Electric Power Networks Research Articles

A Bayesian approach for estimating the post-earthquake recovery trajectories of electric power systems in Japan

ABSTRACT Post-disaster recovery modelling of engineering systems has become an important facet of catastrophe risk modelling and management for natural hazards. The post-disaster recovery trajectory of a civil infrastructure system can be quantified using (a) the initial post-disaster functionality level, Q o ; (b) rapidity, h (i.e., the rate of functionality restoration); and (c) recovery time, R t . This study uses a Bayesian estimation approach to derive a set of probabilistic models to estimate Q o , R t , and h of electric power networks (EPNs) using post-earthquake recovery data from 16 large earthquakes in Japan between 2003 and 2022. The considered predictor (explanatory) variables include earthquake magnitude, year of occurrence, seismic intensity, and exposed population (PEX). Apart from being a simple and efficient stand-alone tool, the proposed data-driven models can be a useful benchmarking tool for simulation-based approaches for EPN recovery modelling.

Implications of 5G rollout on post-earthquake functionality of regional telecommunication infrastructure

Telecommunication infrastructure (TI) is becoming increasingly vital in modern society, where information exchange is needed in almost all aspects of the built environment, business operations, and people's daily lives. The ongoing 5G rollout will lead to a paradigm shift in regional TI deployment landscape, with increased seismic hazard exposure particularly due to the densely deployed small cells. As TI is known to be vulnerable to seismic hazard impacts yet necessary for post-earthquake emergency response, this study carries out a pioneering effort in quantifying the post-earthquake TI failures and functionality to better support risk mitigation decision-making. We propose a novel seismic risk assessment framework for regional 5G TI, by holistically integrating regional seismic hazard analysis, infrastructure seismic exposure data, electric power infrastructure seismic fragility modeling and network connectivity analysis, as well as wireless TI functionality modeling. The proposed framework is evaluated based on a hypothetical regional infrastructure testbed located in Memphis, Tennessee, subjected to several earthquake scenarios. From a reference heterogeneous 5G TI deployment scenario, the results indicate that significant performance degradation of 5G TI is expected especially after major earthquake events. Enabled by the proposed framework, we further compared the efficacy of several risk mitigation strategies and pertinent implications are provided.

A Multi-Source Power System’s Load Frequency Control Utilizing Particle Swarm Optimization

Electrical power networks consist of numerous energy control zones connected by tie-lines, with the addition of nonconventional sources resulting in considerable variations in tie-line power and frequency. Under these circumstances, a load frequency control (LFC) loop gives constancy and security to interconnected power systems (IPSs) by supplying all consumers with high-quality power at a nominal frequency and tie-line power change. This article proposes employing a proportional–integral–derivative (PID) controller to effectively control the frequency in a one-area multi-source power network comprising thermal, solar, wind, and fuel cells and in a thermal two-area tie-line IPS. The particle swarm optimization (PSO) technique was utilized to tune the PID controller parameters, with the integral time absolute error being utilized as an objective function. The efficacy and stability of the PSO-PID controller methodology were further tested in various scenarios for proposed networks. The frequency fluctuations associated with the one-area multi-source power source and with the two-area tie-line IPS’s area 1 and area 2 frequency variations were 59.98 Hz, 59.81 Hz, and 60 Hz, respectively, and, in all other investigated scenarios, they were less than that of the traditional PID controller. The results clearly show that, in terms of frequency responses, the PSO-PID controller performs better than the conventional PID controller.

Dynamic Voltage Stability of an Electric Power Network with Double Fed Induction Wind Power Generators

In recent years, the large penetration of wind power poses new challenges for the voltage stability analysis of an electric power network. In this paper is studied the effect of large scale integration of wind power in the dynamic voltage stability of a power network under a fault condition. The automatic voltage regulators of the generating units, the turbine speed governors and the double fed induction generator were modeled. Different load models were used and the under load tap changers were also taken into account. The simulation results were obtained using the EUROSTAG software package. Finally, some conclusions that provide a better understanding of the dynamic voltage stability in a system with a large amount of wind power generation are pointed out.

