Electrical Transmission Research Articles

SCADA World: An Exploration of the Diversity in Power Grid Networks

Despite a growing interest in understanding the industrial control networks that monitor and control our critical infrastructures (such as the power grid), to date, SCADA networks have been analyzed in isolation from each other. They have been treated as monolithic networks without taking into consideration their differences. In this paper, we analyze real-world data from different parts of a power grid (generation, transmission, distribution, and end-consumer) and show that these industrial networks exhibit a variety of unique behaviors and configurations that have not been documented before. To the best of our knowledge, our study is the first to tackle the analysis of power grid networks at this level. Our results help us dispel several misconceptions proposed by previous work, and we also provide new insights into the differences and types of SCADA networks.

Electricity power production, transmission and distribution losses in Ghana: the role of regulatory quality

ABSTRACT Ghana faces annual productivity losses of $320–$924 million due to electricity crises, impacting GDP by 2%-6% and stifling economic growth with over 5% power losses. The study, therefore, utilized time series data to explore the relationship between electricity production, transmission, and distribution losses in Ghana from 1983–2018, specifically focusing on the role of regulatory quality in this relationship. Using statistical tests like Philip-Perron and Augmented Dickey-Fuller, the study confirmed cointegration among the variables. The Autoregressive Distributed Lag model was then employed, analyzing data from 1983 to 2018. The research compared a base model with variables affecting electricity losses to an extended model that incorporated Institutions and their interaction with electricity production. The study reveals that improving regulatory quality and institutional strength significantly reduces electricity losses in Ghana, highlighting the need for strategic policies to enhance efficiency and reliability in the electricity sector. Results also showed that the labor force had a positive impact on losses, while economic growth and electricity production had a negative effect. Foreign direct investment and gross fixed capital formation were not significant. The study’s short-term findings confirmed these relationships. The inclusion of Institutions maintained similar signs and significance in variables except for foreign direct investment. The study recommends enhancing institutional quality, attracting more FDI into the energy sector, and implementing targeted measures to manage the labor force’s impact on electricity demand and losses.

Simulation based comparative analysis of electric field stress on insulated cross-arm

Insulated cross-arms for overhead transmission lines have become increasingly common in the past decade. The 3D finite element analysis (FEA) of the electric field distribution in insulated cross-arms is particularly intriguing due to the differences from conventional glass or ceramic insulators. The complex geometry of composite cross-arms, which feature four separate insulator strings and varying shed profiles, poses a challenge in modelling them using 3D FEA packages. The findings indicate that insulated cross-arms can operate within suitable parameters for traditional composite insulators. This paper presents and analyses the electric field distribution around an insulated cross-arm, which aims to replace existing high-voltage insulators and the steel cross-arms of transmission towers. The design of grading devices plays a crucial role in ensuring the safety of these structures. The use of grading ring devices at both ends of the insulator has proven effective in relieving stress on the insulator string under normal and abnormal conditions, enabling the insulated cross-arm to function effectively with conventional composite insulators. Significant reductions in electric field strength were observed, amounting to approximately 35.93 % inside the core, 31.14 % on the core surface, 35.64 % through the shed, and 16.67 % above the shed for compression members. For tension members, reductions from the low-voltage end to both ends were around 33.82 % inside the core, 38.55 % on the core surface, and 17.48 % through the shed. However, an 8.43 % increase was observed above the shed, indicating a deviation from the decreasing trend observed in other areas. These research findings provide valuable insights for designing and managing high-voltage systems, ensuring effective insulation and enhanced safety. It benefits electrical utilities and transmission line manufacturers by improving reliability and safety for overhead transmission lines.

Calculation algorithm for electromagnetic wave processes in multi-wire intersystem ETL

The nature of the transient process and the magnitude of the overvoltages are determined by a large number of factors in the HV/EHV AC transmission networks. The paper presents the study of mathematical modelling of electromagnetic wave processes in long-distance electric transmission line (ETL). The mathematical model is based on electromagnetic processes occurring on distributed parameter lines that are characterized by specific derivatives of the system of differential equations. The application of a spline-interpolation technique enables the calculation of currents and voltages at the nodes of the scheme, which obtains the unknown coordinates of the overhead line mode at the beginning of the ETL to solve the transmission line equation. The following results are derived from computer simulations of transients during switching on. With a simulation model, the importance of intelligent control of shunt reactor (SR) and ungrounded reactor (UR) was demonstrated and considered for a 500 kV power networks.

