Real Electrical Network Research Articles

Optimal allocation of renewable energy systems in a weak distribution network

In the context of a real electrical distribution network in Puerto Carreño, Colombia, this paper addresses the challenge of enhancing power supply reliability through the strategic integration of Renewable Energy Sources with Hydrogen Energy Systems. The planning problem is reformulated as a Mixed-Integer Quadratically Constrained Programming problem, enabling the use of efficient solvers with global optimal solution. Considering the extensive curtailment options and numerous allocation components, the optimization problem naturally scales up. To address this computational intensity, representative scenarios are derived from the original high-dimensional probability distribution employing the Gaussian Mixture Model. These scenarios are used in conjunction with the proposed optimization framework to achieve cost-effective power grids while reducing fossil fuel dependency.

Evaluation of Harmonic Currents and Network Impedance using Norton Model in an Unidentified Network Configuration

This paper presents a study that focuses on the evaluation of the analysis of harmonic currents emitted by loads and the harmonic impedance of a real electrical network using the Norton model. The primary advantage of employing this model lies in its ability to address scenarios where the complete network configuration, particularly from the distribution side, is not known. By calculating currents and voltages at the supply-side for two different operating conditions, the harmonic current content and the network impedance can be evaluated. To induce variations in operating conditions, a switching shunt capacitor is utilized. The results show that the fifth and the seventh harmonics clearly appear with values of 189.382 A and 135.073 A, respectively, while the other harmonics have values close to zero. The harmonic impedance also shows the presence of the fifth and the seventh harmonics with values of 1865.681 Ω and 4289.3 Ω, respectively. The main contribution of this paper focuses on converting the real electrical network into numerical data that can be accepted by the software. The components of the network model have to be carefully selected to understand the harmonic analysis and to success the simulation, which is conducted using the EMTP-ATPDraw program. The results of this investigation can be used as a database for electrical transmission and distribution companies in case of making any changes in the network, such as installation of new loads or cables, or in case of making measurements.

Uncertainty Detection in Supervisor–Operator Audio Records of Real Electrical Network Operations

The quality of verbal communication, understood as the absence of uncertainty in the message transmitted, is a key factor in mission-critical processes. Several processes are handled by direct voice communication between these endpoints and any miscommunication could have an impact in success of the task. For that reason, the quality control of verbal communication is required to ensure that the instructions issued are effectively understood and adequately executed. In this context, it is expected that instructions from the command center are issued once, and that the acknowledgment from the field are minimal. In the present work, the communication between an electrical company control center and factory workers in the field was chosen for analysis. We developed two complementary approaches by using machine learning and deep learning algorithms to assess, in an automatic way, the quality of information transmission in the voice communications. Preliminary results demonstrate that the automatic uncertainty detection is feasible, despite the small number of samples available at the present time. To support further studies, a repository was created in GitHub with the spectrogram and the tokenized words of all audios.

Optimizing TOC and IOC units of directional overcurrent relays in mutually coupled circuits using evolutionary PSO: Requirements and modeling

The efficient coordination of directional overcurrent relays is a challenging problem. Recent papers in the literature have focused on developing efficient algorithms to solve this issue. However, there is a lack of reporting practical procedures that affects the mathematical formulation to ensure accurate outputs by any optimization algorithm. In this paper, we show a comprehensive procedure that considers mutually coupled circuits via Graph Theory, the requirements of short-circuit current calculation, contingencies to be considered as well as the setting of Instantaneous Overcurrent (IOC) and Time Overcurrent (TOC) units, both for phase and ground protection. The simulation has been carried out by using a real electric network and C++ language programming. Computational simulation has shown the performance of the method, which provides high-quality solutions, with adequate coordination of the selected protective devices that increase the efficiency in setting this type of protection with safety. Evolutionary Particle Swarm Optimization (EPSO) outperformed conventional Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) as the best metaheuristic for optimally minimizing the proposed problem, achieving faster convergence times for the phase overcurrent protection scenario (16.36 s vs. 22.27 s and 17.03 s, respectively), and also for the ground overcurrent protection scenario (19.87 s vs. 20.44 s and 20.11 s, respectively).