Proposal of a regional grid cluster model for analysis of electrical power network performance

Proposal of a regional grid cluster model for analysis of electrical power network performance

Risk assessment and electrical control of high-permeability renewable energy photovoltaic system under extreme weather conditions

Abstract High-permeability photovoltaic (PV) systems are a key technical way to bring about new energy changes in electric power networks. Risk assessment and electrical regulation during extreme weather can make PV systems with high permeability work much more efficiently during severe weather. We establish an operational risk model for a high penetration rate PV system using the PV probability model, load parameter model, and probabilistic trend calculation model. Based on the results of the tidal current calculation, the risk assessment indexes of PV systems are constructed, including the voltage overrun risk index and branch circuit tidal current overrun risk index. The Monte Carlo simulation method using the Latin hypercubic sampling method is used to simulate the operational loads of PV systems under extreme weather conditions such as windy, rainy, and snowy conditions and to form a fault simulation set. Finally, we implement the QMC method to assess the risk of PV systems with high permeability and use the RBF neural network design to achieve automatic control of PV electrical equipment. When the weather is the same extreme, the risk of overrun at each node goes up with the number of nodes. When the weather is different, the risk of voltage overrun at each node under ice-covered load goes up by about half compared to rain load, and the risk of active overrun at each branch goes up by almost six times compared to rain load.

Optimization of losses by switching to higher voltage in distribution networks

The article considers the basis of scientific research in the field of electric power industry the issues of transition to 20 kV voltage in the distribution power grids of Uzbekistan. The main advantages of this method are analysed, as well as the factors affecting power and energy losses in electrical systems and networks. The paper presents a schematic diagram of an electric network section, on which a comparative calculation and analysis of voltage, energy and power losses in 6/10/20 kV networks is carried out. Special attention is paid to the peculiarities of calculation of these parameters, as well as the basic expressions for their calculation and the resulting graphical relationships. From the analysis it can be concluded that it is reasonable to use 20 kV voltage in distribution networks. It allows to reduce power and energy losses, which is an important factor in the efficient operation of electric power systems, to increase line capacity and service range. However, when selecting the optimal voltage for certain conditions, it is necessary to take into account a number of factors, such as the length of transmission lines, the type of wires and transformers used, and the load level of the network.

A Comprehensive and Critical Review on Integrated Electric Power and Gas Networks

A Comprehensive and Critical Review on Integrated Electric Power and Gas Networks

Fast and Generic Energy Flow Analysis of the Integrated Electric Power and Heating Networks

Energy flow analysis is a fundamental tool to determine the network states of the integrated energy systems (IES). For the widely deployed IES with coupled power grids (PG) and heating networks (HN), we still lack a generic tool that can be easily employed to calculate the quasi-dynamic energy flows of it. In this paper, we have developed a generic code package (named as MATHN) for energy flow analysis of the quality-regulated HN. After that, a generic solution framework that leverages MATPOWER and MATHN to realize decomposed energy flow calculation of PG and HN is proposed. Behind the MATHN tool, a model reformulation technique is proposed to eliminate the massive indirect variables of the basic HN model discretized by finite difference, which finally derives a compact matrix formulation (similar to the network equation of power grid: I=YU) for generic description of any HN and also slashes the original model scale by around 20 times. Moreover, the solution strategy behind the MATHN tool further converts this matrix formulation into a standard system of non-homogeneous linear equations, with which some existing well-recognized algorithms can be directly applied for efficient and accurate solution. Case studies on three different scales of test systems demonstrate the generality, efficiency and accuracy of our methods. All the codes and input data are packaged into the MATHN tool and are made open-source for non-commercial use.

