Virtual State Estimation Calculator Model for Three Phase Power System Network

The main objective of this research work is to develop a simple state estimation calculator in LabView for three phase power system network. LabView based state estimation calculator has been chosen as the main platform because it is a user friendly and easy to apply in power systems. This research work is intended to simultaneously acclimate the power system engineers with the utilization of LabView with electrical power systems. This proposed work will discuss about the configuration and the improvement of the intelligent instructional VI （virtual instrument） modules in power systems for state estimation solutions. In the proposed model state estimation has been carried out and model has been developed such that it can accommodate the latest versions of state estimation algorithm.

基于System Generator的卷积加速结构设计与实现

为解决卷积神经网络中卷积运算耗时长、运算复杂的问题,针对卷积运算的并行性特征,提出一种基于分块的流水线加速方法,并基于该方法在System Generator上进行了电路设计。通过在FPGA(Field-programmable Gate Array)上进行实验验证,该设计模型能正确输出卷积运算结果;在结构和输入数据相同的情况下,该设计模型在计算速度上相比于普通CPU最高可加速258倍,相比于服务器级CPU提高了近40倍,具有良好的加速效果。

Neural Network-Powered License Plate Recognition System Design

The development of scientific inquiry and research has yielded numerous benefits in the realm of intelligent traffic control systems, particularly in the realm of automatic license plate recognition for vehicles. The design of license plate recognition algorithms has undergone digitalization through the utilization of neural networks. In contemporary times, there is a growing demand for vehicle surveillance due to the need for efficient vehicle processing and traffic management. The design, development, and implementation of a license plate recognition system hold significant social, economic, and academic importance. The study aims to present contemporary methodologies and empirical findings pertaining to automated license plate recognition. The primary focus of the automatic license plate recognition algorithm was on image extraction, character segmentation, and recognition. The task of character segmentation has been identified as the most challenging function based on my observations. The license plate recognition project that we designed demonstrated the effectiveness of this method across various observed conditions. Particularly in low-light environments, such as during periods of limited illumination or inclement weather characterized by precipitation. The method has been subjected to testing using a sample size of fifty images, resulting in a 100% accuracy rate. The findings of this study demonstrate the project’s ability to effectively determine the optimal outcomes of simulations.

A Neuro T-Norm Fuzzy Logic Based System

In this study, we are first examining well-known approach to improve fuzzy reasoning model (FRM) by use of the genetic-based learning mechanism [1]. Later we propose our alternative way to build FRM, which has significant precision advantages and does not require any adjustment/learning. We put together neuro-fuzzy system (NFS) to connect the set of exemplar input feature vectors (FV) with associated output label (target), both represented by their membership functions (MF). Next unknown FV would be classified by getting upper value of current output MF. After that the fuzzy truths for all MF upper values are maximized and the label of the winner is considered as the class of the input FV. We use the knowledge in the exemplar-label pairs directly with no training. It sets up automatically and then classifies all input FV from the same population as the exemplar FVs. We show that our approach statistically is almost twice as accurate, as well-known genetic-based learning mechanism FRM.

Review on the Usage of Synchronous and Asynchronous FIFOs in Digital Systems Design

First-Input-First-Output (FIFO) buffers are extensively used in contemporary digital processors and System-on-Chips (SoC). There are synchronous FIFOs and asycnrhonous FIFOs. And different sized FIFOs should be implemented in different ways. FIFOs are used not only for the pipeline design within a processor, for the inter-processor communication networks, for example Network-on-Chips (NoCs), but also for the peripherals and the clock domain crossing at the whole SoC level. In this paper, we review the interface, the circuit implementation, and the various usages of FIFOs in various levels of the digital design. We can find that the usage of FIFOs could greatly facilitate the signal storage, signal decoupling, signal transfer, power domain separation and power domain crossing in digital systems. We hope that more attentions are paid to the usages of synchronous and asynchronous FIFOs and more sophististicated usages are discovered by the digital design communities.

