Hasil untuk "Distribution or transmission of electric power"

G. Dileep

The Smart Grid is an advanced digital two-way power flow power system capable of self-healing, adaptive, resilient and sustainable with foresight for prediction under different uncertainties. In this paper, a survey on various Smart Grid enabling technologies, Smart Grid metering and communication, cloud computing in Smart Grid and Smart Grid applications are explored in detail. Opportunities and future of Smart Grid is also described in this paper. For Smart grid enabling technologies Smart meters, smart sensors, vehicle to grid, plug in hybrid electric vehicle technology, sensor and actuator networks are explored. Advanced metering infrastructure, intelligent electronic devices, phasor measurement units, wide area measurement systems, local area network, home access network, neighborhood area network, wide area networks and cloud computing are explored for Smart Grid metering and communication. Home and building automation, smart substation, feeder automation is explored for smart grid applications. Associations of initial studies for the next step in smart grid applications will provide an economic benefit for the authorities in the long term, and will help to establish standards to be compatible with every application so that all smart grid applications can be coordinated under the control of the same authorities. Therefore, this study is expected to be an important guiding source for researchers and engineers studying the smart grid. It also helps transmission and distribution system operators to follow the right path as they are transforming their classical grids to smart grids.

R. Iravani

M. Saha, J. Izykowski, E. Rosolowski

Christine Gschwendtner, S. Sinsel, Annegret Stephan

Abstract The uptake of electric vehicles supports decarbonization and increasingly interconnects the electricity and transport system. While the integration of electric vehicles could challenge electricity grids, bidirectional power flows between vehicles and grids could support grid operations. Despite the globally increasing number of Vehicle-to-X trials, including Vehicle-to-Grid and Vehicle-to-Customer, an in-depth understanding of trial implementations and expert experiences has largely been overlooked although they are both crucial for technological development and deployment. Based on our analysis of a global Vehicle-to-X trial database and 47 interviews with experts from industry and academia, we (i) provide an overview of the implementation status of Vehicle-to-X and analyze predominate trial configurations, i.e. combinations of characteristics, (ii) identify important technical, social and regulatory challenges for the implementation of Vehicle-to-X and assess and discuss expert evaluations of these challenges and (iii) derive implications for different actors. The most predominate trial configurations are Vehicle-to-Customer and transmission-level services provided by commercial fleets that charge at work due to current practical advantages of centralized approaches. From a technical standpoint, we find that although Vehicle-to-X can defer or even mitigate grid reinforcement at the distribution level, this potential is highly dependent on local conditions. Regarding social aspects, incentives and Vehicle-to-X operations need to be tailored to different vehicle users. Concerning regulation, it is imperative to avoid double taxation of electricity, simplify market participation for small providers, and further develop Vehicle-to-X standards. Implications for actors include the evaluation and enablement of portfolios with different flexibility assets, and stacking of services to increase revenue streams and reduce risk resulting from variations in driving patterns and charging behavior.

A. Christina, Md. Abdus Salam, Q. M. Rahman et al.

Imtiaz Parvez, Maryamossadat Aghili, Hugo Riggs et al.

Bidirectional wireless communication is employed in various smart grid components such as smart meters and control and monitoring applications where security is vital. The Trusted Third Party (TTP) and wireless connectivity between the smart meter and the third party in the key management-based encryption techniques for the smart grid are expected to be totally trustworthy and dependable. In a wired/wireless medium, however, a man-in-the-middle may seek to disrupt, monitor and manipulate the network, or simply execute a replay attack, revealing its vulnerability. Recognizing this, this study presents a novel authentication management (model) comprised of two layer security schema. The first layer implements an efficient novel encryption method for secure data exchange between meters and control center with the help of two partially trusted simple servers (constitutes the TTP). In this setting, one server handles the data encryption between the meter and control center/central database, and the other server administers the random sequence of data transmission. The second layer monitors and verifies exchanged data packets among smart meters. It detects abnormal packets from suspicious sources. To implement this node-to-node authentication, One class support vector machine algorithm is proposed which takes advantages of the location information as well as the data transmission history (node identification, packet size, and data transmission frequency). This schema secures data communication, and imposes a comprehensive privacy throughout the system without considerably extending the complexity of the conventional key management scheme.

