of the system, and the limitations in the penetration by RES units can be decided.

New Safety Feedback Control Design to Guarantee Adequate Frequency Performance in Microgrids

ABSTRACTSafety analysis of power systems is concerned with the system's ability to maintain critical variables within specified limits following a disturbance. Frequency control adequacy has become increasingly important as the system inertia decreases due to the increase in renewable energy penetration. Various controllers for inverters have been proposed to improve the system frequency response and few are capable to ensure the safety of the response. In this article, a diesel‐wind energy system is considered and modeled as a switching system between normal, faulted, and post‐fault modes. A safety feedback controller is designed as a supplementary signal for a wind turbine generator such that the speed of the diesel generator stays within a permissible range in the presence of a finite energy disturbance. Numerical results on the modified 33‐bus microgrid system obtained of the proposed novel approach indicate that the suggested control configuration can guarantee adequate frequency response without excessive conservativeness.

Complementary Analysis and Performance Improvement of a Hydro-Wind Hybrid Power System

Hydropower as a flexible regulation resource is a rare choice to suppress the ever-increasing penetration of wind power in electrical power systems. The complementary characteristics and performance improvement of a hydro–wind hybrid power system based on a mathematical model of the hybrid power system is studied in this paper. This established model takes into account the stochastic variation in wind speeds in the wind power subsystem and the hydraulic–mechanical–electrical coupling characteristics of the hydropower subsystem. The complementary analysis is conducted based on the evaluation variables outputted by the established model, such as the wind power, hydro-regulation power, hydraulic power, and frequency. To make full use of the regulation capability of the hydropower system, the optimization of parameter settings is also carried out to improve complementary performances of the hybrid power system. The results from the complementary analysis show the detailed characteristics of hydro–wind coordinated operation under different types of real wind speeds. Here, 95% of installed hydro-capacity is used to complement the power shortage of the intermittent wind energy under the low wind speed. Alternatively, only around 66% of the installed hydro-capacity can be utilized to cope with the fluctuation in wind power under the medium and high wind speeds before the optimization of parameter settings. The recommended values and change rules of the control, hydraulic, and electrical parameters for the hydropower system are subsequently revealed from the analysis of parameter settings to contribute to a stable and safe hybrid power system. The results show that the optimized parameter can increase the maximal regulating capacity of the hydropower system by nearly 9 MW, approximately a sixth of the total installed hydropower capacity. The method and results obtained in this paper provide theoretical and technical guidance for the safe and economical operation of power stations.

Motor Fault Diagnosis and Detection with Convolutional Autoencoder (CAE) Based on Analysis of Electrical Energy Data

This study develops a Convolutional Autoencoder (CAE) and deep neural network (DNN)-based model optimized for real-time signal processing and high accuracy in motor fault diagnosis. This model learns complex patterns from voltage and current data and precisely analyzes them in combination with DNN through latent space representation. Traditional diagnostic methods relied on vibration and current sensors, empirical knowledge, or harmonic and threshold-based monitoring, but they had limitations in recognizing complex patterns and providing accurate diagnoses. Our model significantly enhances the accuracy of power data analysis and fault diagnosis by mapping each phase (R, S, and T) of the electrical system to the red, green, and blue (RGB) channels of image processing and applying various signal processing techniques. Optimized for real-time data streaming, this model demonstrated high practicality and effectiveness in an actual industrial environment, achieving 99.9% accuracy, 99.8% recall, and 99.9% precision. Specifically, it was able to more accurately diagnose motor efficiency and fault risks by utilizing power system analysis indicators such as phase voltage, total harmonic distortion (THD), and voltage unbalance. This integrated approach significantly enhances the real-time applicability of electric motor fault diagnosis and is expected to provide a crucial foundation for various industrial applications in the future.

