Grid Design Research Articles

Inception 1D-convolutional neural network for accurate prediction of electrical insulator leakage current from environmental data during its normal operation using long-term recording

Contamination flashover remains one of the biggest challenges for power grid designers and maintenance engineers. Insulator leakage current contains relevant information about their state so that continuous monitoring is considered the most effective way to prevent contamination flashover. In this work, we attempted to accurately predict insulator leakage current in real time during normal operations based on environmental data using long-term recordings.We first confirmed that the history of environmental data also contained relevant information to predict leakage current by conditional Granger analysis and determined that 20 was the optimal number of previous samples for this purpose. We then compared the performance of typical regression models and convolutional neural network (CNN), when using both current and the last 21 samples as input features. We confirmed that the model with the last 21 samples might perform significantly better. Input features pre-processing by cascaded inception architecture was fundamental to capture the complex dynamic interaction between environmental data and leakage current and significantly improved the model performance. CNN based on inception architecture performed much better, achieving an average R2 of 0.94 ± 0.03. The proposed model could be used to predict leakage current in both porcelain insulators with or without coatings and silicone composite insulators.Our results pave the way for creating an on-line pre-warning system adapted to individual installations, can anticipate the negative consequences of weather and/or pollution deposits and is useful for designing a strategic high-voltage electrical insulator preventive maintenance plan for preventing contamination flashover and thus increase power grid reliability and resilience.

A Simplified Method of Manually Constructing Small Format Tissue Microarray for Use in Resource-Constrained Settings.

Tissue microarray (TMA) is a method of harvesting small tissue cores from a number of donor paraffin tissue blocks and arraying them in a recipient paraffin block. It has numerous advantages and applications but is expensive. This study aimed to develop a simple yet efficient method of manual, small-format TMA block construction. Disposable skin punch biopsy needles were used to manually core out 4-mm cylinders from the archival donor blocks comprising tissue from 60 thyroidectomy specimens. These cores were oriented in the embedding cassette in accordance with the grid design. The molten wax was slowly dispensed and allowed to be set. Sectioning, mounting, and hematoxylin and eosin (H&E) staining were performed by a conventional method. Immunohistochemical studies, using HBME-1, CK19, and S100 antibodies, were also performed on these tissue array sections. There was no core loss during processing. Technical issues like core tilt and floatation were easily tackled. Morphological identification, histological typing, and immunohistochemical analysis could be satisfactorily performed in these TMA sections. Donor blocks did not break after punching. This TMA construction method is simple, feasible, easily reproducible, and time-saving. It can serve as an excellent cost-effective alternative for resource-poor laboratories for carrying out immunohistochemical studies.

Hybrid Bacterial Foraging Optimization with Sparse Autoencoder for Energy Systems

The Internet of Things (IoT) technologies has gained significant interest in the design of smart grids (SGs). The increasing amount of distributed generations, maturity of existing grid infrastructures, and demand network transformation have received maximum attention. An essential energy storing model mostly the electrical energy stored methods are developing as the diagnoses for its procedure was becoming further compelling. The dynamic electrical energy stored model using Electric Vehicles (EVs) is comparatively standard because of its excellent electrical property and flexibility however the chance of damage to its battery was there in event of overcharging or deep discharging and its mass penetration deeply influences the grids. This paper offers a new Hybridization of Bacterial foraging optimization with Sparse Autoencoder (HBFOA-SAE) model for IoT Enabled energy systems. The proposed HBFOA-SAE model majorly intends to effectually estimate the state of charge (SOC) values in the IoT based energy system. To accomplish this, the SAE technique was executed to proper determination of the SOC values in the energy systems. Next, for improving the performance of the SOC estimation process, the HBFOA is employed. In addition, the HBFOA technique is derived by the integration of the hill climbing (HC) concepts with the BFOA to improve the overall efficiency. For ensuring better outcomes for the HBFOA-SAE model, a comprehensive set of simulations were performed and the outcomes are inspected under several aspects. The experimental results reported the supremacy of the HBFOA-SAE model over the recent state of art approaches.

Efficiency Optimization via Mission Profile-Based Power Routing by Design of Hybrid Grid Connecting Converter Architecture

Hybrid grids with low voltage direct current (LVdc) distribution are an attractive opportunity for the integration of electric vehicle charging stations and photovoltaic power plants. With dc connectivity reduced power losses are possible, however, multiple conversion stages can impair an efficient operation. A solution can be the use of an “interconnected” architecture that allows the integration of multiple insulated dc and ac grids. The reconfiguration of this modular topology allows optimization for different design objectives. This work investigates the system efficiency-optimized reconfiguration. Two approaches for deriving the reconfiguration of the hybrid grid connecting converter architecture based on mission profiles are proposed. A validation of the analysis via laboratory results is given.

