Power Network Reliability Research Articles

Intelligent optimal sitting and sizing of distributed resources in presence of renewable energy and fuel cells based on reliability and emission factors

As the integration of renewable energy sources—such as wind, solar, and fuel cells—into power systems increases, challenges related to system reliability and cost efficiency become paramount. This paper examines the reliability of a standard power network composed of diverse energy sources including wind turbines, solar panels, fuel cells, batteries, and diesel generators. This paper proposes a novel hybrid optimization approach utilizing a Grey Wolf Optimizer combined with another advanced algorithm to minimize the total cost of energy production, inclusive of emission penalties for CO2, NO2, and SO2. The proposed approach is tested on IEEE 57-bus and IEEE 118-bus systems, demonstrating significant improvements over existing algorithms. Quantitative results show that our method reduces the total cost by up to 18 % and enhances system reliability by reducing voltage deviations in various scenarios by 12 %. The paper also provides insights into the optimal sizing and placement of wind turbines, photovoltaics, diesel generators, and fuel cells under different emission constraints (15000, 25000, and 45000 kg), further emphasizing the flexibility and effectiveness of our method in addressing environmental and economic challenges in modern power systems.

Predicting propeller emergence severity in adverse sea conditions: An integrated approach using stacked machine learning models

In adverse sea conditions, variations in the propeller submergence depth can induce ventilation and out-of-water effects. These effects result in propeller-torque and thrust losses, impacting the shipboard power network's reliability and accelerate wear on propulsion shaft system. Ensuring the stability and safety of sailing ships necessitates predicting the occurrence and severity of ventilation and out-of-water effects. This, in turn, enables the implementation of a switching strategy with a fast response for propulsion control. Nonetheless, existing methods can only identify current propeller ventilation states, mainly categorised as ventilation and non-ventilation, or more elaborately, as full ventilation, partial ventilation and non-ventilation. These methods, however, face a critical limitation—they cannot predict the severity of ventilation or the out-of-water effect, leading to ineffective propulsion-control-strategy switching. This study proposes a method for predicting propeller emergence severity (that is, non-emergence, light emergence and severe emergence) under wave conditions. This method introduces a novel approach for establishing propeller emergence states and a sophisticated stacked model. The new method categorises different propeller emergence states for diverse classifications based on the maximum emergence severity that the propeller can develop. This to overcome the challenges in predicting the development of the ventilation severity and the out-of-water effect. The innovative stacked model helps improve the overall prediction performance of a single intelligent algorithm. Finally, using simulation experimental data, it is verified that the propeller emergence severity method has satisfactory effectiveness and accuracy. The proposed method provides crucial technical support for the efficient switching of propulsion control strategies in electric propulsion systems when ships are navigating under adverse sea conditions.

Impact of Fault Resistance on Distance Relaying of Ahoada-Yenagoa Transmission Line Using Neplan

Relay protection schemes play a vital part in guaranteeing reliability and integrity of electrical power networks by promptly detecting and isolating faults in the transmission network. Fault resistance encountered during a fault event, is a crucial parameter that significantly influences the effectiveness of relay protection systems. This paper investigates the performance of a distance relying system under different fault resistance using NEPLAN software environment on a 46-km Ahoada to Yenagoa transmission line. The performance of the distance protection relaying system under single line to ground (SLG) at 80% of the transmission line with fault resistances of 0.65Ω and 2.9Ω was modeled and analyzed using NEPLAN. From our investigation, the result reveal that when a fault resistance of 0.65 Ω and 2.9 Ω was introduced in the system during a SLG at 80% of the line (zone 1), the apparent impedance seen by the relay increased from 5.475 Ω without fault resistance to 5.602Ω and 6.407 Ω respectively. The results show that for a fault resistance of 0.65 Ω, the apparent impedances (ZAPP) trajectory falls inside the impedance characteristic of zone 2 instead of zone 1 while a fault resistance of 2.9 Ω fall outside zone 2. The findings highlight the significance of fault resistance in transmission line relaying for distance protection.