Arbel Yaniv, Parteek Kumar, Yuval Beck

Yongze Li, Jianyu Wu, P. Yang et al.

Microwaves have become a promising wireless driving strategy due to the advantages of transmissivity through obstacles, fast energy targeting, and selective heating. Although there are some studies on microwave powered artificial muscles based on different structures, the lack of studies on microwave control has limited the development of microwave‐driven (MWD) robots. Here, a far‐field MWD parallel robot controlled by adjusting energy distribution via changing the polarization direction of microwaves at 2.47 GHz is first reported. The parallel robot is based on three double‐layer bending actuators composed of wave‐absorbing sheets and bimetallic sheets, and it can implement circular and triangular path at a distance of 0.4 m under 700 W transmitting power. The thermal response rate of the actuator under microwaves is studied, and it is found that the electric‐field components can provide a faster thermal response at the optimal length of actuator than magnetic‐field components. The work of the parallel robot is demonstrated in an enclosed space composed of microwave‐transparent materials. This developed method demonstrates the multi‐degree‐of‐freedom controllability for robots using microwaves and offers potential solutions for some engineering cases, such as pipeline/reactors inspection and medical applications.

Martin Lindner, Jan Peper, Nils Offermann et al.

Abstract Anticipating and relieving congestions is an ongoing challenge for transmission system operators. Distributed grid‐scale battery energy storage systems enable operators to shift power flows and remedy congestion through virtual power lines and grid boosters. This paper includes battery energy storage systems in a combined preventive and curative congestion management optimization. First, it analyzes the impact of the two operational strategies in a case study of the German transmission grid. Furthermore, it outlines curative ad‐hoc measures to overcome uncertainties during operational planning and real‐time operation. The simulation results indicate that battery energy storage systems further increase the use of curative measures and reduce congestion management costs.

Mohamed M. F. Darwish, Mahmoud Elsisi, Mostafa M. Fouda et al.

Baichuan Teng, Jianjun Ma, Miao Zhu et al.

Abstract DC short‐circuit fault has become one of the major concerns in bipolar DC system operation under complicated conditions. Compared with conventional two‐port DC‐DC converter, fault‐tolerant DC‐DC converter with multiple external ports is evaluated as a preferential choice for high reliability, availability and flexibility required bipolar DC system due to its capability of fault reconfiguration. This article focuses on a type of fault‐tolerant DC‐DC converter interconnected with DC bus and integrated energy storage devices applied in bipolar DC system and theoretical analyses on transmitted power characteristics under bipolar mode and monopolar mode are also carried out in this article. For bipolar mode, the minimized‐peak‐current control strategy is proposed to reduce current stress on switching devices. As for monopolar mode and source‐port fault mode, the fault reconfiguration method and constant‐transmitted‐power control strategy are designed to eliminate fault impaction and achieve the constant transmitted power of output port connected with critical load, by means of power sharing between input port and normal output port or between the normal output ports. Furthermore, intersection of zero‐voltage‐switching (ZVS) operation area under different working modes is depicted with consideration of two optimizing control. Finally, the performance of the proposed fault reconfiguration method and optimizing control have been tested in PLECS environment and experimental prototype to verify the reliability and flexibility.

Bahram Shakerighadi, Nicklas Johansson, Robert Eriksson et al.

Abstract Inverter‐based generators (IBGs) are becoming popular in modern power systems. When the penetration of IBGs is increasing in power systems, new stability, protection, and monitoring challenges are introduced in the grid. Grid‐forming (GFM) control of converters is seen as a promising solution for future power grids to overcome particular stability challenges. Here, the technical challenges of the GFM‐based IBGs are reviewed from the point of view of TSOs and academic research. The properties of different GFM methods are studied for different GFM‐based IBGs for a single grid‐tied IBG and using the IEEE 9‐bus test system. Simulation results are provided by using the PSCAD‐EMT simulation software.