Energy efficiency analysis of ammonia-fueled power systems for vehicles considering residual heat recovery

Ammonia shows great potential as a zero-carbon fuel for vehicles. However, both the internal combustion engine (ICE) and the proton exchange membrane fuel cell (PEMFC), the currently available vehicle engines, require hydrogen decomposed from ammonia. On-board hydrogen production is an energy-intensive process that significantly reduces system efficiency. Therefore, energy recovery from residual heat is essential to promote overall efficiency, but ICE and FC require different amounts of hydrogen, and produce residual heat of dissimilar quality and quantity. To thoroughly understand the relationships among system configuration, rate of residual heat recovery and system efficiency, this paper takes three typical ammonia-fueled power systems, which employs only ICE, only PEMFC and both ICE and PEMFC as engine(s), respectively, as examples to set up system efficiency model and conduct simulation under various operating conditions. Results show there is a mismatch between the produced residual heat and the heat required for ammonia decomposition for systems using only ICE or PEMFC. For system using both PEMFC and ICE, the residual heat can be recovered to a maximum extent by way of parameters matching and dynamic power management between engines. This system has the highest efficiency and widest high efficiency region among the three analyzed typical configurations.

Online Monitoring System of Electromechanical Transient Simulation Data of Distribution Network Based on Edge Computing

The current distribution network is developing toward the direction of information and intelligent distribution Internet of Things (IoT). In order to explore the online monitoring system for transient electromechanical simulation of distribution networks, this paper is based on the equivalent model of generator sets. Firstly, it describes the relevant theoretical knowledge of edge computing, designs the distribution IoT based on edge computing, and briefly introduces its network architecture. Secondly, based on the discrete-time domain equivalent model of generators, the electromechanical transient simulation distribution network is constructed by introducing the machine network division of the power network. Finally, the Western System Coordinating Council (WSCC)-3 units and 9 nodes are taken as an example, and simulation experiments are conducted under two fault simulation conditions to verify the effectiveness of the simulation model. The results show that under the two fault simulation conditions, the results of equivalent model simulation of generator terminal voltage and relative power angle change are like those of the Power System Analysis Software Package (PSASP). The changing trend of the two is similar and stable. After the PSASP results are stabilized at a value, the simulation results fluctuate extremely up and down the value. For example, under fault condition 1, the changing trend of the relative power angle of the No. 2 generator is first fluctuating and then becomes stable. After violent fluctuation, the relative power angle tends to be stable from about 20s to -12.35°. The result of PSASP software is stable at -12.35°. The transient electromechanical simulation of the generator equivalent model can provide some ideas for the online monitoring system of the distribution network.

Real-Time Simulation and Hardware-in-the-Loop Testing Based on OPAL-RT ePHASORSIM: A Review of Recent Advances and a Simple Validation in EV Charging Management Systems

Phasor-domain (RMS) simulations have become increasingly vital in modern power system analysis, particularly as the complexity and scale of these systems have expanded with the integration of renewable energy sources. ePHASORSIM, an advanced phasor-based simulation tool developed by OPAL-RT, plays a crucial role in this context by enabling real-time phasor-domain simulation and hardware-in-the-loop testing. To keep pace with these evolving needs, continuous efforts are being made to further improve the accuracy, efficiency, and reliability of ePHASORSIM-based simulations. These efforts include automating model conversion processes for enhanced integration with ePHASORSIM, extending ePHASORSIM’s simulation range with custom models, developing hybrid co-simulation techniques involving ePHASORSIM and an EMT simulator, enhancing simulation scalability, and refining HIL testing to achieve more precise validation of control and protection systems. This paper provides a comprehensive review of these recent advances. Additionally, the paper discusses the conversion of models from PowerFactory—a widely used and comprehensive modeling environment—to ePHASORSIM through both automated tools and manual methods using Excel workbooks, which has been discussed little in the literature. Furthermore, as ePHASORSIM is a relatively new tool with limited cross-validation studies, the paper aims to contribute to this area by presenting a comparative validation against DIgSILENT PowerFactory, with a specific emphasis on its application in electric vehicle charging management systems.

