Electric Power Grid Research Articles

ФУНКЦИОНАЛЬНЫЕ ВОЗМОЖНОСТИ СИСТЕМ РЕЛЕЙНОЙ ЗАЩИТЫ И АВТОМАТИКИ ЦИФРОВЫХ ПОДСТАНЦИЙ

A comprehensive analysis of the data on the technical accounting of the functioning of electrical relay protection complexes in the unified national electric power grid of Russia is presented, thanks to which the main types, causes and patterns of incorrect and emergency operation of the entire range of protections are established. An approach to the potential transition to servicing industrial electric power facilities based on the use of the entire set of relay protection functionality to solve the problems of automating maintenance procedures on a new hardware and methodological basis is proposed. Optimal criteria for evaluating the operability of electrical relay protection complexes and automation of digital transformer substations are formulated, which additionally take into account the influence of completeness and reliability of electrical information on the condition of protected electrical equipment affecting the quality of protection. It is shown that the organization of maintenance of electrical equipment by means of relay protection and automation according to the actual condition at an energy facility with a developed system of automated information collection and processing is a natural step of transformation in the electric power industry. The analysis of the relevance of the current technology of maintenance and repair of electrical equipment showed a significant reduction in the impact on the functional groups of measurement, information environment and receiving modules of electrical relay protection complexes and automation of digital substations.

Optimization and Stabilization of Distributed Secondary Voltage Control with Time Delays and Packet Losses Using LMIs

The proposed hierarchical secondary voltage control is a spatially distributed control system using communication networks which are disturbed by both a time delays and packet data dropouts. A state feedback integral control is adopted to eliminate the effect of non-zero disturbance and provide exact tracking of the references of the pilot points and alignment of the reactive powers of the generators that participate in the control. The system is modeled as a discrete-time switched system, and the control gains are synthesized by solving LMIs for a stability condition based on a state-dependent Lyapunov function. For that, the cone complementarity linearization (CCL) algorithm is used. The effectiveness of the proposed control strategy in preventing time delays and packet losses is simulated, considering the model of a realistic electric power grid under typical operational conditions using MATLAB.

Day-ahead schedule optimization of household appliances for demand flexibility: Case study on PV/T powered buildings

Employing the demand flexibility strategy in PV powered buildings can effectively balance solar energy supply and building energy demand, thereby increasing the self-consumption ratio of PV electricity. Despite this, its solar energy utilization is still low due to the limit of the PV efficiency. On the other hand, PV/T modules not only generate electricity but also produce domestic hot water, thus providing higher solar efficiency. In this study, the demand flexibility of various shiftable appliances in a PV/T powered building was investigated. An optimization-based demand flexibility strategy was proposed to reduce electricity cost and maximum grid power. The case study showed that the proposed strategy could reduce the electricity cost by 23 % and smooth grid power fluctuation. Moreover, compared with the PV powered building, the PV/T powered building could reduce the electricity cost by 10 % and significantly improve utility grid friendliness. Furthermore, the forecast error of boundary conditions negatively affected the electricity cost and grid power fluctuations. The sensitivity analysis revealed that the ambient temperature and solar irradiation on the PV/T modules had a greater impact on the optimization objective. Overall, this work aims to provide guidance for planning the flexibility operation of PV/T powered buildings.

Power Quality Enhancement Using Renewable Energy Sources and Electric Mobility

In the present day, there is a growing emergence of obstacles pertaining to the remuneration of power quality (PQ) issues. In this context, the implementation of renewable energy sources (RES) solutions has a critical significance. The transition from traditional electrical power grids to smart grids necessitates the utilization of a significant quantity of power electronics converters and RES. These converters are essential for the incorporation of crucial technologies like renewable energies, electric mobility, and energy storage systems. Consequently, PQ concerns gain heightened significance in this context. The article focuses on elucidating the primary phenomena related to PQ issues in smart grids, their origins, and consequences across various sectors. Additionally, the paper provides a comprehensive examination and categorization of the primary PQ issues, along with their corresponding alignment with established standards. It also offers an assessment of PQ problems associated with RES and their integration with electric mobility.