Statistical Assessment of Electric Shock Hazard in MV Electrical Power Substations Supplied from Networks with Non-Effectively Earthed Neutral Point

This paper focuses on the evaluation of the electric shock hazard accompanying earth faults in a non-effectively earthed medium-voltage (MV) electrical power network. This hazard depends on the duration and value of the fault current. While the fault current depends on several factors, the most important is the neutral point earthing method. The value of the fault current affects the earthing-electrode voltage value, being the basis for the assessment of electric shock hazard in MV/LV substations. The earthing-electrode voltage is also influenced by the resistance of the substation earthing, which in practice is random. Therefore, an original statistical evaluation method for assessing the electric shock hazard has been developed and presented in this paper. It is based on a statistical model of the MV/LV substation earthing resistance, worked out on the basis of experiments and measurements in real electrical power networks. This method can be used for the determination of statistical distributions of earthing-conductor voltages in real electrical power networks, and on this basis, the MV/LV substations with rates of electric shock hazard that are too high can be indicated. This also makes it possible to determine the longest permissible fault current interruption times or the highest permissible earthing resistances for specific substations. This method is also applicable when selecting the neutral point earthing method. The developed method was used in all of the above proposed areas by performing calculations on a model of a real 15 kV network with the neutral point earthed by a resistor. This analysis proves the practicability of the method both at the stage of designing power networks, and when a change in the neutral point earthing method in existing networks is being considered. Particularly valuable is also the statistical model of an earthing electrode resistance, developed on the basis of measurements in 2408 MV/LV substations, which may also be applicable in the future studies.

Forecasting of voltage disturbances at the beginning of ferroresonance phenomena in power systems using by a new approach of long-short term memory (LSTM): LSTM for Ferroresonance in power systems

Ferroresonance is an unexpected, continuous, and undesirable event that causes excessive growth and distortion in the voltage and current waveform, whose cause is unknown and suddenly develops in power systems. To take precautions against the ferroresonance phenomenon, it is necessary to be able to predict how the distortions in the ferroresonance voltage will continue. Today, the ferroresonance problem has not been fully solved yet and more scientific studies are still needed. In this study, a new approach of an LSTM network has been developed that predicts the irregular and excessively large-amplitude continuing behavioral disturbances of the phase voltage in a real electrical power network exposed to ferroresonance. As a result of the study, the ferroresonance-voltage continuing in distorted waveform was estimated with an error of 0.0346 according to the Mean Absolute Percent Error (MAPE). The training data used in the study is only about 5% of all predicted ferroresonance voltage data. The successful estimation of 95% of the Ferreroresonance voltage using only about 5%, proves the success of the LSTM model applied with a new approach for the study.

Chu and Beasley Genetic Algorithm to Solve the Transmission Network Expansion Planning Problem Considering Active Power Losses

Due to the accelerated growth of electricity demand, the scarcity of primary resources to produce electricity, and technological advances in recent years, electricity companies must face and solve these challenges in the best possible way, and for that, the Transmission Network Expansion Planning (TNEP) plays a crucial role, since the decisions taken in longterm planning determine the optimal form of expansion of the networks, to respond to these needs of electricity demands. On the other hand, there is also the tendency to leave the TNEP problem more efficient, robust, and closer to what happens in real electrical networks. For these reasons, this article proposes a methodology to solve the TNEP problem considering active power losses. The problem is formulated as a mixed-integer nonlinear programming (MINLP) problem. The Chu-Beasley Genetic Algorithm (CBGA) is used to transform the MINLP problem into a linear programming (LP) problem. Furthermore, the Villasana Garver constructive heuristic (VGCH) algorithm is used to make the investment proposals made by the AGCB feasible. To measure the efficiency and effectiveness of the proposed methodology several tests are performed on the 6- bus Garver system, the IEEE 24-bus test system, and the South Brazilian 46-bus test system

Evaluación de Resiliencia en el Sistema Eléctrico Ecuatoriano frente a Eventos Sísmicos

El desencadenamiento de una serie de eventos naturales catastróficos (tales como terremotos, tsunamis, incendios forestales, tornados, etc.), han provocado que los sistemas eléctricos de potencia sean más vulnerables a sufrir daños en sus componentes, afectando así en gran medida su capacidad para suministrar energía eléctrica. En este contexto, el desafío actual de los sistemas eléctricos se centra en simular y cuantificar el impacto de los diversos eventos catastróficos considerando su aleatoriedad de ocurrencia y alta complejidad. El presente trabajo propone una metodología para evaluar el impacto sísmico en un sistema eléctrico real, usando simulaciones de Monte Carlo para determinar la vulnerabilidad de los componentes del sistema, incorporando un modelo DC-OPF con el objetivo de obtener los flujos óptimos de potencia activa y cuantificar la energía no suministrada (ENS) del sistema. La metodología propuesta es aplicada en el Sistema Nacional Interconectado (SNI) del Ecuador para obtener indicadores y métricas que permiten evaluar la resiliencia del sistema. Los resultados de la simulación muestran la vulnerabilidad del SNI y cuantifican la degradación de la resiliencia en términos de operación e infraestructura dependiendo de la magnitud y ubicación de los eventos sísmicos.