A Power Grid Topological Error Identification Method Based on Knowledge Graphs and Graph Convolutional Networks

Precise and comprehensive model development is essential for predicting power network balance and maintaining power system analysis and optimization. The development of big data technologies and measurement systems has introduced new challenges in power grid modeling, simulation, and fault prediction. In-depth analysis of grid data has become vital for maintaining steady and safe operations. Traditional knowledge graphs can structure data in graph form, but identifying topological errors remains a challenge. Meanwhile, Graph Convolutional Networks (GCNs) can be trained on graph data to detect connections between entities, facilitating the identification of potential topological errors. Therefore, this paper proposes a method for power grid topological error identification that combines knowledge graphs with GCNs. The proposed method first constructs a knowledge graph to organize grid data and introduces a new GCN model for deep training, significantly improving the accuracy and robustness of topological error identification compared to traditional GCNs. This method is tested on the IEEE 30-bus system, the IEEE 118-bus system, and a provincial power grid system. The results demonstrate the method’s effectiveness in identifying topological errors, even in scenarios involving branch disconnections and data loss.

4E Analysis of Solar Photovoltaic, Wind, and Hybrid Power Systems in Southern Pakistan: Energy, Exergy, Economic, and Environmental Perspectives

4E Analysis of Solar Photovoltaic, Wind, and Hybrid Power Systems in Southern Pakistan: Energy, Exergy, Economic, and Environmental Perspectives

Numerical investigation on the thermal performance of a molten salt tank under different electric heating method

Two-tank molten salt (MS) thermal energy storage (TES) technology is an efficient and widely used energy storage technology. This study develops a two-dimensional discrete model (2DIM) using the Modelica language to accurately and quickly represent molten salt temperature distribution and heat loss, applicable to system-level analysis in thermal power systems. It also uncovers variations in heat loss, cooling rate, and required auxiliary electric heating power across different tank volumes, liquid levels, and MS temperatures, offering guidance for optimizing design, energy management, and operational strategies. Additionally, the study examined the impact of different electric heater placements on the performance of the thermal storage system. The results show that heating the gas inside the tank is more effective than traditional direct electric heating, reducing molten salt heat loss by 25.89 % and increasing energy storage efficiency by 0.17 %.The research provide a reference for the study of efficient utilization of TES tank in different thermal systems.

Environmental, technological, and economic analysis of supercritical coal-fired power system.

Developing countries primarily rely on fossil-based energy sources to meet their energy demands. The use of fossil fuels has several adverse environmental repercussions that damage the biosphere both directly and indirectly. Among fossil fuels, coal brings about the heaviest environmental externalities, yet its abundance makes its use widespread, particular in countries having significant power generation deficits, such as Pakistan. This study presents an environmental, technological, and economic analysis of a supercritical coal-based power unit located in Pakistan and used for electricity generation. For environmental assessment, the CML-1A baseline method in OpenLCA software was used, and eight midpoint impact indicators were selected. The functional unit chosen was 1 MWh of generated electricity. The results indicated that the category of ozone layer depletion has the least impact, whereas global warming potential has the highest impact score. Except for photochemical oxidation and human toxicity, the plant operational stage dominated most of the selected impact categories. The current paper also reveals that the removal efficiency of CO2 and other pollutants is higher in supercritical compared to subcritical plants. Moreover, the economic feasibility of supercritical plant is compared with chemical looping combustion (CLC)-based supercritical coal-fired power plant, and results shows that CLC-based coal-fired power plant is a more competitive and environmentally friendly option. The utilization of a scientific cleaner energy-management system in real-time, as exemplified in this study, may facilitate the development of a optimalpolicy framework that encouragesfor the adoption of cleaner coal power generation in developing countries, ultimately resulting in improved energy sustainability. Furthermore, this paper also presents some policy implications which could be helpful for policymakers, researchers, and industrialists to improve the sustainability of energy in emerging economies.