New interactions between various soliton solutions, including bell, kink, and multiple soliton profiles, for the (2+1)-dimensional nonlinear electrical transmission line equation

New interactions between various soliton solutions, including bell, kink, and multiple soliton profiles, for the (2+1)-dimensional nonlinear electrical transmission line equation

Design and implementation of a high misalignment-tolerance wireless charger for an electric vehicle with control of the constant current/voltage charging

Wireless charging of Electric Vehicles (EVs) has been extensively researched in the realm of electric cars, offering a convenient method. Nonetheless, there has been a scarcity of experiments conducted on low-power electric vehicles. To establish a wireless power transfer system for an electric vehicle, optimal power and transmission efficiency necessitate arranging the coils coaxially. In wireless charging systems, coils often experience angular and lateral misalignments. In this paper, a new alignment strategy is introduced to tackle the misalignment problem between the transmitter and receiver coils in the wireless charging of Electric Vehicles (EVs). The study involves the design and analysis of a coil, considering factors such as mutual inductance and efficiency. Wireless coils with angular misalignment are modelled in Ansys Maxwell simulation software. The proposed practical EV system aims to align the coils using angular motion, effectively reducing misalignment during the parking of two-wheelers. This is achieved by tilting the transmitter coil in the desired direction. Furthermore, micro sensing coils are employed to identify misalignment and facilitate automatic alignment. Additionally, adopting a power control technique becomes essential to achieve both constant current (CC) and constant voltage (CV) modes during battery charging. Integrating CC and CV modes is crucial for efficiently charging lithium-ion batteries, ensuring prolonged lifespan and optimal capacity utilization. The developed system can improve the efficiency of the wireless charging system to 90.3% with a 24 V, 16 Ah Lithium Ion Phosphate (LiFePO4) battery at a 160 mm distance between the coils.

Endogenous system-wide output prices in incentive regulation

We propose a simplification of frontier-based regulation currently implemented in several countries and demonstrate its potential application to the regulation of the Brazilian electricity transmission sector. A common regulation uses Data Envelopment Analysis (DEA) to estimate a cost function and mandates that firms adjust their costs to the DEA-estimated best-practice costs. Nevertheless, as DEA allows for individualized pricing of the services, such a DEA-based regulation may be challenging to understand and predict. Moreover, it may encourage strategic behavior in the selection of service profiles, thereby reducing competitive pressure on other firms with similar profiles. This could adversely affect the industry structure, leading to firms with suboptimal scales and scope. Therefore, instead of individualized output prices, we propose the use of a common set of endogenously determined prices that minimizes the total costs to end consumers, while ensuring individual rationality and incentive compatibility. We also present an extended approach that enables the regulator to strike a balance between rewarding well-performing agents and encouraging underperforming agents to save costs, while maintaining a minimal deviation from an expected aggregated payment. Achieving this balance is vital for incentivizing the agents to innovate and invest in more sustainable facilities in the electricity sector, promoting advancements in technology, energy efficiency, and environmental sustainability. Using Brazilian data, we demonstrate that the proposed incentive mechanism is operational and offers substantial advantages over the existing regulatory framework.

Swirling Capillary Instability of Rivlin–Ericksen Liquid with Heat Transfer and Axial Electric Field

The mutual influences of the electric field, rotation, and heat transmission find applications in controlled drug delivery systems, precise microfluidic manipulation, and advanced materials’ processing techniques due to their ability to tailor fluid behavior and surface morphology with enhanced precision and efficiency. Capillary instability has widespread relevance in various natural and industrial processes, ranging from the breakup of liquid jets and the formation of droplets in inkjet printing to the dynamics of thin liquid films and the behavior of liquid bridges in microgravity environments. This study examines the swirling impact on the instability arising from the capillary effects at the boundary of Rivlin–Ericksen and viscous liquids, influenced by an axial electric field, heat, and mass transmission. Capillary instability arises when the cohesive forces at the interface between two fluids are disrupted by perturbations, leading to the formation of characteristic patterns such as waves or droplets. The influence of gravity and fluid flow velocity is disregarded in the context of capillary instability analyses. The annular region is formed by two cylinders: one containing a viscous fluid and the other a Rivlin–Ericksen viscoelastic fluid. The Rivlin–Ericksen model is pivotal for comprehending the characteristics of viscoelastic fluids, widely utilized in industrial and biological contexts. It precisely characterizes their rheological complexities, encompassing elasticity and viscosity, critical for forecasting flow dynamics in polymer processing, food production, and drug delivery. Moreover, its applications extend to biomedical engineering, offering insights crucial for medical device design and understanding biological phenomena like blood flow. The inside cylinder remains stationary, and the outside cylinder rotates at a steady pace. A numerically analyzed quadratic growth rate is obtained from perturbed equations using potential flow theory and the Rivlin–Ericksen fluid model. The findings demonstrate enhanced stability due to the heat and mass transfer and increased stability from swirling. Notably, the heat transfer stabilizes the interface, while the density ratio and centrifuge number also impact stability. An axial electric field exhibits a dual effect, with certain permittivity and conductivity ratios causing perturbation growth decay or expansion.