ETAP software based power flow analysis of 225/60/11KV substation in Tinghir

Through technological advances, such as computer-based software, it is now possible to study and analyze complex electrical system problems and identify potential solutions. This analysis typically includes Load flow analysis (LFA), or power flow analysis (PFA). LFA is a crucial tool in power system engineering used for modeling and designing electrical power networks. It aims to determine the steady-state operating conditions of a power system to ensure a stable and efficient power balance between generation and load demands. LFA helps design robust power networks, maintains system stability, plans maintenance activities, and assists in the economic dispatch of power generation. This study focuses on modelling the 225/60/11 kV substation in Tinghir, a predominantly rural subdivision of the Drâa-Tafilalet region of Morocco. The model used data obtained from SPIE Maroc, specialists in industrial and tertiary electricity. AC and DC load flow analysis is performed on the Tinghir substation auxiliary services under two scenarios: one where the service equipment is powered by the auxiliary service transformer (AST) as the primary source, and another where the equipment supplied by a generator set due to a failure in the main power supply. ETAP software is selected for the simulation due to its advanced real-time power management capabilities and is widely used in power generation, transmission, and distribution systems. The Newton-Raphson method, known for its fast convergence and accuracy, is used for power flow analysis, making it ideal for complex systems. The results evaluate system performance under both normal and backup conditions, ensuring reliable operation of the auxiliary service installation at Tinghir’s substation.

A Novel Perspective for Hosoya and M Polynomials for Analyzing Electric Power Network Topology

A Novel Perspective for Hosoya and M Polynomials for Analyzing Electric Power Network Topology

The power flow analysis for electric power network: A tutorial article

The power system network is complex. This makes it more challenging to obtain valuable information because of its hundreds of buses and transmission lines. In addition, solving the steady-state equations of the power system network requires substantial mathematical computations. The power flow analysis is a study of the electrical power system. Engineers and utility companies use it for the design, control, planning, and future improvement of the electrical power network. Power flow analysis calculates the voltage magnitude, phase angles, active and reactive power flows, losses of the power system network under various loads, and generation conditions. This paper is a tutorial article aimed to present the power flow analysis techniques of Gauss-Seidel, Newton-Raphson, and Fast-Decoupled approaches. The Power World Simulator is used to demonstrate the software implementation of the approaches. The results show that Newton Raphson and Fast Decoupled have a faster convergence. The Newton Raphson method is the popular technique used for the analysis. An illustrative example for an IEEE 3-bus system on each technique is also presented in the article.

АВТОМАТИЗИРОВАННАЯ СИСТЕМА СУШКИ И ОЧИСТКИ РАСТИТЕЛЬНОГО СЫРЬЯ С ПРИМЕНЕНИЕМ ТЕПЛОВЫХ АККУМУЛЯТОРОВ И ЭЛЕКТРОНАГРЕВАТЕЛЕЙ С ЭФФЕКТОМ САМОРЕГУЛИРОВАНИЯ ТЕМПЕРАТУРЫ

The paper presents an automated system for processing fruit and vegetable products, which includes such technological operations as steam peeling (thermovacuum method), cutting, convective and vacuum drying of fruit and vegetable products. For efficient operation of the plant a control system is used, which provides full automation of the whole complex of technological elements. The plant has a high level of energy efficiency, as it uses thermal accumulators (with the effect of thermomagnetic convection) and heaters with temperature self-regulation. The parameters of the operation modes of thermal accumulators agree with the operation of the heater with adaptive energy consumption (with variable power and constant temperature) depending on the temperature of heating of plant raw materials. At the first stage, when intensive heat flow is required for drying - thermal accumulators provide inertia-free heating of horticultural products. The function of the heater is connected with controlled heating depending on the temperature of plant raw material, providing heat flow correlated with the operation of thermal accumulators. The use of combined and adaptive heating from thermal accumulators and electric heaters allows for uniform temperature distribution (temperature field), which ensures efficient processing of vegetable raw materials. Automated change of heating power from electric heaters and thermal accumulators provides the possibility of adaptation to any power electric network based on the need for the level of processed horticultural products, and the use of thermal accumulators allows to accumulate thermal energy from solar collectors.