Defense against stealthy dummy Load Redistribution attacks

Load Redistribution (LR) attacks operate by adversarial manipulations of load measurements in electrical power grids. Machine Learning (ML) based detectors have been effective to detect LR attacks where the attacked load vectors are outliers of the distribution of normal load vectors. On the other hand a recent family of attacks, known as dummy LR attacks, are capable of bypassing the ML-based detectors by choosing attack load vectors that are not outliers. This paper presents an approach for defense against such stealthy third-generation dummy LR attacks by identifying and monitoring critical loads. A case study on the IEEE 30 bus system demonstrates the effectiveness of the proposed approach for defense against dummy LR attacks. A larger case study on actual load and line power flow measurements of the Delhi Power Grid demonstrates that the proposed approach can be extended to real-world grids.

Faults Diagnosis for Large-Scale Battery Packs via Texture Analysis on Spatial–Temporal Images Converted From Electrical Behaviors

Battery failures have become the most intractable obstacles undermining the market confidence in applications like electric vehicle and power grid energy storage. This paper aims to fashion a generic diagnosis scheme against the faults in large-scale battery systems. First, a voltmeter array-based anomaly perception mechanism against the electrical behaviors of battery packs is developed. Then, system information on spatial arrangement and temporal dynamics is organically fused and drawn as a kind of pseudo 2D images (P2Is). Afterwards, by analyzing the resultant P2Is with the 2D variational mode decomposition (2D-VMD) and gray level co-occurrence matrix (GLCM), some statistical quantities concerning multi-scale texture features, extracted and refined by the principal component analysis (PCA), are found to have strong indicative associations with battery fault type and fault grade. Finally, relying on the multi-class relevance vector machine (M-RVM), feature evidences are synthesized to detect fault occurrence and give judgements on fault specifics of type and severity. Experimental verifications on a li-ion battery pack with 180 cells suggest that the proposed scheme behaves well in fault type isolating, with an accuracy rate of 97.6% and in fault severity grading, with an accuracy rate of 84.67%.

Model-free reinforcement learning-based energy management for plug-in electric vehicles in a cooperative multi-agent home microgrid with consideration of travel behavior

The rise in popularity of plug-in electric vehicles (PEVs) and the increasing use of renewable energy sources (RESs) have paved the way for advanced energy management systems (EMSs) that optimize energy usage and distribution in home microgrids (H-MGs). This study focuses on the integration of PEVs in H-MGs using an EMS and analyzes its impact on electrical power grids (EPGs). We examine the effect of PEV charging and discharging patterns on H-MG energy flow, considering various scenarios such as high renewable energy generation, different levels of PEV penetration, and EPG connection status. Our findings indicate that an efficient EMS can significantly enhance H-MGs’ overall efficiency by intelligently scheduling PEV charging and discharging, maximizing the use of locally generated renewable energy, and reducing peak load on the EPG. We demonstrate that a cooperative multi-agent system EMS, driven by a robust continuous and real-time fuzzy Q-learning (FQL) method, can reduce electricity market prices by 15% by increasing the use of renewable energy generation by 25%. To fully realize the benefits of EMS, we address challenges such as reducing dependence on EPG by 30%, improving battery state by 12%, and ensuring EPG stability in the face of uncertainties.

On the security of a novel privacy‐preserving authentication scheme for V2G networks

AbstractVehicle‐to‐grid (V2G) network has a clear advantage in terms of economic advantages, it has attracted the interest of electric vehicle (EV) and power grid users. However, numerous security concerns limit its further progress. In existing V2G protocols a trusted third party independently generates the master key of the system, so if the adversary compromises the third party, then the system may become vulnerable to system master key leakage attack. Recently, Su et al. presented a privacy‐preserving mutual authentication protocol for V2G networks. Firstly, we crypt‐analysis Su et al.'s protocol and show that their protocol is vulnerable to several security attacks such as the reveal of the master secret key, impersonation attacks and the incorrect notion of EV's anonymity and traceability and does not meet the security features they claimed in their paper. Secondly, we verify that Su et al.'s protocol is unsafe against impersonation attacks, system key leakage, and electrical vehicle anonymity attack using the AVISPA tool.

