Grid Failure Research Articles

Emergency Dispatch Strategy Considering Spatiotemporal Evolution of Power Grid Failures Under Typhoon Conditions

The increasing climate-change-induced tropical cyclone phenomena expose the power grid to significant operation risks by disrupting the normal operation of grid components. This paper considers the failure mechanism with respect to critical grid components and reveals a novel spatiotemporal revolution of grid failures during the passage of typhoons. Based on the spatiotemporal evolution of grid failures, a threshold-based emergency scenario set and the corresponding two-stage robust optimization-based emergency dispatch model are developed. The robust emergency dispatch strategy is obtained using a column-and-constraint generation (C&CG) algorithm. The simulation results show that the proposed robust emergency dispatch strategy can guarantee a considerable degree of robustness under multiple emergency scenarios driven by uncertain typhoon conditions.

The impact of North American winter weather regimes on electricity load in the central United States

AbstractExtreme wintertime cold in the central United States (US) can drive excessive electricity demand and grid failures, with substantial socioeconomic effects. Predicting cold-induced demand surges is relatively understudied, especially on the subseasonal-to-seasonal (S2S) timescale of 2 weeks to 2 months. North American winter weather regimes are atmospheric tools that are based on persistent atmospheric circulation patterns, and have been linked to potential S2S predictability of extreme cold in the central US. We study the relationship between winter weather regimes and daily peak load across 13 balancing authorities in the Southwest Power Pool. Anomalous ridging across Alaska, the West Coast, and Greenland drive increases in demand and extreme demand risk. Conversely, anomalous troughing across the Arctic and North Pacific reduces extreme demand risk. Thus, weather regimes may not only be an important long-lead predictor for North American electricity load, but potentially a useful tool for end users and stakeholders.

An investigation on NGR failure in Indian smart cities while replacing the existing overhead lines by underground cables

Abstract Nowadays, Indian power distribution companies (PDCs) are implementing smart distribution networks. Older cities are becoming smarter as per the recent government’s policy. Existing overhead distribution lines are being replaced by underground cables as an essential criterion of a smart city. One of the main problems arising in this process is the overheating of the neutral grounding resistor (NGR) in 11 kV distribution systems, even in normal conditions. NGRs, placed inside the substations, are overloading the air conditioning and exhaust systems of the substation. Sometimes failure of the NGR occurs due to overheating. In this paper, a comprehensive investigation has been carried out to reach the roots of this problem. It is observed that long underground cables have a higher ground capacitance than overhead distribution lines. Due to the higher cable capacitance, the third harmonic current circulates through neutral, which overheats the NGR even in normal conditions. The situation becomes worse when the substation runs on diesel generators (DGs) in an isolated state under main grid failure, as a higher amount of third-harmonic current circulates depending on the type of winding and pitch factor of the DGs. Different solutions are proposed, and their advantages and disadvantages are analyzed. Finally, the rating of the NGR is modified, and louvers-cooling fan arrangement is preferred for the running substation.

Strategic optimization of PV integrated fuel cell systems for energy surplus utilization in grid failure scenarios

Effective energy management in grid-connected renewable energy systems is essential for achieving cost-efficiency and reliability. This work presents a versatile control technique to tackle power system difficulties in grid-connected and grid-failure modes. The concept employs a digital iterative approach to optimize the operation of a DC-DC converter, guaranteeing the attainment of maximum power output and stability. During a grid breakdown, the system injects carefully adjusted active power into the grid to ensure that voltage and current levels are maintained at appropriate levels, hence preventing overloading. The proposed strategy exhibits a 99% enhancement in system responsiveness and a 96% decrease in overshoot when compared to conventional methods, thus substantiating its efficacy in practical scenarios.

IoT Systems Based Microgrid: A Review

Smart microgrids, as the foundations of the future smart grid, combine distinct Internet of Things (IoT) designs and technologies for applications that are designed to create, regulate, monitor, and protect the microgrid (MG), particularly as the IoT develops and evolves on a daily basis. A smart MG is a small grid that may operate individually or in tandem with the electric grid, and it is ideal for institutional, commercial, and industrial consumers, as well as urban and rural societies. A MG can operate in two methods (stand-alone and grid-connected), with the ability to transition between modes due to local grid faults, planned maintenance, expansions, deficits and failures in the host system, and other factors. Energy storage is the process of storing and converting energy that can be used for a variety of purposes, including voltage and frequency management, power backup, and cost optimization. IoT is designed to deliver solutions for optimal energy management, security protocols, control methods, and applications in the MG, with numerous distributed energy resources (DER) and interconnected loads. The use of IoT architecture for MG operations and controls is discussed in this research. With the use of power grid equipment and IoT-enabled technology