乏燃料贮存格架结构改进设计研究

乏燃料贮存格架结构改进设计研究

Coupling Analysis and Protection Design of Substation Grounding Grid and Surrounding Metal Pipe Grid

When the substation grounding grid and part of the underground metal pipe grid are close to each other, the two produce resistive coupling, and the current of the transmission line will flow through the grounding body and through the soil to the buried pipe grid, which may break through the anti-corrosion layer of the pipe grid, and may burn the body of the pipe grid in serious cases; the underground metal pipe grid will also have an impact on the parameters of the grounding grid. To this end, this paper is based on the numerical calculation method of field-path coupling, combined with the actual situation of substation, using CDEGS and ETAP software to simulate and analyze the current dissipation process when a short-circuit fault occurs in the substation after the ground grid is put into operation under multi-layer soil environment, and to study the influence of resistive coupling between the grounding grid and the surrounding metal pipe grid during an industrial frequency grounding short circuit. Optimize the structure of the grounding system so that the contact voltage across and step voltage is lower than the safety limit to protect the personal safety in the station; at the same time, take certain protective measures to slow down the corrosion of the pipe grid.

Hybrid Optimized PI Controller Design for Grid Tied PV Based Electric Vehicle

Nowadays, researchers are becoming increasingly concerned about developing a highly efficient emission free transportation and energy generation system for addressing the pressing issue of environmental crisis in the form of pollution and climate change. The introduction of Electric Vehicles (EVs) solves the challenge of emission-free transportation while the necessity for decarbonized energy production is fulfilled by the installation and expansion of solar-powered Photovoltaic (PV) systems. Hence, this paper focuses on designing an effective PV based EV charging system that aids in stepping towards the achievement of a pollution free future. For overcoming the inherent intermittency associated with PV, a novel DC-DC converter is designed by integrating both Trans Z-source converter and Luo converter, which offers remarkable benefits of high conversion range, lesser voltage stress and excellent efficiency. A novel robust Lion Grey Wolf Optimized Proportional Integral (LGWO-PI) controller is designed for significantly strengthening the operation of the integrated converter in terms of peak overshoot, Total Harmonic Distortion (THD) and settling time. A 3φ Voltage Source Inverter (VSI) is employed to convert the stable DC output from the PV system to AC, which is then used for driving the Brushless Direct Current Motor (BLDC) motor of EV. The speed of the BLDC is regulated using a PI controller. The BLDC motor gets the power supply from the grid during the unavailability of PV based power supply. The grid is integrated with the designed EV charging system through a 1φ VSI and the process of grid voltage synchronization is carried out with the application of PI controller. The simulation for evaluating the operation of the presented EV charging system is done using MATLAB and the attained outcomes have validated that this introduced methodology delivers enhanced performance with optimal efficiency of 97.6% and lesser THD of 2.1%.

Analysis of IR Drop for Robust Power Grid of Semiconductor Chip Design: A Review

Modern semiconductor industry has a major focus on die size reduction and favours the usage of multiple metal layers to increase gross margins. High congestion and voltage or IR drop challenges result from designs with higher and lower core utilisations. Owing to this issue, one of the major difficulties in large silicon-on-chip (SoC) design is the implementation of a power grid design. It’s essential to correctly analyze IR drops to guarantee the reliability of the power grid. This paper presents a comprehensive review approach for the analysis of IR drop for robust power grid design in semiconductor chips. The necessity of the vector-based dynamic analysis and the drawbacks of the vector-less analysis have been addressed. The various techniques used to mitigate IR drop effects, including power grid modeling techniques, use of decoupling capacitors, and voltage drop analysis are explored. The review concludes by identifying the most promising techniques for robust power grid design in semiconductor chips and providing recommendations for future research. The simulations are carried out using ANSYS RedHawk, and the analysis findings are achieved using FinFET technology.