A security-constrained robust optimization for energy management of active distribution networks with presence of energy storage and demand flexibility

A discernible rise in the frequency and intensity of unpredictable events and their significant social and economic effects have made power system planners pay special attention to the security and reliability of power networks. For this purpose, this article tries to provide an efficient model for strengthening the security of active distribution networks based on multiple microgrids by optimally using energy storage resources and consumption management plans. In the proposed plan, a hierarchical two-stage approach has been developed in which the first stage models the incident and their impact on the distribution network. Then, in the next stage, preventive and corrective measures are implemented to increase system readiness and reduce damages caused by severe accidents. At this stage, various tools such as energy storage, distributed and renewable production sources have been used in addition to responsive loads. In the corrective phase, the independent microgrid partitioning method is used to restore the distribution network to increase the speed of load pickup process. In order to consider the uncertainty and the risk caused by events on the performance of the proposed plan, the problem is done by robust optimization to obtain more realistic results. Finally, in order to confirm the effectiveness of the proposed method in improving the security of distribution systems, a standard network of 33 buses was used with different operating conditions. The results confirm that the proposed security-constrained robust optimization plan not only reduces system operating costs, but also improves consumer security in the face of severe accidents. Although the increase in network security is associated with a slight increase in system costs, the benefit of reducing outages and optimal use of network capacity has led to the effectiveness of the proposed plan.

A Curve Fitting–Based Directional Protection of Transmission Lines Using Genetic Programing

In modern power systems, there is a growing need for protection techniques that are fast, precise, and stable to enhance the reliability and stability of power networks. This paper introduces an advanced technique for fault direction estimation that addresses key limitations in existing methods. Our proposed algorithm eliminates the dead‐zone issue, effectively handling both forward and reverse faults regardless of their location, including faults near relay regions. Using genetic programing (GP), we derive a closed‐form equation to drive the fault direction estimation algorithm, ensuring accurate and reliable results. The algorithm demonstrates exceptional speed and reliability in fault detection and direction estimation, even under challenging conditions such as current transformer (CT) saturation, power swing, and source strength variations. It is also insensitive to fault resistance and fault inception angle, increasing its robustness. A notable advantage of this algorithm is its efficiency at low sampling frequencies, making it highly adaptable for industrial applications and compatible with modern software and hardware requirements. We validated the algorithm through simulations on the electromagnetic transients program (EMTP‐RV) platform and with field data from the Manesht 230 kV substation in Ilam province, Iran. The results confirm the algorithm’s impressive speed and high reliability.

Internet of Things (IOT) Based Machine Learning Techniques for Wind Energy Harvesting

The Internet of Things (IoT) is a significant avenue for research in renewable energy, particularly in enhancing windmill performance, reducing wind energy costs, and mitigating risks in wind power. This article concentrates on leveraging IoT for assessing wind and solar energy, as well as estimating module lifespans. IoT has improved assessment methods, monitoring precision, and product testing, influencing power network reliability and inventory management in green energy. Predicting green energy output is crucial but challenging due to wind speed fluctuations. Machine learning (ML) techniques are applied to predict wind-based electricity output, with a comparative evaluation of forecasting methods. IoT technologies and algorithms enable energy consumption forecasts, yielding more accurate predictions and lower root mean square error (RMSE). Accurate meteorological forecasts are paramount in the green energy sector, necessitating predictive models for authentic wind generator data. The research aims to develop technologies for precise forecasts, with a focus on comprehensive wind forecast algorithms for photovoltaic systems. Various ML techniques and green energy prediction software are assessed for their accuracy in this endeavor.