Modeling and Evaluating Power Grid Resilience Under Extreme Space Weather

AbstractThe geomagnetically induced current (GIC) produced during extreme geomagnetic storms can easily lead to large‐scale blackouts in China due to the increase in the scale of its electric power grid. A power grid's resilience is its capability to resist various natural hazards, withstand primary failures, and quickly resume normal operation. To avoid power grid damages, this study developed a resilient power grid, incorporating failure, power flow calculation and recovery models under a uniform induced geoelectric field. We chose a system's performance loss as the resilience evaluation indicator, which intuitively reflected a system's loss under GIC. In addition, the recovery model was optimized using a genetic algorithm, and two resilience improvement measures were proposed. The IEEE‐RTS‐79 system, consisting of 10 generators, 24 buses and 5 transformers, was chosen as an example to verify the feasibility of this study. The results show that the genetic algorithm and optimization measures effectively enhanced the system's resilience indicator and provided a reference for preventing system damages under GIC and quick recovery after possible failures.

Fault current limiter based on high temperature superconductors

High Temperature Superconductors (HTS) made the Superconducting Fault Current Limiter (SFCL) a reality in power electric grids. Resistive SFCL, which is the subject of this article, is based on a unique property of superconductors to quench from a non-dissipative to a high dissipative state above a given current. SFCL is an attractive response to the poorly solved problem of fault currents in power electric grids and makes it possible to enhance the security and quality of electricity, something that matters more than ever. Liquid nitrogen cryogenics – which is possible thanks to HTS- makes the cryogenics user friendly. In-field SFCL operations confirm this. Second generation (2 G) HTS materials or Coated Conductors suit well to SFCL. Due to its high interest, SFCL has been the subject of a great deal of research and development. In terms of Technology Readiness Level (TRL) it reaches 8 with several in grid test experiences.Here a short history of SFCL is presented with a highlight about Curl 10, Ampacity and SuperOx devices. The two major locations in the grid are reported: grid coupling and feeder protection. The quench phenomena is described in a bit more detail before the basic design (length and cross section) is presented. The design is primarily thermal, considering two extreme operations: fault with very high prospective current (clear short-circuit) and fault with prospective current close to the minimum runaway current along the length. This operation is called the hot spot one. It is due to the intrinsic variation of the critical current along the length and to the low Normal Zone Propagation Velocity (NZPV). The cost of the superconducting conductor is given, showing no bottleneck for an economic development. All the more it is still possible to lower the cost with some developments. This article ends with two real advances presently underway: Current Flow Diverter (CFD) and Sapphire substrate superconducting 2 G tape. CFD aims to increase the NZPV, to still further secure the operation and to reduce the conductor cross section. The use of sapphire substrates allows to reduce significantly the length of the design.

Grid-Forming Control: Advancements towards 100% Inverter-Based Grids—A Review

Changes are being implemented in the electrical power grid to accommodate the increased penetration of renewable energy sources interfaced with grid-connected inverters. The grid-forming (GFM) control paradigm of inverters in active power grids has emerged as a technique through which to tackle the effects of the diminishing dominance of synchronous generators (SGs) and is preferred to the grid-following (GFL) control for providing system control and stability in converter-dominated grids. Therefore, the development of the GFM control is important as the grid advances towards 100% inverter-based grids. In this paper, therefore, we aim to review the changing grid scenario; the behaviour of grid-connected inverter control paradigms and major GFM inverter controls, including their modifications to tackle low inertia, reduced power quality, fault-ride through capability, and reduced stability; and the state-of-the-art GFM models that are pushing the universality of GFM inverter control.