Gabriela N. Lopes, Thiago S. Menezes, Douglas P. S. Gomes et al.

High Impedance Faults (HIFs) are recurring events in electrical Distribution Systems (DSs) and occur by the contact between energized conductors and high impedance surfaces. HIFs may pose hazards to living beings and cause bushfires. However, the HIF protection has not been completely solved due to the small fault current and varying impedance, inhibiting traditional protection techniques from functioning correctly. In the literature, researchers have mainly focused on detection techniques. Thus, the development of HIF Location Methods (HIFLMs) is recent, and evidences for conclusive solutions are still lacking. Moreover, to this date, no existing study reviews the main challenges concerning HIFLMs in DSs. This paper proposes a systematic analysis of the common stages to design the main existing HIFLMs. The strategy is evaluating the similar characteristics that pose a common research path regarding challenges faced in real-world conditions. Additionally, this paper proposes a case study to assess the best input signals, metrics, and machine learning-based decision algorithms of a new HIFLM. The results are promising, with high identification rates, even in noisy conditions. The methodology can help to select the datasets for supervised learning-based HIFLM. Highlighting the state-of-art of current methods and support development of HIFLMs are this paper’s main contributions.

Miao Ma, Chenxing Wang, Yuhong Li et al.

Abstract The acceptance check is a key step to decide whether an overhead transmission line can be put into use. However, for the acceptance check of towers, the manual means is still adopted mostly nowadays, which is dangerous and inefficient. The main challenges for intelligent check technique are the automatic tower segmentation and intelligent requirements of some detection items. Here, based on point clouds from lidars, some intelligent methods are proposed for tower related acceptance check items. The geometric structural changing rules for towers are found and analyzed to identify and segment towers from the scene point cloud automatically. A model‐constrained method is proposed for fine filtering of towers. With point cloud registration strategies, the tilt angle of a tower is calculated intelligently and the defect detection of a tower is conducted successfully. Experiments show that the results of the proposed methods are accurate, efficient and automatic, which have potential for real applications.

Nour A. Mohamed, Hany M. Hasanien, Essam A. Al‐Ammar et al.

Abstract This article describes a technique for improving the performance of an offshore wind farm (OWF), which includes a permanent magnet synchronous generator (PMSG) driven by a variable‐speed wind turbine (VSWT) and connected to the grid through a high‐voltage direct current transmission system (HVDC). Under various network disturbances, the gorilla tropical optimization (GTO) metaheuristic method is used to fine‐tune the proportional‐integral (PI) controller gains for VSC‐based PMSG‐VSWT and VSC‐based HVDC transmission systems. This study compares several strategies for extracting the maximum power from a system while maintaining stability under symmetrical and unsymmetrical fault circumstances. Compared to different algorithms, GTO provides better results and improves system recovery and stability after disturbances. As a consequence, dynamic and transient stability may be enhanced. MATLAB/Simulink is used to implement the control mechanism.

Shayan Z. T. Motlagh, Asghar Akbari Foroud

Abstract This paper proposes an intelligent approach based on the empirical Fourier decomposition (EFD) to identify harmonic sources at the point of common coupling (PCC) when different inverter‐based distributed generations (DGs) like microturbine (MT), battery energy storage system (BESS), photovoltaic (PV), superconducting magnetic energy storage (SMES), wind turbine with a permanent magnet synchronous generator (PMSG), and doubly‐fed induction generator (DFIG) wind turbine are presented. In order to decrease memory storage and computational burden, strife feature selection is used. Applying just voltage signals consumes less processing time and decreases measurement devices. Moreover, the whale optimization algorithm (WOA) as the optimizer of the parameters of the support vector machine (SVM) classifier is used. Consequently, the results from the proposed method can be helpful for both engineers and researchers to plan and develop a better strategy to mitigate harmonic distortion.