Examination of Gas Active Arc Extinguishing and Lightning Protection for Transmission Lines

The study investigated the gas active arc extinguishing and lightning protection for transmission lines. Lightning is one of the most significant sources of over voltages in overhead transmission lines. The lightning over voltages could lead to failure of the devices connected to the transmission line. Fundamental constraint on the reliability of an electrical power transmission system is the effectiveness of its protective system. The role of the protective system is to safeguard transmission system components from the effects of electrical overstress. Shield wire and surge arresters are an important means of lightning protection in transmission and distribution systems. Therefore, it is necessary to analyze the influence of over voltages caused due to lighting. The requirements of system security for lightning protection technology reach the high standard that lightning strike tripping and wire breakage are not allowed. Both the power supply side and the demand side have very high requirements for lightning protection of transmission lines, but the lightning accident rate remains high. This situation poses a great threat to the reliability and safety of power network, it is urgent to solve this problem. The gas active interrupter principle is put forward. From two latitudes of lightning overvoltage and power frequency over current, the effective control of lightning accident rate caused by large probability and multiple lightning strike is realized. This paper is aimed at evaluation of protection level of transmission line by using gas active arc extinguishing, shield wire and line surge arresters against lightning overvoltage. When lightning strikes, the internal short gap of the main body and the air gap break down, and the lightning arc enters the arc-extinguishing body through the breakdown channel. Arc is compressed by force to form internal and external gradients temperature in order to produce jet airflow. Jet airflow acts on the subsequent power frequency follow current arc, a model coupling an arc and a compressed jet airflow in a multi-fracture compression airflow arc-extinguishing structure is established and simulated. The increase in voltage due to lightning are investigated by using the MATLAB software. Direct and induced, types of lightning strokes are considered. The model of a 33kV three-phase overhead power transmission line is developed considering the RL circuit. The simulations are performed based on time domain analysis. Also, numerical analysis is made for 133kV tower structure transmitting power over 220km from 132 KV Sub-transmission Lines in port Harcourt region. Based on the simulation study this research study gas active arc extinguishing and lightning protection for transmission lines, are very important in computer application like Electromagnetic Transient Propagation (EMTP) and Power System Computer Aided Design (PSCAD) which are used in future study. These soft wares provide an alternative way to bring the precise result in study of lightning protection level of high voltage transmission line.

Measurement and Identification of Partial Discharge in 11kV XLPE Cable Jointing

The reliability of power networks can be compromised by failures in cable connections, which are often caused by poor insulation quality. The use of different insulating materials during the connection process can result in defects, leading to partial discharge (PD) in high voltage equipment. PD measurements using a Rogowski Coil sensor and a high-efficiency Oscilloscope, following the IEC-60270 guidelines, are a widely recognized method for evaluating the quality of insulation systems. Experimental measurement was performed at university high voltage laboratory. This paper focuses on measuring PDs in extension (joint) cables, where they typically occur, specifically in 11kV XLPE jointing cables, and comparing them with ordinary cables without jointing. The project aims to analyze PD signal characteristics and identify partial discharge patterns in the time and frequency domains using MATLAB. .

SWSN3: A simulation tool for reliability calculation in WSN

Knowledge about the reliability of a wireless sensor network is important in industry. Indeed, in holonic manufacturing, it is convenient to ensure that decisions are made with reliable data. However, experimental evaluation in a real environment is a task that consumes time and financial resources, it also depends on several factors such as the technical characteristics of the transceiver and the location of the nodes. Thus, the use of simulation and calculation software in Industry 4.0 can potentially reduce costs and implementation time significantly, nonetheless some simulators deal with power consumption and network reliability with theoretical models that have limitations for commercial devices. This paper presents the sWSN3 tool that, through an intuitive graphical interface allows placing sensor nodes on the virtual environment of a plant layout and calculates the reliability of a wireless sensor network using parameters such as signal to noise ratio, received packet rate, and battery life time. Results show that sWSN3 can accurately estimate the reliability of a virtual WSN.