Meta-transfer learning-based method for multi-fault analysis and assessment in power system

Meta-transfer learning-based method for multi-fault analysis and assessment in power system

I-CNN-LSTM: An Improved CNN-LSTM for Transient Stability Analysis of More Electric Aircraft Power Systems

I-CNN-LSTM: An Improved CNN-LSTM for Transient Stability Analysis of More Electric Aircraft Power Systems

Small-Signal Stability Analysis of DC Ship Hybrid Power System With Energy Storage Device Based on Hybrid H-Matrix Model

Small-Signal Stability Analysis of DC Ship Hybrid Power System With Energy Storage Device Based on Hybrid H-Matrix Model

Modeling and Stability Analysis of Fuel Cell-Based Marine Hybrid Power Systems

Modeling and Stability Analysis of Fuel Cell-Based Marine Hybrid Power Systems

Optimal design and techno-economic analysis of a solar-wind hybrid power system for laayoune city electrification with hydrogen and batteries as a storage device

The pressing environmental concerns associated with fossil fuels have propelled renewable energy sources, particularly solar and wind energy, into a more prominent position. This article aims to explore an optimal configuration and conduct a technical and economic analysis of a hybrid solar-wind energy system tailored for electrifying Laayoune city. This system, equipped with hydrogen tank and batteries as storage devices, aims to meet the annual energy requirements of residential areas estimated at 310.87 GWh/year. In addition to addressing energy needs, the study tackles significant challenges such as reducing dependence on traditional energy sources, curbing greenhouse gas emissions, and bolstering energy security in the region. Utilizing HOMER Pro software, the research evaluates various combinations of renewable resources, including solar and wind, alongside storage solutions such as batteries, fuel cells, and hydrogen storage, to find the most viable solution in terms of electricity generation, cost, and environmental impact. The findings highlight a hybrid configuration comprising solar, wind, battery, grid, and converter components as the most cost-effective approach for Laayoune's renewable energy system. This integrated system not only yields an energy cost of 0.0477 $/kWh and a net present cost (NPC) of 336 M$ but also generates 627.69 GWh/year of energy. Furthermore, it achieves a 100% renewable energy ratio while completely eliminating CO2 emissions.

Research Methods for Transient Stability Analysis of Power Systems under Large Disturbances

Transient stability analysis is critical for maintaining the reliability and security of power systems. This paper provides a comprehensive review of research methods for transient stability analysis under large disturbances, detailing the modeling concepts and implementation approaches. The research methods for large disturbance transient stability analysis are categorized into five main types: simulation methods, direct methods, data-driven methods, analytical methods, and other methods. Within the analytical method category, several common analytical strategies are introduced, including the asymptotic expansion method, intrusive approximation method, and other analytical methods. The fundamental principles, characteristics, and recent research advancements of these methods are detailed, with particular attention to their performance in various aspects such as computational efficiency, accuracy, applicability to different system models, and stability region estimation. The advantages and disadvantages of each method are compared, offering insights to support further research into transient stability analysis for hybrid power grids under large disturbances.

Performance analysis of IoT-enabled hydro-photovoltaic power systems considering electrical power mission chains

Synergistically and complementarily managing the operation of hydropower plants and other weather-dependent renewable energy generation plants (e.g., solar energy plants) provides an effective measure to improve the performance efficiency (PE) of renewable energy. However, environmental uncertainty and physical system unavailability pose challenges in assessing the PE of the power generation. This paper proposes an approach to synergistically and complementarily managing the operation of hydro-photovoltaic (HPV) power systems in IoT under uncertain environments and develops a mission chain-based PE model for quantifying the capacity of the fulfilment of a power supply mission to satisfy users’ demand for power. An importance measure-based restoration strategy is then proposed to enhance the PE of an HPV power system (PEPS). The approach is examined by taking a large-scale HPV in China in the case study. The results show that, in winters and in summers, the PEPS is higher than PE of a photovoltaic power system and a hydropower system, respectively, and the PEPS with the importance measure-based restoration strategy is higher than that under the random restoration strategy, respectively. The findings not only lay the foundation for the complementary operation of hybrid renewable energy power systems but also provide a reference for the restoration in case of power cuts.