Modelling the operation modes of local MicroGrid networks with mobile wind and solar power plants

The basis for the development of the global energy sector is the introduction of alternative energy and, accordingly, a complete change in approaches to the structural reorganisation of energy systems. An analysis of the state of electric power networks in Ukraine shows their almost complete depreciation, low reliability and structural obsolescence, which makes further development and expansion difficult to ensure the rapid growth of electricity consumption. Therefore, a trendy solution to the problem of modernising electric power networks while increasing their capacity and reliability is the use of MicroGrid systems, which are structural elements of the Smart Grid concept based on the intellectualisation of the management of the full cycle of electricity generation, use and storage. The miniaturisation and localisation of smart electric networks makes it possible to minimise power losses and ensure full control over their operating modes. A MicroGrid provides management of distributed energy resources and is essentially a hybrid, as it includes renewable energy sources alongside traditional ones. Regulation of MicroGrid operation modes and power flows in it is the key to increasing the sustainability of the operation processes. The article proposes the use of mobile wind-solar power plants as sources of distributed generation in the MicroGrid system, which is a new technical solution for improving the structural scheme of its implementation and optimising the management of operating modes. The structure of MicroGrid is substantiated and developed, and mathematical modelling of autonomous and hybrid modes of operation of the system with mobile renewable energy power plants is performed. The obtained results show the feasibility and energy efficiency of the developed MicroGrid system. Conclusions are drawn regarding the prospects for further development of MicroGrid with mobile power plants.

Analysis of Reactive Power in Electrical Networks Supplying Nonlinear Fast-Varying Loads

This study concerns problems related to the assessment of reactive power in power networks with nonlinear fast-varying loads, such as electric arc furnaces, rolling mill drives, etc. The operation of this type of load is characterized by the introduction of interharmonic currents (including higher harmonics) into the power supply network and a relatively low power factor. Rapid changes in the RMS value of the current also cause voltage fluctuations and the related phenomenon of light-flickering. Therefore, there is a need to evaluate the power selection of compensating devices, taking into account the random nature of load changes and the distortion of current and voltage waveforms, in particular, interharmonic components, the impact of which has not been fully investigated so far. To analyze the random nature of load changes, autocorrelation functions were used, which allowed for the estimation of the expected values of the arc furnace current distortion coefficient (based on the recorded waveforms). In order to determine the parameters of reactive power compensating devices, and in particular capacitor banks, an autocorrelation function in the exponential-cosine-sine form was used, which meets the conditions of differentiation. This study contains comparative results of the reactive power of capacitor banks determined using different methods. The criterion for selecting capacitor bank parameters was the minimization of energy losses in the power supply network. The calculations presented in this study show that by taking into account higher harmonics and interharmonics in the voltage and currents of fast-varying loads, the installed power of the capacitor bank can be reduced by approximately 7%, and energy losses in the power grid can be reduced by 3–5%.

Predictive models of the dependability of electric power transmission (using the example of AO Tyvaenergo)

Aim. The paper analysed the damage rate of the electric power networks of AO Tyvaenergosbyt between 2014 and 2022 and preventively evaluates emergency shutdowns in the company’s networks in 2023. The author provides a brief historical reference regarding the company’s foundation, a description of the structure of its power supply network. The damage rate of elements, as well as main electrical equipment of the company’s power supply network were examined. The quantity of electrical power undersupplied to customers as the result of emergency shutdowns was analysed. The number of failures was classified depending on the amount of undersupplied electrical power. The paper studied the applicability of certain methods of prediction of the number of emergency shutdowns for the obtained interpolated series of preceding failures. The most appropriate method was established that was used for preventively evaluating the damage rate of the examined power networks for each month of 2023.Methods. The paper uses methods of mathematical analysis, general scientific methods of research, properties and capabilities of the MATLAB graphic interface and Excel tables. Statistical and cybernetical methods of prediction were considered for the purpose of predictive model development. The probability of failures within the examined power networks was evaluated. Equations were obtained for autoregression failure models that enable predictive evaluation of failure by months.The Results of the study may prove to be useful to the experts of Tyvaenergosbyt, as well as other power grid companies that are developing advanced emergency prevention activities aimed at improving the reliability of power supply.Conclusion. The approach to predictive evaluation of emergency shutdowns proposed in the paper showed that the most efficient method of predicting failures in a company’s power networks is the method of autoregression models using interpolation of data on preceding failures. The probability of prediction fulfilment is 95%.