High Impedance Fault Detection Protection Scheme for Power Distribution Systems

Protection schemes are used in safe-guarding and ensuring the reliability of an electrical power network. Developing an effective protection scheme for high impedance fault (HIF) detection remains a challenge in research for protection engineers. The development of an HIF detection scheme has been a subject of interest for many decades and several methods have been proposed to find an optimal solution. The conventional current-based methods have technical limitations to effectively detect and minimize the impact of HIF. This paper presents a protection scheme based on signal processing and machine learning techniques to detect HIF. The scheme employs the discrete wavelet transform (DWT) for signal decomposition and feature extraction and uses the support vector machine (SVM) classifier to effectively detect the HIF. In addition, the decision tree (DT) classifier is implemented to validate the proposed scheme. A practical experiment was conducted to verify the efficiency of the method. The classification results obtained from the scheme indicated an accuracy level of 97.6% and 87% for the simulation and experimental setups. Furthermore, we tested the neural network (NN) and decision tree (DT) classifiers to further validate the proposed method.

An Analysis of Influence of Network Topology on Power Network Reliability Based on OPLC

Optical fiber to the home (PFTTH) is an access network technology, which uses optical fiber composite low voltage cable (OPLC) to realize the deep integration of the power grid and communication network infrastructure. Key technologies include network structure design and high-speed access technology, PON technology, and the OPLC technology. This paper introduces the key technologies of power fiber-to-home networking and the influence of network topology on the reliability of PFTTH.

A-star algorithm based on admissible searching for strategically placing PMU considering redundancy and cost/benefit analysis

This research examines an admissible search algorithm-dependent A-star strategy and takes into account redundancy and cost/benefit analysis under normal operating conditions. The goal is to allocate a phasor measurement unit (PMU) for maximal observability of the interconnected power network. To determine the fewest number of PMU required to make the connected power network totally observable using redundancy analysis, the A-star approach is utilized. The redundancy analysis of the power network is carried out in order to determine the appropriate PMU placement, which results in the acquisition of total power network observability and reliability. To put the suggested technique through its paces, it has been tested on IEEE-standard test systems such as IEEE-14 bus, IEEE-30 bus, New England-39 bus, IEEE-57 bus, and IEEE-118 bus. The results obtained using the suggested methodology are compared to those obtained through standard literature research. The experimental findings of the suggested method revealed the resilience and accuracy of the A-star algorithm as well as its effectiveness in achieving maximum observability of the connected power network.

Partial discharge localization in power transformers using acoustic time reversal

The localization of partial discharges (PD) is important to monitor the conditioning of high voltage insulator materials. One of the key components in power grids is the high power transformer. Localization of PDs in these pieces of equipment can increase the reliability of power networks. One of the most commonly used methods to localize PDs is the time difference of arrival (TDoA) technique. Recently, time reversal (TR) techniques in the electromagnetic regime have been proposed to localize PD sources with a lower number of needed sensors compared to the TDoA technique. Contrary to TDoA, TR-based techniques do not need line-of-sight wave propagation from PD sources to the sensor(s). In this study, we extend the TR technique to localize PD sources in the acoustic regime for three-dimensional structures. Similar to the electromagnetic TR methods, a typical time reversal process includes three steps: 1) record the acoustic fields caused by a PD source using at least one sensor, 2) time reverse and back inject into the medium the recorded acoustic signal(s), 3) use a proper criterion to obtain the focusing point associated with the location of the PD source. The acoustic TR technique presented in this paper uses only one sensor. Numerical simulations are used to evaluate the performance of the acoustic TR technique for three-dimensional power transformer models. To do this, an open source MATLAB toolbox is used to solve the acoustic wave equation. The numerical results show that the TR technique can accurately localize the PD sources in three-dimensional power transformer models. Our analysis shows that the presence of windings inside the transformer tank does not degrade the efficiency of the acoustic TR technique.