Dynamic load shedding and system restoration using wide area distribution management system

AbstractThe demand for electric power has consistently been on the rise, owing to urbanisation and technological improvements. On the generation side, renewable sources have been favoured over their polluting, exhaustible, non‐renewable counterparts. These changes in the power system have necessitated a system for maintaining the supply‐demand balance, to maintain system stability. A complex power system is also more prone to blackouts and grid failure. Islanding helps in provision of supply to consumers in a microgrid, reducing the possibility of a blackout. Depending on the power demand and generation, loads need to be shed or restored to mitigate power imbalances. A wide area distribution management system (WADMS) is proposed to dynamically shed and restore loads in the islanded mode, with the aid of micro phasor measurement units (µPMUs). A priority and consumer‐based load shedding and restoration (PCLS) algorithm is proposed in the WADMS that preferentially sheds or restores loads based on their assigned load priority indices and number of consumers. The algorithm has been tested on a modified IEEE 13 bus system, incorporated with a solar photovoltaic (PV) system, diesel generators (DGs) and an energy storage system (ESS) in MATLAB Simulink.

Focus on the disruption of networks and system dynamics.

Networks are designed to ensure proper functioning and sustained operability of the underlying systems. However, disruptions are generally unavoidable. Internal interactions and external environmental effects can lead to the removal of nodes or edges, resulting in unexpected collective behavior. For instance, a single failing node or removed edge may trigger a cascading failure in an electric power grid. This Focus Issue delves into recent advances in understanding the impacts of disruptions on networks and their system dynamics. The central theme is the disruption of networks and their dynamics from the perspectives of both data-driven analysis as well as modeling. Topics covered include disruptions in the dynamics of empirical systems such as nuclear reaction networks, infrastructure networks, social networks, epidemics, brain dynamics, and physiology. Emphasis is placed on various phenomena in collective behavior, including critical phase transitions, irregular collective dynamics, complex patterns of synchrony and asynchrony, chimera states, and anomalous oscillations. The tools used for these studies include control theory, diffusion processes, stochastic processes, and network theory. This collection offers an exciting addition to the evolving landscape of network disruption research.

Design and Implementation of Crowbar and STATCOM for Enhanced Stability of Grid-Tied Doubly Fed Induction Wind Generators

These days, one of the most used layouts in the wind power industry is a variable-speed doubly-fed induction wind generator (DFIWG). For providing active power (P) and reactive power (Q) control during grid failures, this research examines the DFIWG. The system's transient behavior is examined under normal and abnormal circumstances. Through control of rotor side (RSC) and grid side (GSC) converters, Q assistance for the grid, and power converter stress reduction, the suggested control approach achieves system stability while enabling DFIWG to operate smoothly during grid failures. The DFIWG is exposed to three- and two-phase faults to analyze the machine's performance. The crowbar and STATCOM tools are implemented to enhance the system performance under faults and compared with the base case. The implemented tools successfully suppress rotor and stator overcurrent, over voltage at the DC link (DCL), and power oscillations, as well as supporting the grid voltage understudied cases. The obtained results prove that both STATCOM and crowbar not only enhance the system's effectiveness and performance but also enable the system to achieve the fault ride-through capacity (FRTC). MATLAB/SIMULINK 2017b is used for time-domain computer simulations.

A Fault Direction Criterion Based on Post-Fault Positive-Sequence Information for Inverter Interfaced Distributed Generators Multi-Point Grid-Connected System

In response to the poor reliability in identifying fault direction in distribution networks with Inverter Interfaced Distributed Generators (IIDGs), considering the control strategy of low-voltage ride-through, a fault direction criterion based on post-fault positive-sequence steady-state components is proposed. Firstly, the output steady-state characteristics of IIDGs considering the low-voltage ride-through capability are analyzed during grid failure, and the applicability of existing directional elements in a distribution network with IIDGs connected dispersively is demonstrated. Subsequently, for the typical structure of an active distribution grid operating under flexible modes, the positive-sequence voltage and current are examined in various fault scenarios, and a reliable direction criterion is suggested based on the difference in post-fault positive-sequence impedance angles on different sides of the lines that are suitable whether on the grid side or the IIDG side. Lastly, the reliability of the proposed direction criterion is verified by simulation and the results indicate that the fault direction can be correctly determined, whereas phase-to-phase and three-phase short circuit faults occur in different scenarios, independent of the penetration and grid-connected positions of IIDGs, fault location, and transition resistance. It is suitable for fault direction discrimination of an IIDGs multi-point grid-connected system under a flexible operation mode.