Milad Rahimipour Behbahani, Alireza Jalilian

Abstract Distribution network reconfiguration (DNR) is capable to improve indices of power systems by changing the distribution network (DN) topology under normal conditions. Here, DNR is implemented to improve the power quality (PQ) and power losses of DN. Furthermore, to achieve better optimum in DNR, discrete particle swarm optimization (DPSO) algorithm is equipped with a smart radial method. The proposed algorithm is faster than other metaheuristic methods due to the prevention of regeneration non‐radial configurations. In addition, the algorithm increases the probability of finding the optimal configurations using the mutation function. The results clearly demonstrated the positive effect of DNR in improving harmonic losses, total harmonic distortion (THD), and power losses. Furthermore, the proposed method is compared with other metaheuristic algorithms in IEEE 33 bus DN, IEEE 69 bus DN, and real 95‐bus DN in presence of photovoltaic (PV). The results show that the developed algorithm leads to the better or same accuracy and speed in all comparisons. In addition, results indicated that considering the summation of fundamental and harmonic losses compared to only fundamental losses in DNR can lead to further energy saving in DNs.

Shubhani Aggarwal, Neeraj Kumar, Sudeep Tanwar et al.

The smart grid is generally studied as an efficient and powerful electric grid. With the assistance of information and communication technology (ICT), the electric grid can increase the performance of the power grid system with smart energy management. On the other hand, with the usage of renewable energy resources (RERs), smart energy storage, and new transmission technologies in the power grid system, various new features such as real-time monitoring, fast restoration, battery displays, automated outage management, etc. have been assimilated into the smart grid. These new features generate more complexity in energy transmission and constitute important challenges like low energy consumption, high energy cost, social welfare, etc. while designing energy trading mechanisms in the smart grid. In the Internet-of-Things (IoT) era, several scenarios such as micro-grids, energy harvesting networks, and vehicle-to-grid (V2G) networks are present where energy trading plays an important role. However, in these scenarios, there are energy transmission and distribution, security and privacy, energy consumption, system reliability, the criticality of data delivery, and a few more challenges caused by distrust, non-transparent, and uncertain energy markets. Motivated from these challenges, we present a four-layered architecture of energy trading used in the smart grid. We propose a comprehensive background regarding the main concepts of energy trading and the implication of enabling technologies that manage the energy imbalances in the smart grid. Then, we present a problem taxonomy based on incentive, mathematical, and simulation model-driven approaches, which are widely used to control and maintain the energy trading mechanisms. Based on the findings from the literature, we also present a solution taxonomy with enabling technologies such as Energy Internet, Software-defined networking (SDN), and blockchain. In the end, a summary of future research directions based on the energy trading mechanisms is explored to provide deep insights to the readers.

N. Shaukat, S. M. Ali, C. A. Mehmood et al.

A. Aciu, C. Nicola, M. Nicola et al.

Power transformers play an important role in electrical systems; being considered the core of electric power transmissions and distribution networks, the owners and users of these assets are increasingly concerned with adopting reliable, automated, and non-invasive techniques to monitor and diagnose their operating conditions. Thus, monitoring the conditions of power transformers has evolved, in the sense that a complete characterization of the conditions of oil–paper insulation can be achieved through dissolved gas analysis (DGA) and furan compounds analysis, since these analyses provide a lot of information about the phenomena that occur in power transformers. The Duval triangles and pentagons methods can be used with a high percentage of correct predictions compared to the known classical methods (key gases, International Electrotechnical Commission (IEC), Rogers, Doernenburg ratios), because, in addition to the six types of basic faults, they also identify four sub-types of thermal faults that provide important additional information for the appropriate corrective actions to be applied to the transformers. A new approach is presented based on the complementarity between the analysis of the gases dissolved in the transformer oil and the analysis of furan compounds, for the identification of the different faults, especially when there are multiple faults, by extending the diagnosis of the operating conditions of the power transformers, in terms of paper degradation. The implemented software system based on artificial neural networks was tested and validated in practice, with good results.