Increasing Electric Vehicle Penetration Using Smart Switching and Emergency Uprating

One of the key challenges facing distribution network operators today is the expected increase in electric vehicles. The increased load from EV charging will result in distribution assets becoming “thermally overloaded” due to higher operating temperatures. In addition to the issue of increased load, we have a limited understanding of the behavior and performance of the distribution assets and their potential to accept the increased load. It has been well acknowledged that EVs increase the network loading level, leading to a reduced system reliability performance. These results have not been quantified in a realistic case study, including actual cable rating and design properties. To address this gap, this paper proposes a novel methodology in the existing power network reliability evaluation framework, which quantifies the impact of different EV penetration levels on distribution network reliability, and the thermal performance of distribution cables. Novel approaches using smart switching technology and emergency uprating are proposed to reduce the peak power demand caused by EVs, in order to reinforce the reliability of the grid and to boost the maximum allowable EV penetration in the distribution networks. The methodology was applied using a case study on the modified EV-integrated RBTS (Roy Billinton Test System) bus four distribution network. The results showed that the negative impact of EVs on network performance can be mitigated by the implementation of smart switching technology. The peak demand under contingencies can also be accepted by the cables though emergency uprating. The frequency and duration of EV demand interruption was also significantly reduced. Thus, a higher EV penetration can be accommodated.

Impact of installing renewable energy sources on a small-scale power network in the Caribbean

Many small island states in the Caribbean like Antigua and Barbuda depend heavily on petroleum-based products for power generation. Given the fluctuating oil prices, there is now an urgent push for increased energy security. Antigua is one of the fastest-growing islands for grid-connected Renewable Energy Sources (RES). Whilst the increase in grid-connected RES improves the islands’ energy security, and it is equally important to understand the impact that RES have on the network’s reliability and security. Thus, a base case model of the power network was built, and the following areas were analysed: load flow, contingency analysis, and fault analysis. The Antigua Public Utilities Authority (APUA) 69kV power network is used as a case study for this project. PowerWorld and Homer Energy software have been used to simulate and model the grid. Results from the project show that RES changes the power flow and could help to improve the system voltage profile if placed correctly. Whilst increased penetration of Wind Turbine Generators (WTG) on the grid increases the system fault levels, they also play a key role in active and reactive power control. This means that the APUA network must be more flexible, and system operators must have network visibility to react to changes on the network. The aim of this paper is to investigate the impact that RES (in particular, wind and solar PV) has on the operational, security, or reliability of a small-scale power network.

SAMP-RPL: secure and adaptive multipath RPL for enhanced security and reliability in heterogeneous IoT-connected low power and lossy networks

The Internet of things (IoT) is made up of huge sets of networked low-power devices. Regardless of the application specificities, those devices are generally tasked to provide highly important services that can be reached out through the internet. Communications with IoT networks cannot be achieved without the support of efficient underlying routing schemes. However, the constraints related to scarce resources, as well as the wireless and lossy nature of IoT networks may tremendously affect the communications reliability. Consequently, routing efficiency could be affected. Moreover, the exposure to internal and external cyber-attacks, especially those that threaten data and service availability, complicates even further routing and security missions in such a constrained context. In this paper, we propose an efficient solution that enhances both the communications reliability and security in the heterogeneous IoT-enabled low power and lossy networks. The solution relies on three variants of adaptive and secure multipath routing for IPv6 routing protocol for low-power and lossy networks (RPL). To the best of our knowledge, this is the first solution that deals with multipath routing security issue for RPL protocol, in IoT contexts. The proposed solution is evaluated with Cooja simulator of Contiki OS. The assessment results show obviously the effectiveness of the proposed solution for improved communication reliability and security, at low costs.