SWIRL: The First Australian Operational Radar-Based 3D Wind Analysis System

Abstract In this paper, the first Australian operational radar-based three-dimensional (3D) wind analysis system named Synthetic Wind Information from Radar and Lidar (SWIRL) is described and evaluated. SWIRL employs a variational minimization formulation to combine results from four individual wind retrieval techniques of varied complexity to derive 3D winds in single-Doppler and multi-Doppler radar regions: a variational version of the traditional velocity azimuth display (VVAD) and double VAD (DVAD) techniques, a single-Doppler wind retrieval technique using optical flow horizontal wind proxies, and a multi-Doppler 3D wind retrieval technique. The SWIRL 3D wind components are evaluated against wind profiler observations and radar simulations using a very high-resolution (50 m) numerical simulation of a supercell thunderstorm. We find that SWIRL can retrieve very accurate horizontal winds, especially below 2-km height in the multi-Doppler regions, with mean absolute errors on wind speed and direction < 2 m s−1 and 10° on average and <2.5 m s−1 and 15°–20° 90% of the time. These errors do not increase noticeably with wind speed, highlighting the suitability of these retrieved winds to be used for damaging and destructive wind detection and nowcasting. The single-Doppler retrieval using optical flow is also found to provide reasonably accurate winds at these heights. The accurate retrieval of convective-scale updrafts and downdrafts, even using multi-Doppler information, is still a major challenge, with mean absolute errors of vertical velocity of about 50% on average. This can be attributed to the limitations of the current radar technology used operationally, imposing slow antenna speeds. Significance Statement Damaging and destructive winds have the potential to inflict significant damage to properties and assets and, tragically, result in loss of life. Efficient direction of emergency services to affected areas is essential for a prompt return to normal conditions. Wind farm operators require precise information on anticipated wind shifts to reduce the risk of energy grid failures. Strong winds also contribute to compound weather events, such as water ingress through hail-damaged roofs or structural damage to buildings caused by hailstones. The purpose of this work was to equip Australia with the first operational wind monitoring system, based on operational radar observations, to serve all these critical applications (and more).

Optimization of mobile emergency resource scheduling after power grid failure based on real-time traffic flow

Optimization of mobile emergency resource scheduling after power grid failure based on real-time traffic flow

Distributed voltage unbalance mitigation in islanded microgrid using moth flame optimization and firebug swarm optimization

In recent trends, hybrid renewable energy sources (HRES) provide a better solution to meet energy demand, maximizing the productivity of electricity network. Due to the above-mentioned features, several researchers have given more attention to PV-wind-based HRES systems. A stable energy supply must be added, including batteries, diesel generator (DG), to meet demand in the event of a grid failure. To meet the voltage unbalance in islanded mode, the sizes of DG have need to be selected sensibly and HRES requires additional energy storage. To examine the voltage unbalance problems of an islanded microgrid, a hybrid optimization approach known as moth flame optimization (MFO) and firebug swarm optimization (FSO) is introduced. Due to various loads, harmonic distortion causes the voltage to unbalance, which can result in voltage collapse. To deliver a quick response in an island mode, a comprehensive algorithm called MFO-FSO control is proposed. MATLAB software is used to validate the results which demonstrate that the proposed MFO-FSO outperforms the conventional decoupling double synchronous reference frame (DDSRF) methods by reducing total harmonic distortion (THD) up to 1.21% and voltage unbalance factor (VUF) up to 1.427%.

Recent advances on control strategies for microgrid islanding operation

In order to achieve the national strategic goals of peaking carbon emissions by 2030 and achieving carbon neutrality by 2060, the electricity-energy-ecosystem is undergoing significant transformation, presenting new opportunities for the development of new energy generation technologies. With the widespread adoption of renewable energy sources, such as solar and wind energy, microgrids have begun to play a prominent role as small-scale power systems. Microgrids, as small, autonomous power systems, have received significant attention in recent years. Microgrids can enhance energy sustainability by integrating renewable energy resources and energy storage systems, while also providing the capability to maintain power supply during main grid failures or planned maintenance. This article aims to review the advances in control strategy research for microgrid islanding operation, with a focus on the classification of control strategies, design principles, and their impact on microgrid stability. The article also explores potential directions for future research to enhance the efficiency and reliability of microgrid islanding operation, providing valuable references for future studies.