Comparative Analysis of Equal and Unequal Grounding Grid Configurations by Compression Ratio and Least Square Curve Fitting Techniques

The primary aim of the power system grounding is to safeguard the person and satisfying the performance of the power system to maintain reliable operation. With equal conductor spacing grounding grid design, the distribution of the current in the grid is not uniform. Hence, unequal grid conductor span in which grid conductors are concentrated more at the periphery is safer to practice than equal spacing. This paper presents the comparative analysis of two novel techniques that create unequal spacing among the grid conductors: the least-square curve fitting technique and the compression ratio technique with equal grid configuration for both square and rectangular grids. Particle Swarm Optimization (PSO) is adopted for finding out one optimal feasible solution among many feasible solutions of equal grid configuration for both square and rectangular grids. Comparative analysis is also carried out between square and rectangular grids using the least square curve fitting technique as it results in only one unequal grid configuration. Simulation results are obtained by the MATLAB software developed. Percentage of improvement in ground potential rise, step voltage, touch voltage, and grid resistance with variation in compression ratios are plotted.

Uneven Grid-based Linear Parameter-Varying Controller Design for Guided Projectiles

This paper proposes a Linear Parameter-Varying (LPV) controller design for the pitch channel dynamics of a new class of Long Range Guided Projectiles (LRGP). The grid-based approach is preferred since it provides advantages in terms of performance and conservatism. Differently from standard aerospace applications that limit the scheduling vector to the variation of the altitude and the Mach number, the investigated flight envelope is parameterized through a 3D grid, which includes the variation of the angle-of-attack, crucial for range optimization purposes. Thus, an extensive investigation of the grid design is required to minimize the computational complexity of the controller synthesis. The performances of the LPV controller are assessed by employing a nonlinear reference tracking simulation scenario.

Grid-type LED media façade with reflective walls for building-integrated photovoltaics with virtually no shading loss

Although anthropogenic climate change has demanded the development and use of building-integrated photovoltaics in zero energy building design, their poor aesthetic value has hindered their public acceptance. Accordingly, a grid-type LED display with reflective walls is herein proposed to bestow not only an aesthetic value to plain photovoltaic modules, but also an informative function as a media façade. Its lightweight, modular design enables it to be detachable and repairable. Upright flexible printed circuit boards embedded in the grid walls allow the use of wide copper electrodes and dual in-line package LEDs while casting virtually no shadows, leading to low resistive loss, excellent heat dissipation, and high luminance. The grid design exhibits a shading loss of only −3.67 %, which contributes to its superiority over conventional plane-type LED displays with a shading loss of −22.59 %. Reflective walls redirecting sunlight at solar incidence angles towards the photovoltaic modules lead to an average relative maximum power of 87.50 %, which is far higher than the 76.47 % achieved with opaque walls. The effective energy production simulations suggest that the grid-type LED displays can be run in a self-standing mode for up to 21.74 h per day. The presented grid-type LED display will contribute to the fast and wide adoption of building-integrated photovoltaics with increased public acceptance.

Simulation and Optimization of CNTs Cold Cathode Emission Grid Structure

Carbon nanotubes (CNTs) show significant advantages in the development of cold cathode X-ray tubes due to their excellent field emission performance; however, there are still some problems, such as short lifetime and the low emission current of large-area CNTs. In this paper, a front-grid carbon nanotube array model was established, and the electric field intensity near the tip of the CNTs' electric field enhancement factor was analytically calculated. A simulation model of a CNT three-dimensional field emission electron gun was established by using computer simulation technology (CST). The effects of grid wire diameter, grid aperture shape, and the distribution of grid projection on the cathode surface on the cathode current, anode current, and electron transmission efficiency were analyzed. The aperture ratio was used to evaluate the grid performance, and the simulation results show that the ideal aperture ratio should be between 65% and 85%. A grid structure combining a coarse grid and a fine grid was designed, which can make the electric field intensity around the grid evenly distributed, and effectively increased the cathode emission current by 24.2% compared with the structure without the fine grid. The effect of grid aperture ratio on the electron transmission efficiency was tested. The simulation results and optimized structure can provide a reference for the grid design of cold cathode emission X-ray tubes.

Power Grid Infrastructural Resilience against Extreme Events

Extreme weather events are one of the main causes of large-scale power outages in distribution systems. The changing climate has led to an increase in the frequency and severity of these events, which, if not mitigated, are expected to lead to more instances of widespread outages and the severe societal and economic damages that ensue. Protecting the power grid against such events, which are high impact yet low frequency, requires a paradigm shift in grid design practices. In recent years, many researchers have focused on the resilience of the power grid against extreme weather events by proposing various grid hardening and/or redundancy solutions. The goal of this paper is to provide a survey of the literature related to the infrastructural resilience of the power grid against extreme events. Currently, no standard definitions or metrics exist for power grid resilience, and researchers adopt various models for quantifying and assessing it. Hence, a review of the most commonly used definitions and metrics for resilience is provided first, with a discussion of their advantages and disadvantages. Next, the paper presents an extensive and critical review of the solution methodologies proposed in the literature for improving the infrastructural resilience of the power grid. The shortcomings of the current solution methods and gaps in research are identified, followed by a discussion of the future directions in research.