Calculating voltage magnitudes and voltage phase angles of real electrical networks using artificial intelligence techniques

In the field of electrical network, it is necessary, under different conditions, to learn about the behavior of the system. Power Flow Analysis is the tool per excellent that allow as to make a deep study and define all quantities of each bus of the system. To determine power flow analysis there is a lot of methods, we have either numerical or intelligent techniques. Lately, researchers always work on finding intelligent methods that allow them to solve their complex problems. The goal of this article is to compare two intelligent methods that are capable of predicting quantities; Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System using real electrical networks. To do that we used few significant discrepancies. These methods are characterized by giving results in real time. To make this comparison successful, we implemented these two methods, to predict the voltage magnitudes and the voltage phase angles, on two Moroccan electrical networks. The results of the comparison show that the method of Adaptive Neuro-Fuzzy Inference System have more advantages than the method of Artificial Neural Network.

Spatial and temporal flexibility assessment in distribution network

In this study, a spatial and temporal flexibility assessment (FA) procedure in a distribution network is presented by taking into account the voltage drop and lines’ loading. Subsequent to the power increase due to a connection requirement is the proportional voltage drop change that determinates the final power allowed for the technical limitations – voltage limit and loading capacity. A generally applicable FA procedure is presented that is tested in a part of a real Slovene electric power distribution network. The used approach shows the additional power that can be injected in a network node without technical violations, that is, the critical consumption power to serve as a secure-power supply buffer. To further allocate power, a flexibility profile must be applied with а required flexible power and duration. The results show the practical execution of the proposed procedure in finding the scope of flexibility power, the temporal duration and the frequency of occurrence. The output helps the distribution network operator to fast-screen the additional power connection request and postpones network investments based on the need to execute and apply flexibility. Moreover, the procedure presented can be used to offer limitation plans or flexibility prioritisation schemes to market stakeholders.

Radial basis function for fast voltage stability assessment using Phasor Measurement Units

A simple method, based on Machine Learning Radial Basis Functions, RBF, is developed for estimating voltage stability margins in power systems. A reduced set of magnitude and angles of bus voltage phasors is used as input. Observability optimization technique for locating Phasor Measurement Units, PMUs, is applied. A RBF is designed and used for fast calculation of voltage stability margins for online applications with PMUs. The method allows estimating active local and global power margins in normal operation and under contingencies. Optimized placement of PMUs leads to a minimum number of these devices to estimate the margins, but is shown that it is not a matter of PMUs quantity but of PMUs location for decreasing training time or having success in estimation convergence. Compared with previous work, the most significant enhancement is that our RBF learns from PMU data. To test the proposed method, validations in the IEEE 14-bus system and in a real electrical network are done.

TO ASSESS THE POSSIBILITY OF ENSURING THE QUALITY OF ELECTRICITY IN TERMS OF VOLTAGE DEVIATIONS OF CONSUMERS

The article deals with the issue of assessing the possibility of ensuring the quality of electricity in terms of voltage deviation by consumers. The analysis of the characteristics of modern markets, energy and power. It is revealed that the transition of the new market economy is left without the possibility of regulating the voltage consumers, which are parties to retail markets. The order of an assessment of possibility of providing the required quality of the electric power on conclusions of electric receivers is offered and its realization on the example of real electric networks is shown. Recommendations were developed to address the problem of voltage regulation at the consumer.

Criticality Analysis for Network Utilities Asset Management

The proposed work describes the main part of asset criticality analysis for Distribution Network Services Providers (DNSP), also known as Network Utilities, the severity-value factors definition. The methodology is based on the risk-based evaluation of assets, considering potential impacts of their failures on network value. Thus, it provides the capability to take maintenance management decision in terms of value and risk, considering the whole network under unique and homogeneous criteria. A hierarchy of assets ranked according to with value and risk will come out of this process, which represents a fundamental result serving as input of the subsequent steps of the asset management process. Specific attention is paid to network utilities issues, characterizing assets in these companies, and the services that they provide. In addition to this, high requirements established by the Service Level Agreements (SLA), that are characteristics of network services contracts, make this methodology especially suitable in this application. In order to illustrate method applicability, an example extracted from a real electrical network use case is included.

Testing of Peltier current leads used in real electrical superconducting network

Peltier current leads (PCLs) for high-temperature superconducting (HTS) DC applications can significantly reduce heat load on the cryogenic systems and increase overall performance of the HTS equipment. In order to investigate their operational properties in real electrical network for the first time, 144 PCLs developed in Chubu University were mounted at the terminals of 500-meter long HTS DC cable facility in Ishikari, Japan. Real-time data acquisition system monitoring a large amount of data allowed us to analysis of the PCL array operation both in idle mode and under the load of up to 6 kA per cable.