A Blocking Method for Overload-Dominant Cascading Failures in Power Grid Based on Source and Load Collaborative Regulation

Adjusting generator output and cutting off load can effectively solve the problem of continuous overload and disconnection of power lines caused by power flow transfer. To suppress large-scale power outages caused by overload-dominant cascading failures, a blocking method for overload-dominant cascading failures in the power grid based on source and load collaborative regulation is proposed. The shortest path algorithm was used to identify loads and generators with shorter electrical distances from overloaded lines. Under the premise of meeting the static safety constraints of the power grid, considering the regulation of generator output and the removal of interruptible loads, a multiobjective cascading failure blocking model is established with the minimum overall control cost of the system and the minimum probability coefficient of line failure. Use the NSGA-II algorithm to solve the model and obtain the optimal plan for adjusting generator output and cutting off load. Through example verification, the proposed method can effectively alleviate the phenomenon of line overload, thereby blocking the continuation of overload-dominant cascading failures.

Axial compression performance of underwater columns reinforced with stainless steel tube-FRP grids

Stainless steel tubes have excellent plasticity and ductility, and FRP grids have favorable advantages for application in specific structural reinforcements. For systems including underwater construction without drainage, underwater columns reinforced with stainless steel tube-FRP grids are proposed using nondispersive mortar (NDM) as the reinforcement layer to best leverage the material properties of all elements. This paper carried out axial compression tests on 18 underwater columns reinforced with stainless steel tube-FRP grids (SS-FGWCs), 6 columns reinforced with stainless steel tube-FRP grids on land (SS-FGLCs), 3 underwater columns reinforced with stainless steel tubes (SSWCs), and 3 unreinforced concrete columns. The research parameters include the number of FRP grid layers, the types of FRP grids, and the reinforcement layer mortar pouring environments. The test results showed that FRP grids can be combined with stainless steel tubes (SSs) and nondispersive mortar (NDM) to reinforce concrete columns in underwater construction without drainage. In addition, compared with those of the SSWC specimens, after the BFRP grid and CFRP grid were built in, the ultimate stresses of the specimens increased by 13.4% ∼ 20.8% and 19.5% ∼ 25.4%, respectively, and the ultimate strains increased by 6.8% ∼ 31.7% and 21.8% ∼ 59.1%, respectively. Compared to BFRP grids, CFRP grids provide better reinforcement of the underwater columns. Existing prediction models were evaluated for ultimate stress calculations, the calculation methods for the ultimate stress and ultimate strain applicable to the SS-FGWCs and SS-FGLCs were revised, and a calculation model for the FRP grid failure point was proposed. Finally, a corresponding full stress–strain curve model was established.

Fault-tolerant shunt active power filter with synchronous reference frame control and self-tuning filter

This research proposes a novel method that combines Proportional-Integral (PI) control, Artificial Neural Networks (ANNs), and Synchronous Reference Frame (SRF) theory to improve the performance of a three-phase shunt Active Power Filter (APF) under fault situations. The main goal is to reduce power quality problems in electrical grids that are having problems, such harmonics and voltage sags. To precisely manage the APF, the reference frame in which the grid voltages and currents are synchronized is identified using the SRF theory. In order to provide quick and precise correction of voltage and current distortions, the PI controller is integrated to control the APF's compensatory action. The PI controller offers trustworthy control while running normally, but during errors or disruptions, its functionality may suffer. In order to overcome this difficulty, a self-tuning filter in the form of an Artificial Neural Network (ANN) is presented, which may adaptively modify the PI controller's settings under fault situations. To maintain ideal filter performance, the ANN constantly learns from the system's reaction and modifies in real-time. This self-adjusting feature makes sure that even in the event of grid failures, the APF maintains its ability to mitigate problems with power quality. The suggested method effectively reduces harmonics, voltage sags, and other power quality disturbances under both normal and fault circumstances, as shown by the simulation results. In complicated electrical grid systems, the combination of SRF theory, PI control, and ANN-based self-tuning provides a strong way to improve the dependability and effectiveness of three-phase shunt Active Power Filters.