A Distributionally Robust Defender-Attacker-Defender Model for Resilience Enhancement of Power Systems Against Malicious Cyberattacks

The cybersecurity of electric power grids is emerging as a critical challenge for the power industry in the transformation of modern power systems towards the future smart grid. It is of great importance to enhance the resilience of power systems against potential cyber threats. In this paper, a distributionally robust recovery resource allocation method based on the tri-level defender-attacker-defender (D-A-D) model is proposed to enhance the resilience of power systems in the face of malicious cyberattacks. The proposed recovery resource allocation method is able to optimally distribute the recovery resources among the substations in the grid to mitigate the impacts of successful cyberattacks during the recovery process, and improve the resilience performance of power systems against the attacks. In the proposed model, the recovery resource represents the available resource that can be expended to support the recovery efforts of the cyber-physical power system. It is expected to accelerate the recovery process of the system after successful attacks. The recovery resource may include necessary software, hardware, and labor force. Meanwhile, a distributionally robust optimization (DRO) model is proposed to address the uncertainty of the power system operation conditions, e.g., renewable energy resources (RESs). In order to verify the proposed system defense method, case studies were conducted on the IEEE Reliability Test System RTS-79. The results of the case studies show that the proposed method can provide a robust solution to recovery resource allocation for mitigating the risk of potential cyberattacks.

A Passivity-based direct power control scheme of a back to back NPC converter

In this paper, a direct power control (DPC) is proposed in order to improve the power dispatch in electrical power grids, as well as in microgrids. The objective of defining the active power and reactive power as state variables is to get a representation of the first level in a hierarchical control. The DPC model is studied under passivity rules, and an implementation of passivity-based control is proposed. Simulations are carried out to show the effectiveness of the proposed research.

An enhanced optimizer of social network search for multi-dimension optimal power flow in electrical power grids

This paper presents an enhanced computational optimizer of the Social Network Search Technique (ESNST) for multi-dimension Optimal Power Flow (OPF) in Electrical Power Grids (EPGs). The SNST is motivated by social network users who have various moods: conversation, imitation, innovation, and disputation. The proposed ESNST is introduced with two strategies. The first is the aggressive exploit process, which aims to increase the number of people seeking the best possible perspective to develop SNST performance. The second strategy proposes an adaptive parameter to aid in higher exploitation towards the end of iterations. This paper considers the multi-dimension OPF in EPGs with several minimization objectives for fuel costs, grid losses, and produced emissions. Not only that but also the system's power demands and losses must be satisfied. The performance of the proposed SNST and ESNST is evaluated on IEEE standard 30-bus, 57-bus, 118-bus, and practical West Delta Region EPGs. The results reveal the solution quality and robustness of the proposed ESNST compared with the SNST and other relevant techniques reported in the literature.

Analysis of the simultaneity factor of fast-charging sites using Monte-Carlo simulation

Given the increasing number of battery electric vehicles, the availability of suitable fast-charging infrastructure is crucial. However, designing such sites requires enough capacity in the electric power grid. A major influencing factor on the effect of fast-charging sites on the power grid is the simultaneity factor, i.e. the share of installed power related to the theoretical maximum power. The aim of this work is to investigate optimal simultaneity factors for fast-charging sites depending on various influencing factors. Real-world charging data from the biggest German operator is used in a stochastic approach via Monte-Carlo Simulation. It was found that in most cases, fast-charging sites can be designed with a simultaneity factor of 0.5 to satisfy demand. Applying this would reduce the effect on the power grid as well as reduce costs and time to build charging infrastructure. In consequence, the demand of the rising electric vehicle number can be met more efficiently.