Early warning and proactive control strategies for power blackouts caused by gas network malfunctions

There is growing consensus that gas-fired generators will play a crucial role during the transition to net-zero energy systems, both as an alternative to coal-fired generators and as a flexibility service provider for power systems. However, malfunctions of gas networks have caused several large-scale power blackouts. The transition from coal and oil to gas fuels significantly increases the interdependence between gas networks and electric power systems, raising the risks of more frequent and widespread power blackouts due to the malfunction of gas networks. In a coupled gas–electricity system, the identification and transmission of gas network malfunction information, followed by the redispatch of electric power generation, occur notably faster than the propagation and escalation of the malfunction itself, e.g., significantly diminished pressure. On this basis, we propose a gas-electric early warning system that can reduce the negative impacts of gas network malfunctions on the power system. A proactive control strategy of the power system is also formulated based on the early warning indicators. The effectiveness of this method is demonstrated via case studies of a real coupled gas–electricity system in China.

Characterising early warning signals for critical transitions using a distribution moment approximation for the Fokker–Planck equation

Critical transitions are abrupt transition in time-varying systems. They occur in many different scientific contexts, ranging from climate and ecology to physiology and electricity transmission, and can be driven by different underlying mathematical structures. Here we focus on those driven by underlying bifurcations (so-called B-tipping), which are associated with qualitative changes in the underlying system energy landscape. Building on Kuehn’s fast-slow framework (Kuehn, 2011), we relax the assumptions of stationarity and reflecting boundary conditions by employing a distribution moment approach, which allows us to classify the utility of early warning signals (such as the variance) even when the timescales are not well separated, or the reflection boundary assumption is restrictive. This allows a more complete characterisation of moment-based early warning signals.

Contribution to the determination of the effect of magnetic storms on the electric power transmission system

Abstract When a magnetic storm hits a power transmission system, quasi-stationary geomagnetically induced currents (GIC) are generated in the high-voltage part of the system. These currents cause semi-saturation of the magnetic circuits of power transformers, which induces current overload in their high-voltage windings and subsequently thermal overload, which can lead to system failures. This rather complex phenomenon was described in [11] by a system of nonlinear differential equations and subsequently solved. This very challenging method is replaced in the present work by a simple approach. It allows not only predicting the imminent danger of system collapse, but gives transformer designers valuable information on how they can counteract this danger.

Bi-Level Continuous-Time Model for the Coordinated Operation of Coupled Electric Power Transmission and Energy Storage Transportation Systems

Bi-Level Continuous-Time Model for the Coordinated Operation of Coupled Electric Power Transmission and Energy Storage Transportation Systems

Extensive soma-soma plate-like contact sites (ephapses) connect suprachiasmatic nucleus neurons.

The hypothalamic suprachiasmatic nucleus (SCN) is the central pacemaker for mammalian circadian rhythms. As such, this ensemble of cell-autonomous neuronal oscillators with divergent periods must maintain coordinated oscillations. To investigate ultrastructural features enabling such synchronization, 805 coronal ultrathin sections of mouse SCN tissue were imaged with electron microscopy and aligned into a volumetric stack, from which selected neurons within the SCN core were reconstructed insilico. We found that clustered SCN core neurons were physically connected to each other via multiple large soma-to-soma plate-like contacts. In some cases, a sliver of a glial process was interleaved. These contacts were large, covering on average ∼21% of apposing neuronal somata. It is possible that contacts may be the electrophysiological substrate for synchronization between SCN neurons. Such plate-like contacts may explain why the synchronization of SCN neurons is maintained even when chemical synaptic transmission or electrical synaptic transmission via gap junctions is blocked. Such ephaptic contact-mediated synchronization among nearby neurons may therefore contribute to the wave-like oscillations of circadian core clock genes and calcium signals observed in the SCN.

Optimizing loss functions for improved energy demand prediction in smart power grids

In this paper, our aim is to improve the accuracy and effectiveness of energy demand forecasting, particularly within modern electricity transmission systems and smart grid technology. To achieve this, we developed a hybrid approach that combines machine learning, representation learning, and other deep learning techniques. This approach is based on extracting essential features, including time-based attributes, identifiable trends, and optimal lags. The outcome of our investigation is the observation that triplet losses demonstrate remarkable accuracy, particularly when employed with a larger margin size and for longer prediction lengths. This finding signifies a substantial improvement in the precision and reliability of energy demand forecasting within modern electricity transmission systems. Our research not only improves predictive modeling in the power grid but also demonstrates the practical use of advanced analytics in addressing renewable energy integration challenges, refining energy demand forecasting for efficient management, system operation, and market analysis.