Dispatching Stochastic Heterogeneous Resources Accounting for Grid and Battery Losses

We compute an optimal day-ahead dispatch plan for distribution networks with stochastic resources and batteries, while accounting for grid and battery losses. We formulate and solve a scenario-based AC Optimal Power Flow (OPF), which is by construction non-convex. We explain why the existing relaxation methods do not apply and we propose a novel iterative scheme, corrected DistFlow (CoDistFlow), to solve the scenario-based AC OPF problem in radial networks. It uses a modified branch flow model for radial networks with angle relaxation that accounts for line shunt capacitances. At each step, it solves a convex problem based on a modified DistFlow OPF with correction terms for line losses and node voltages. Then, it updates the correction terms using the results of a full load flow. We prove that under a mild condition, a fixed point of CoDistFlow provides an exact solution to the full AC power flow equations. We propose treating battery losses similarly to grid losses by using a single-port electrical equivalent instead of battery efficiencies. We evaluate the performance of the proposed scheme in a simple and real electrical networks. We conclude that grid and battery losses affect the feasibility of the day-ahead dispatch plan and show how CoDistFlow can handle them correctly.

Assessing Impact of Renewable Energy Integration on System Strength Using Site-Dependent Short Circuit Ratio

The increasing penetration of renewable energy sources (RESs) can challenge both power system planners and operators to maintain system reliability. Potential power system stability issues may arise when a large amount of RESs are connected to a weak power system. The short-circuit ratio (SCR) with some modifications has been used to analyze power system strength. However, the existing SCR-based methods for system strength assessment neglect real electrical network connections among multiple RESs, which may not reflect the effect of the interactions among multiple RESs at different sites on system strength. To account for the interactions among electrically interconnected RESs, the so-called site-dependent SCR (SDSCR) is proposed in this paper by analyzing the relationship between system strength and voltage stability. The efficacy of the proposed SDSCR is demonstrated through numerical simulation case studies on the IEEE 39-bus system.

Measurement and detection of voltage dips and swells in power circuits

The different power quality phenomena may have characteristics quite different from each other in terms of amplitude, duration, repetition, effects on the system elements, perception of users, etc. Events like interruptions and voltage dips and swells are characterized as phenomena where the root mean square (rms) value of the supply voltage falls below or rises above a prefixed threshold. Description of three-phase measurement device for detecting voltage dips and swells in electric power network is given in this paper. The device has been tested on a real electric power network and practical results of measurement are given.

Optimal sizing and placement of rooftop solar photovoltaic at Kabul city real distribution network

Renewable energy resources (RERs) such as wind and solar are said to be considerable promising of the power system worldwide, and Afghanistan is evaluated for abundant and feasible electricity generation capacity from these resources. It fortifies merging of RER to the electric power system of Afghanistan where power quality issue sums up with scheduled and unscheduled load shedding due to the shortage of electricity. This research study presents an optimal solution comprising of rooftop solar photovoltaic (PV) as distributed generation to a real and substantial 162-bus electric distribution network (EDN) in Kabul, the capital of Afghanistan. Genetic algorithm (GA) based on Newton-Raphson power flow with the objective of power loss minimisation is put forward for sizing and placement of the solar PV at practically available locations or candidate buses of the network. This approach tends to reduce the dependency on the import power and at the same time improves the performance of the current system through minimisation of the total power loss and voltage deviation. The proposed method is simulated by MATLAB ® software to compare and demonstrate the performance of the system under different scenarios of the PV allocations.

Analysis of probabilistic load flow using point estimation method to evaluate the quantiles of electrical networks state variables

The objective of the study is to provide a clear and comprehensive analysis of probabilistic load flow (PLF) using the point estimation method, and its accuracy in the evaluation of the quantiles of the state variables of real electrical distribution networks. The three-points estimation method (TPEM) has been implemented to evaluate the first four moments of output variables (voltages, currents, and active power flows), and several methods to reconstruct the probability density function from moments and calculate the quantiles have been compared, including generalised lambda distribution and Gram–Charlier development. Monte Carlo PLF has been taken as reference to evaluate the accuracy of aforementioned TPEM results and the scope of application of the method in a real electrical distribution system.

Probabilistic assessment of power system mode with a varying degree of wind sources integration

At present among renewable sources the wind and solar plants have the most significant portion of power generation. Randomly changing and intermittent nature of this power leads to the stochasticity of the power grid mode, estimation of parameters of which requires application of probabilistic modeling. In the paper it is proposed an advanced algorithm of probabilistic load flow based on the development of two-point estimation method, the efficiency of which is confirmed on the basis of computational experiments and comparative analysis of the Monte Carlo simulation results. Calculations and analysis of the modeling results were carried out on standard 14-nodal scheme of IEEE and real electrical network of “Azerenerji” Grid.