Renewable-based microgrid energy management: A comprehensive exploration of techniques, strategies, and long-term viability

Renewable-based microgrid energy management systems have emerged as a promising solution to address energy security, sustainability and resilience concerns. This paper offers a comprehensive exploration of the techniques, strategies and long-term viability of such systems. The purpose of the study delves into the implementation of smart management and control systems, which enable real-time data analysis, grid optimization and effective load management, thus maximizing the utilization of renewable energy and enhancing overall system efficiency. It demonstrates the significance of decentralized energy management and its role in fostering energy independence and sustainability within local communities and small-scale industrial setups. The paper further investigates the resilience and redundancy aspects of microgrids, highlighting the importance of autonomous operation during grid failures and emergencies. Thus, the incorporation of energy-efficient practices, appliances and demand-side management strategies to promote energy conservation and reduce overall energy consumption of solar power, wind power, hydro power, biopower and geothermal. The important outreach and training are creating environmentally friendly energy consumption and improving the long-term sustainability of microgrid energy control systems that rely on energy generated from renewable sources. The study seeks to enhance ecological energy handling techniques and the utilization of clean sources of energy by offering knowledge regarding the promise of the microgrid to become a versatile and environmentally friendly power solution via this examination.

ANFIS controller for photovoltaic inverter transient and voltage stability enhancement

Grid operations are evolving as a result of the extension of existing huge scope inverter-based power stations and sun oriented (PV) power plants. In light of these alterations, the grid code has been updated to mandate the use of inverter based. In the event of grid failure, power plants should remain online and offer dynamic backup. The term “momentary cessation of operation” is commonly used to describe this characteristic. Very little is known about how PV power plants' temporary shutdowns contribute to the larger issue of unstable power supplies, and very few studies have been published on the topic. While trying to settle this issue, this study offers an ANFIS regulator engineering for PV inverters to work on that ephemeral solidness about coordinated dynamo associated through this network. This examination shows how each direct electric current connect condensers on that solar cell inverter might be utilized to assimilate a piece of the dynamic energy put away in the coordinated machine during the brief delays by utilizing the ANFIS regulator framework introduced. Besides, the recommended approach further develops voltage solidness by infusing responsive power. The viability of the recommended control system is affirmed by the introduced exploratory and reproduced discoveries.

Neural network predictive control for fault detection and identification in DFIG with SMES for low voltage ride-through requirements

The increasing reliance on renewable energy sources brings to light the operational challenges of doubly fed induction generators (DFIGs), particularly under grid disturbances. This study introduces an innovative approach employing Neural Network Predictive Control (NNPC) for fault detection and identification (FDI) in DFIG systems, integrated with Superconducting Magnetic Energy Storage (SMES) to meet Low Voltage Ride-Through (LVRT) requirements. Our method uniquely combines NNPC for dynamic wind speed prediction and precise control of rotor-side and grid-side converters with the stability enhancement offered by SMES. Simulation results demonstrate a notable improvement in DFIG performance under variable wind conditions and grid failures. The system-maintained voltage stability at the Point of Common Coupling (PCC) with less than 5% deviation during transients and ensured consistent power output, marking a significant advancement in LVRT compliance. However, the model assumes steady-state grid conditions and does not account for extreme weather scenarios, indicating areas for future research. This study's findings contribute valuable insights into the robust operation of DFIGs within modern renewable energy grids.

Surface Structural Changes in Silicone Rubber Due to Electrical Tracking.

There is a growing interest in the use of silicone composite insulators for electrical power transmission and distribution applications. However, such materials are susceptible to degradation as they are exposed to electrical and environmental stresses during operating conditions. Therefore, it is crucial to gain a thorough understanding of the degradation mechanism through changes in the material structure that may provide insight into potential failures in the electrical grid. Attenuated total reflection Fourier transform infrared spectroscopy and two-dimensional correlation spectroscopy (2D-COS) were used along with contact angle measurements to characterize changes in silicone rubber samples from actual insulators subjected to tracking wheel testing. The results showed a decrease in absorbance of different infrared bands representing different functional groups, such as Si-O-Si, methyl functional groups, and both Al-O and hydroxyl groups of alumina trihydrate as a function of the number of tracking cycles. The sequence of changes in the functional groups was determined by 2D-COS as Al-O and OH followed by Si-O-Si polymer backbone modes, followed by polymer methyl side chains. An enhancement in the average contact angle with the number of tracking cycles revealed a concomitant increase in surface roughness with electrical tracking.