Enhancing Grid Integration and Design of Low Speed PMSGs by Exploiting SRF-PLL-Based Sensorless Control and Holistic Modeling

This article proposes a holistic co-design framework with a low-cost approach for a permanent magnet synchronous generator (PMSG) that enables to optimizes both the electromagnetic and mechanical design, in conjunction with the injection of the maximum available power towards the power grid through a controlled electronic back-to-back converter. The proposed sensorless controller includes a hybrid PLL with a dynamically adjustable tabulated gains system and a feedforward frequency estimator. These add-ons allow to precisely track the speed and angle of the rotor shaft for near-zero speeds. This methodology includes the development of analytical models for the structural, magnetic and electrical components. The efficiency and performance of the machine and controller is verified by simulation under different load conditions and high angular speed variability of a 1.5 kW scale prototype in JMAG and Matlab & Simulink™ environments, reaching an efficiency of 80%.

Gyroid minimal surface-based composite porous structure with superior mechanical property via triangular grid design and stress distribution optimization

Triply periodic minimal surface structures (TPMS) possess excellent printability during additive manufacturing processing and mechanical properties. However, for TPMS shell structure due to the single connected regions, the porosity and connectivity become limited on the premise of mechanical property. In this study, triangular grid-based design of Gyroid composite porous structure (CPS) and optimized CPS through assigning diameter based on stress distribution were proposed for obtaining higher porosity and improved mechanical properties, following the analysis of curvature distribution characteristics. Afterwards, finite element simulation and quasi-static compression tests were performed for studying the stress distribution and mechanical responses. The results showed that the designed Gyroid CPS with high porosity did not obviously destroy the original curvature characteristic, while strength, modulus and specific energy absorption were enhanced simultaneously. It is expected to provide beneficial inspiration for the design and application of TPMS-based porous structures with the integration of high porosity and mechanical property.

Method for spatiotemporal wind power generation profile under hurricanes: U.S.-Caribbean super grid proposition

Wind turbines hit by hurricanes produce high variability of power generation profile. This research proposes a method to estimate this variability and solutions to smooth it. The method calculates the hurricane wind-speed profile in each turbine by Holland's parametric equation in spatiotemporal steps of the hurricane trajectory. The calculated wind speed profile is converted into a power generation profile using wind turbine characteristic curves. Since the simulations show high variability of power profile, this research investigates two strategies to smooth such variability. The first one is systemic. A U.S.-Caribbean super grid interconnecting the Caribbean islands with the U.S. power grid by submarine high voltage direct current (HVDC) cables is proposed. This super grid shows technical feasibility since the proposed route of cables meets some installation criteria, such as a maximum water depth of 3 km and cable length not exceeding 879 km. The U.S.-Caribbean super grid reduces power profile variability by draining the wind power peak caused by hurricanes passing through the Caribbeans and transmitting it to the US power grid by the Florida-Bahamas HVDC interconnector. Another strategy, with special turbines, was tested to evaluate a potential reduction in power variability. However, the special turbines with a high cutout speed showed a limited effect on reducing the variability compared to the U.S.-Caribbean super grid. The proposed power profile estimation method is an essential tool for planning, preliminary design, and reinforcements of high voltage grids in hurricane-prone regions with wind power capacity.

Space-filling single square and square fractal grids induced turbulence: Reynolds stress model parameters-optimization