A novel and effective method based deep learning model for detecting non-technical electricity losses

<p>This study focused on non-technical electricity loss detection. As mentioned, non-technical losses (NTLs) affect utilities and economies financially. Electricity theft, fraud, and metering issues can create NTLs. NTL generate most distribution losses in electrical power networks, costing utilities a lot. NTL detection approaches are data-focused, network-oriented, or hybrid. Data-oriented writing dominated this analysis. After data collection and cleaning and labeling the unlabeled dataset with a target, a methodology was supplied that used four machine learning techniques random forest, decision tree, KNN, and logistic regression and four neural network models-DNN, CNN, CNN-LSTM, and CNN-GRU. The CNN and DNN model have the best accuracy, stability, fast learning, and training time.</p>

Benefit allocation of electricity–gas–heat–hydrogen integrated energy system based on Shapley value

Abstract The integrated energy system is an important development direction for achieving energy transformation in the context of the low-carbon development era, and an integrated energy system that uses renewable energy can reduce carbon emissions and improve energy utilization efficiency. The electric power network and the natural gas network are important transmission carriers in the energy field, so the coupling relationship between them has been of wide concern. This paper establishes an integrated energy system considering electricity, gas, heat and hydrogen loads; takes each subject in the integrated energy system as the research object; analyses the economic returns of each subject under different operation modes; applies the Shapley value method for benefit allocation; and quantifies the contribution value of the subject to the alliance through different influencing factors to revise the benefit allocation value. Compared with the independent mode, the overall benefits of the integrated energy system increase in the cooperative mode and the benefits of all subjects increase. Due to the different characteristics of different subjects in terms of environmental benefits, collaborative innovation and risk sharing, the benefit allocation is reduced for new-energy subjects and increased for power-to-gas subjects and combined heat and power generation units after revising the benefit allocation, to improve the matching degree between the contribution level and the benefit allocation under the premise of increased profit for each subject. The cooperative mode effectively enhances the economic benefits of the system as a whole and individually, and provides a useful reference for the allocation of benefits of integrated energy systems. The analysis shows that the revised benefit distribution under the cooperative model increases by 3.86%, 4.08% and 3.13% for power-to-gas subjects, combined heat and power generation units, and new-energy units, respectively, compared with the independent function model.

Localization and Estimation of Unknown Forced Inputs: A Group LASSO Approach

This paper studies the problem of locating the sparse set of sources of forcing inputs driving linear systems from noisy measurements when the initial state is unknown. This problem is particularly relevant to detecting forced oscillations in electric power networks. We express measurements as an additive model comprising the initial state and inputs grouped over time, both expanded in terms of the basis functions (i.e., impulse response coefficients). Using this model, with probabilistic guarantees, we recover the locations and simultaneously estimate the initial state and forcing inputs using a variant of the group LASSO (linear absolute shrinkage and selection operator) method. Specifically, we provide upper bounds on: (i) the probability that the group LASSO estimator incorrectly identifies the locations and (ii) the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\ell _{2}$</tex-math></inline-formula> -norm of the estimation error. Our bounds depend on the number of measurements, inputs, and sensors; the sensor noise variance; and the minimum singular value of the observability and impulse response matrices. Our theoretical analysis is one of the first to provide a complete treatment for the group LASSO estimator for the left invertible linear systems with delay. Finally, we validate the performance of the estimator on synthetic models and the IEEE 68-bus, 16-machine power system.

Example of Matlab/Simulink Tool Usage for Evaluation of Wind Turbine Operation During Voltage Regulation and Reactive Power Regulation

Abstract In this paper, the types of wind turbines are listed and described, with the emphasis on horizontal-axis wind turbines. The parts are explained in more detail, the criteria for the selection of the wind turbine generator and the methods of managing the wind turbine are defined. In the Matlab/Simulink programming environment, a model of an electric power network with a wind farm was created, and the characteristics of the operation of wind turbines under normal and fault conditions were presented.