The effects of climate change-induced cooling demand on power grids

The trend towards equipping buildings with active space cooling technology is expected to continue, due to the warming climate. In addition, the electrification of mobility and industry, and the massive rollout of photovoltaics, may put Austria’s power grids under stress if adequate mechanisms are not implemented in time. This study investigates the magnitudes of the loads induced by this increasing demand for cooling, together with the relief that passive cooling measures can provide. Data from current climate models, measured real load profiles from households, building stock models, and dynamic building simulations are utilised, alongside stakeholder and expert opinions, to fine-tune the analysis. This article suggests plausible scenarios for the development of the demand for cooling energy in Austria until 2050, and analyses the aggregated effect of the different options for cooling on the electricity power grid. The integration of cooling loads is expected to cause overloads or voltage violations only for a few types of grid within the periods investigated here. Subsidy programs in the building sector often do not properly consider cooling demand. Building regulations and subsidies should therefore focus on passive measures, and only when these are not sufficient should measures related to active cooling be implemented.

Discussion on Secure Standard Network of Sensors Powered by Microbial Fuel Cells.

Everyday tasks use sensors to monitor and provide information about processes in different scenarios, such as monitoring devices in manufacturing or homes. Sensors need to communicate, with or without wires, while providing secure information. Power can be derived from various energy sources, such as batteries, electrical power grids, and energy harvesting. Energy harvesting is a promising way to provide a sustainable and renewable source to power sensors by scavenging and converting energy from ambient energy sources. However, low energy is harvested through these methods. Therefore, it is becoming a challenge to design and deploy wireless sensor networks while ensuring the sensors have enough power to perform their tasks and communicate with each other through careful management and optimization, matching energy supply with demand. For this reason, data cryptography and authentication are needed to protect sensor communication. This paper studies how energy harvested with microbial fuel cells can be employed in algorithms used in data protection during sensor communication.

Enhancing Service Restoration in Tanzanian Power Grid using Internet of Things Sensors and Renewable Energy Sources

The increased dependence on the electric power grid, coupled with the increasing number of new customers, motivates the need to improve the reliability and resilience of the electric distribution systems. Modern distribution systems are becoming more resilient against power outages due to the increasing integration of Distributed Energy Resources (DERs) and the availability of efficient mechanisms for load shedding. Several studies considered fault detection and Service Restoration (SR) as separate problems without considering the implementation feasibility of integrating both solutions. To ensure the resiliency in the power system, it is important to have proper mechanisms which integrate sensing, detection, and SR as one problem while considering the load shedding and DER for improved capacity. Hence, this study proposed an IoT-based-sensor network framework with an enhanced algorithm coupled with a Binary Bat metaheuristic algorithm for SR integrating sensing, detection, and restoration. The proposed algorithms have been tested in Tanzania's electrical distribution network, considering the inclusion of DERs and load shedding. The results showed that DERs' size and locations significantly impact restoration schemes' performance with a power loss reduction of 74%. Therefore, efficient SR schemes should consider optimal DERs placement and a combination of load shedding and DERs integration for improved performance.

Distributed Reactive Power Injection-Based Approach for Minimization of Losses in Electrical Networks Considering Heuristic Algorithms and Voltage Deviation

This paper deals with the reduction in electrical losses and the minimization of voltage deviation in electrical power grids. To this end, a novel heuristic-based approach is proposed for controlling reactive power injections along an electrical grid with distributed generation using distributed photovoltaic (PV) generation. The proposed approach consists of applying a heuristic, namely a genetic or firefly algorithm, to solve the loss and voltage deviation optimization problem by controlling PV reactive power injections. The proposed method was tested on a radial 100-bus network with an intense penetration of PV generation. The obtained results indicate that the proposed method consistently yields superior grid performance when compared to algorithms previously proposed in the literature. In fact, it led to a reduction in the active power supplied by the reference bus to the grid, thereby alleviating the burden imposed on the most upstream parts of the distribution network. As a consequence, the proposed method contributes to a power-efficient network, enhancing its loss performance and voltage stability.

Focus on Monitoring and Control of Complex Supply Systems

Abstract The ongoing rapid transformation of our energy supply challenges the operation and stability of electric power grids and other supply networks. This focus issue comprises new ideas and concepts in the monitoring and control of complex networks to address these challenges.