Fabrication of a novel high electrical conductivity Si3N4 matrix composite with Cu three-dimensional network structure by spark plasma sintering

Silicon nitride (Si3N4) ceramic matrix conductive composite materials have shown great promise as conductive layer materials for electrical transmission components. However, existing conductive phases struggle to form a three-dimensional (3D) interconnected network in Si3N4 matrix, resulting in poor electrical conductivity. This study proposed a spark plasma sintering (SPS) process utilizing Si3N4 as the substrate and Cu particles as the reinforcement phase to fabricate a novel electrical conductivity Si3N4/Cu composite material. The results indicated that the diffusion of Si atoms in Si3N4 facilitated the formation of copper silicide (CuiSi) interface between the two constituents during sintering, creating a strong chemical bonding for high conductivity. Simultaneously, composite materials with optimized Cu content formed a 3D interconnect network structure, providing a continuous path for electrical conduction. At Cu content of 30 vol%, the Si3N4/Cu composite exhibited a satisfying electrical conductivity of 295.37 S/m, which was 14 orders of magnitude higher than that of Si3N4. The composites also demonstrated a percolation phenomenon, with a theoretical percolation threshold of Cu particles at just 0.1 vol%, an order of magnitude lower than that of carbon reinforcement particles. Furthermore, an integrated design featuring external insulation and internal conductivity was achieved by wrapping a Si3N4 insulation layer around the conductive Si3N4/Cu composites. The fabricated insulation layer exhibited higher resistivity (1.12×1014 Ω) and a lower wear rate (1.3×10−6 mm3/N·m) compared to some contemporary insulation ceramics, while the conductive layer had a lower calorific value, making them excellent candidates for electrical transmission component materials.

Frequency stability study of energy storage participation in new energy power system using virtual synchronous machine control

Aiming at the frequency stability of the power system under the increasing proportion of new energy sources, the study adopts the virtual synchronous machine-based energy storage adaptive control strategy and the frequency response model of the new power system. The energy storage adaptive control strategy coordinates the control of the battery’s charging state and the grid operation state by monitoring the grid operation parameters and the battery operation state in real time, so as to calculate the commanded power of the grid-connected converter. The results show that the system stability of adaptive virtual synchronization control improves when the electric transmission power increases from 205 to 510, while the system stability of virtual synchronization control decreases. The extended SFR model possesses excellent frequency matching ability when the new energy penetration rate is 8.497% and 15.66%. Virtual synchronous energy storage control strategy and the power system frequency response model can effectively predict and control the system frequency change to improve system stability under the increasing penetration rate of new energy.

Transmission Line Power Theft

Abstract: Generation, transmission and distribution of electrical energy involve many operational losses. We can defined the losses in generation technically but distribution and transmission losses cannot be precisely quantified with the sending end information. This illustrates the involvement of nontechnical parameter in transmission and distribution of electricity. Moreover technical losses occur naturally and are caused because of power dissipation in transmission lines, transformers, and other power system components. Technical losses in Transmission & Distribution are computed with the information about total load and the total energy bill. While technology in the raising slopes, we should also note the increasing immoral activities. The system prevents the illegal usage of electricity. At this point of technological development the problem of illegal usage of electricity can be solved without any human control using IoT. With the implementation of this system will save large amount of electricity, and there by electricity will be available for more number of consumer then earlier, in highly populated country such as India, China. Power theft can be defined as the usage of the electrical power without any legal contract with the supplier. To see it, a proposed system (current measurement and comparison) is proposed in which the distribution of family power is done indirectly from the distribution box to each house. Power theft is a persistent issue in many countries, leading to significant financial losses for utility companies and affecting the reliability of power supply. In this study, we propose a novel approach for detecting power theft in transmission lines using NodeMCU ESP8266, a low-cost Wi-Fi-enabled microcontroller, and Blynk IoT platform for remote monitoring and control.The proposed system involves installing current sensors at various locations along the transmission lines to measure the current flow. The NodeMCU ESP8266 is used as a data acquisition unit that collects the current data from the sensors and sends it to the Blynk IoT platform via Wi-Fi for real-time monitoring. The Blynk platform provides a user-friendly interface for visualizing the data and setting up alarms and notifications for abnormal current patterns, which could indicate power theft. The system can also track power consumption trends, identify abnormal usage patterns, and provide insights for optimizing power distribution. The proposed system has several advantages, including low-cost implementation, real-time monitoring, remote access, and easy customization through the Blynk platform. It has the potential to significantly reduce power theft, improve revenue collection for utility companies, and enhance the overall reliability of power supply in transmission lines. Further research and development can be done to optimize the system's performance and expand its applications in different power distribution scenarios.