Temperature self-regulating electrothermal pseudo-slippery surface for anti-icing

Ice accretion has become an urgent problem and considerably decreases the reliability of aerospace, power network, and transportation equipment. Herein, a temperature self-regulating electrothermal pseudo-slippery surface with intelligent anti-icing ability was introduced by combining electrothermal effect and phase transition lubricant, which exhibits positive temperature coefficient (PTC) effect and interfacial state switching performance. The coating exerts its PTC effect to realize smart temperature accommodation, and automatically regulates its EPD for anti-icing under various cold loads, greatly decreasing the energy consumption of anti-icing by ~ 30% at an initial electric power density of 1.5 W/cm2 (compared with general electrothermal coating) and preventing overheating even at an initial electric power density of 5 W/cm2 without requiring complex regulatory equipment. After heating, the reversible solid to liquid phase transition of the lubricant assisted the switch from pseudo-slippage to slippage of the surface, decreasing ice accretion on the coating (by ~ 40% after icing for 120 s at –40 ± 3 °C). Furthermore, the mechanical function of PTC–ESS was highly stable in continuous humid airflow/sand scour tests. The integration strategy will provide inspiration for designing intelligent anti-icing surfaces and promote their engineering applications.

Distributed model predictive control for joint coordination of demand response and optimal power flow with renewables in smart grid

Demand response is an emerging application of smart grid in exploiting timely interactions between utilities and their customers to improve the reliability and sustainability of power networks. This paper investigates the joint coordination of demand response and AC optimal power flow with curtailment of renewable energy resources to not only save the total amount of power generation costs, renewable energy curtailment costs and price-elastic demand costs but also manage the fluctuation of the overall power load under various types of demand response constraints and grid operational constraints. Its online implementation is very challenging since the future power demand is unpredictable with unknown statistics. Centralized and distributed model predictive control (CMPC and DMPC)-based methods are respectively proposed for the centralized and distributed computation of the online scheduling problem. The CMPC can provide a baseline solution for the DMPC. The DMPC is quite challenging that invokes distributed computation of a nonconvex optimization problem at each time slot. A novel alternating direction method of multipliers (ADMM)-based DMPC algorithm is proposed for this challenging DMPC. It involves an iterative subroutine computation during the update procedure of primal variables that can efficiently handle the difficult nonconvex constraints. Comprehensive experiments have been conducted to test the proposed methods. Simulation results show that the gap in objective values between the DMPC and its baseline counterpart (CMPC) are all within 1%, further verifying the effectiveness of the proposed ADMM-based DMPC algorithm.

Grid Island Energy Transition Scenarios Assessment Through Network Reliability and Power Flow Analysis

This paper presents a methodology for the reliability and power flow analysis of islands or off-grid power networks for situations of scarce data and information. It offers a new and pragmatic approach to derive the required power network information, including the power cable parameters and the load at each power node. The paper aims to present the developed methodology, and to illustrate its application, using Ushant Island as a case study. The assessment of the current power network status and the reliability analysis are presented. Grid performance parameters are further compared for conventional diesel generator operation and renewable energy generation scenarios, demonstrating the advantages of replacing the existing diesel units with renewable energy sources in terms of system reliability. The analysis shows that by introducing renewable energy systems to the island’s grid, the reliability of the grid increases by up to 50% and cable capacity usage reduces by up to 30%. Furthermore, this work suggests that it would not be necessary to modify the grid cables when substituting the diesel generator. The paper will be of interest to network planners, community stakeholders, project developers and decision-makers concerned with renewable energy investment on islands and in remote rural areas.

Analysis and design of energy storage capacity of AC-DC hybrid power distribution unit with energy storage to improve the reliability of power grid

Based on the development of AC-DC distribution network, a new AC-DC distribution device with energy storage structure is designed in this paper. This paper first analyzes the existing AC-DC power distribution equipment and network reliability assessment methods. On this basis, the design is put forward, the energy storage link is placed at the DC high voltage side. The constraints of energy storage as an critical load backup power supply are defined and the mathematical model is established. In this paper the timing Monte Carlo method is used to calculate the reliability of the device and the power grid. The model in this paper can be applied to a variety of distribution network structure and energy storage scenarios, with high accuracy. It is concluded that the AC-DC distribution unit has remarkable effect in improving reliability.