The employment of grid-induced turbulent flow structures as a passive means of augmenting solid-fluid heat transfer is receiving considerable attention, especially in HVAC applications. However, there presently exists a gap in simulation approaches, where industry-accessible CFD packages are unable to accurately express crucial second-order turbulent flow statistics generated by space-filling single square grids (SSGs) and square fractal grids (SFGs). The present study reports a successful application of a revised Reynolds Stress Model (RSM), which accurately replicates the streamwise distributions of centerline mean flow velocity and turbulence intensity in the lee of one SSG (operating under three different flow Reynolds number ReDh) and five geometrically different SFG test cases after undergoing Nelder-Mead downhill simplex optimization of key RSM kernel parameters. The optimized RSM presents a disagreement of, at worst, 4.30% and 9.98%, respectively against experimental hot-wire anemometry measurements of first-order and second-order statistics, and is the first known instance of the RSM being validated for turbulence intensity predictions of SSG- and SFG-induced turbulence. Examination of RSM parameters reveals that the pre-factors for the rates of turbulence dissipation production and destruction (C1,ε and C2,ε) hold greatest effect on simulation accuracy, with additional optimization of the turbulent viscosity pre-factor (Cμ) required for SFG cases. This is attributed to the effect of enhanced turbulent transport due to the cascading and multiscale nature of SFG turbulence, which insofar could not be replicated by Reynolds-Averaged Navier-Stokes (RANS) models. The values of optimized C1,ε, C2,ε, and Cμ range between 1.057 to 1.697, 2.226 to 2.556, and 0.17 to 2.27, respectively. This leads to the largest deviation of −26.6%, 33.1%, and 200% for C1,ε, C2,ε, and Cμ, respectively, when compared to their corresponding default values. With regards to the sensitivity of this parameter set on grid design, it is shown that the grid's fractal iteration number N and thickness ratio tr have greatest influence on the variation of C1,ε, C2,ε, and Cμ, while the effect of ReDh is insignificant. Overall, this study presents an alternative approach to capture the anisotropic and inhomogeneous nature of SSG- and SFG-induced turbulence for industrial heat-transfer applications via an accessible RANS package, which was previously constrained to expensive DNS and LES studies.

Electricity consumption and load prediction method for Chinese rural residences based on the randomness and seasonality in electricity usage behavior

Electricity consumption and load prediction, and the influence laws of usage behavior are essential for smart grid and policy guidance. This paper presents an electricity consumption and load prediction method based on a stochastic model considering the randomness and seasonality in the usage behavior of appliances, with the aim of exploring the influence laws of the usage behavior. According to the proposed method, a model was developed and verified by taking certain regional rural residences as examples, and the influence of model inputs on electricity consumption and load were explored. The results showed that the modeled total electricity consumption of individual and regional rural residences were consistent with the actual values. The prediction accuracy of the model could be improved by more than 30% compared with the deterministic model results. Furthermore, the model could reasonably capture the electricity load profiles on a daily as well a seasonal basis. Our research provides a comprehensive framework to predict the electricity consumption and load for Chinese rural residences from sampling and data acquisition to model development, and to preliminarily explore the power demand characteristics and significant influencing factors, which may provide valuable data for power grid design and photovoltaic power generation systems.

Study on Maintenance and Test Method of Primary Equipment in modern substation

In the modern social and economic development, residents and industry more and more high demand for electricity utilization, electricity quality requirements increase, so in order to ensure the safety and stability operation of substation, to strengthen the supervision of power system at the same time, attach importance to an equipment maintenance and test work, and integrate the past problem effective prevention measures are put forward. In substation work state, a device as a foundation for the application of grid design content, practice quality directly affect the efficiency and safety of power grid, so this article in the understanding of modern substation operation condition, on the basis of an equipment and maintenance according to the common sense, key research with computer technology platform as the core equipment maintenance and testing methods, This provides an effective basis for ensuring the long-term development of electric power enterprises.

The Design of DC Micro Grid with a Load-Based Battery Discharge Method for Remote Island Electrification Utilizes Marine Currents and Solar Photovoltaic

This paper presents the design of DC micro grid with a load-based battery discharge method for remote island electrification utilising marine currents and solar photovoltaic. To anticipate the intermittent, a load-based battery discharge method is proposed. A centralized battery storage is sized according to the unfilled load demand by the marine current and the solar PV. Thus, the length of the turbine diameter is varied to meet the optimum system size. Hourly data of marine current speed from Cipalulu Strait in Maluku, Indonesia is provided. Data at a typical time, shows that the marine current peak power occurs every 6 hours perday, whereas the PV is at noon. The loads divide into 6 categories, including household 1, household 2, villagse office, school, mosque, and public health center with the peak demand as 112 kW and 856 kWh perday. All loads, mainly for lightings and electronic equipment work in 24 V DC through converters. The distribution network employs 320 V DC connecting from the power plan to the community residents. Simulations demonstrate that the battery size, solar PV, and turbine radius matches to meet the loads. Simulations also show that the battery utilization meets its current and capacity, meaning that an optimum size and filling the load profile can be smoothly conducted.