A Deep Learning-based Fault Detection and Classification in Smart Electrical Power Transmission System

Progressively, the energy demands and responsibilities to control the demands have expanded dramatically. Subsequently, various solutions have been introduced, including producing high-capacity electrical generating power plants, and applying the grid concept to synchronize the electrical power plants in geographically scattered grids. Electrical Power Transmission Networks (EPTN) are made of many complex, dynamic, and interrelated components. The transmission lines are essential components of the EPTN, and their fundamental duty is to transport electricity from the source area to the distribution network. These components, among others, are continually prone to electrical disturbance or failure. Hence, the EPTN required fault detection and activation of protective mechanisms in the shortest time possible to preserve stability. This research focuses on using a deep learning approach for early fault detection to improve the stability of the EPTN. Early fault detection swiftly identifies and isolates faults, preventing cascading failures and enabling rapid corrective actions. This ensures the resilience and reliability of the grid, optimizing its operation even in the face of disruptions. The design of the deep learning approach comprises a long-term and short-term memory (LSTM) model. The LSTM model is trained on an electrical fault detection dataset that contains three-phase currents and voltages at one end serving as inputs and fault detection as outputs. The proposed LSTM model has attained an accuracy of 99.65 percent with an error rate of just 1.17 percent and outperforms neural network (NN) and convolutional neural network (CNN) models.

Nonlinear dynamic wave characteristics of optical soliton solutions in ion-acoustic wave

Traveling wave solutions are utilized to depict reaction-diffusion and analyze electrical signal transmission and propagation in space-time nonlinear fractional order partial differential equations like the space-time fractional Telegraph and Kolmogorov-Petrovsky Piskunov equations, and that are used in physical science to model combustion, biological research to model nerve impulse propagation, chemical dynamics to model concentration in order wave propagation, and plasma to model the progression of a set of duffing oscillators. In this study, the new generalized (G′/G)−expansion technique was employed to construct some novel and more universal closed-form traveling wave solutions in the sense of conformable derivatives which explain the above-stated phenomena properly. By utilizing complex fractional transformation, the ordinary differential equations are generated from fractional order differential equations. The recommended technique allowed us to produce some dynamical wave patterns of kink, single soliton, compacton, periodic shape, multiple periodic waves, anti-kink, and other structures are developed, which are shown using 3D plots and contour plots to illustrate the physical layout clearly. The traveling waveform responses can be defined in terms of functions based on trigonometry, hyperbolic operations, and rational functions and that are quick, flexible, and simple to reproduce. Furthermore, the obtained closed-form solutions for nonlinear fractional evolution equations make stability analysis and accuracy comparison amongst numerical solvers easier, which asserts that the new generalized (G′/G)−expansion technique is one of the most proficient and effective approaches.

Comparative analysis and implementation of DC microgrid systems versus AC microgrid performance

DC power systems have emerged as a cost-effective solution for electric power generation and transmission, challenging the dominance of AC distribution systems. However, a comprehensive efficiency comparison between DC and AC microgrids remains understudied. This study seeks to explore and conduct a thorough survey on development and designing of DC microgrids to address this gap. Firstly, a comprehensive literature review comparing the efficiencies of AC and DC microgrids has been presented. The analysis highlights the superior efficiency of DC distribution systems over AC systems, supported by detailed advantages. Secondly, hardware implementation has been performed to directly compare the efficiency of DC versus AC systems. Research validity and application are further improved by the hardware prototype’s scalability, which in simulation allows for a thorough assessment of system stability over a range of scenarios from four to six terminals. Test results from the built hardware prototype demonstrate an astounding 15% increase in efficiency using the DC system compared to the AC system, demonstrating its potential for improved performance in real-world scenarios. In simulation results, the designed DC microgrid demonstrates stable voltages of 500V under steady state operation and rapid recovery within 80 ms under both symmetrical and asymmetrical faults has been observed. The research being investigated utilizes hardware implementation and simulation to provide useful insights into the efficiency and stability of DC microgrids in comparison to AC systems. These results are important for developing robust power distribution networks in modern energy environments, promoting sustainability and dependability in infrastructure growth.