A New Approach for the Health Assessment of River Systems Based on Interconnected Water System Networks

Interconnected river system networks is a national water conservancy strategy in China and focus of research. Here we discuss the classification system, material and energy exchange between rivers and lakes, various dynamic flows and ecological functions of river-lake interconnected relationships. We then propose a novel method for the health assessment of river systems based on interconnected water system networks. In a healthy river system there is ＂material and energy exchange＂ and it is the first and foremost relationship of material and energy exchange between rivers and lakes. There are unobstructed various ＂flows＂ between rivers and lakes including material flows （water, dissolved substances, sediments, organisms and contaminants）, energy flows （water levels, flow and flow velocity）, information flows （information generated with water flows, organisms and human activities） and value flows （shipping, power generation, drinking and irrigation）. Under the influences of na- ture and human activity, various flows are connected by river-lake interconnection to carry material and energy exchange between rivers and lakes to achieve river-lake interactions. The material and energy exchange between rivers and lakes become one of the approaches and the direct driving forces of changes in river-lake interconnected relationships. The benignant changes in river-lake interconnected relationship tend to be in relatively steady state and in ideal dynamic balance.

Impact of power system network topology errors on real-time locational marginal price

This paper examines the impact of power transmission network topology change on locational marginal price(LMP) in real-time power markets. We consider the case where the false status of circuit breakers(CBs) that bypass topology error processing can generate an incorrect power system network topology, subsequently distorting the results of the state estimation and economic dispatch.The main goal of this paper is to assess the economic impact of this misconfigured network topology on realtime LMP in an entire power system with network congestion. To this end, we start with our prior result, a simple and analytical congestion price equation, which can be applied to any single line congestion scenario. This equation can be extended to better understand the degree to which the LMP at any bus changes due to any line status error. Furthermore, it enables a rigorous analysis of the relationship between the change in LMP at any bus with respect to any line error and various physical/economical grid conditions such as the bidding prices for marginal generators and the locations of the congested/erroneous lines. Numerical examples on the impact analysis of this topology error are illustrated in IEEE 14-bus and 118-bus systems.

End-to-End Auto-Encoder System for Deep Residual Shrinkage Network for AWGN Channels

With the rapid development of deep learning methods, the data-driven approach has shown powerful advantages over the model-driven one. In this paper, we propose an end-to-end autoencoder communication system based on Deep Residual Shrinkage Networks (DRSNs), where neural networks (DNNs) are used to implement the coding, decoding, modulation and demodulation functions of the communication system. Our proposed autoencoder communication system can better reduce the signal noise by adding an “attention mechanism” and “soft thresholding” modules and has better performance at various signal-to-noise ratios (SNR). Also, we have shown through comparative experiments that the system can operate at moderate block lengths and support different throughputs. It has been shown to work efficiently in the AWGN channel. Simulation results show that our model has a higher Bit-Error-Rate (BER) gain and greatly improved decoding performance compared to conventional modulation and classical autoencoder systems at various signal-to-noise ratios.

Multi-Head Attention Spatial-Temporal Graph Neural Networks for Traffic Forecasting

Accurate traffic prediction is crucial for an intelligent traffic system (ITS). However, the excessive non-linearity and complexity of the spatial-temporal correlation in traffic flow severely limit the prediction accuracy of most existing models, which simply stack temporal and spatial modules and fail to capture spatial-temporal features effectively. To improve the prediction accuracy, a multi-head attention spatial-temporal graph neural network (MSTNet) is proposed in this paper. First, the traffic data is decomposed into unique time spans that conform to positive rules, and valuable traffic node attributes are mined through an adaptive graph structure. Second, time and spatial features are captured using a multi-head attention spatial-temporal module. Finally, a multi-step prediction module is used to achieve future traffic condition prediction. Numerical experiments were conducted on an open-source dataset, and the results demonstrate that MSTNet performs well in spatial-temporal feature extraction and achieves more positive forecasting results than the baseline methods.

Mathematical Modeling and Control Algorithm Development for Bidirectional Power Flow in CCS-CNT System

As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS-CNT) are becoming increasingly critical. Traditional power distribution networks, often limited by unidirectional flow capabilities and inflexibility, struggle to meet the complex demands of modern energy systems. The CCS-CNT system offers a transformative approach by enabling bidirectional power flow between high-voltage transmission lines and local distribution networks, a feature that is essential for integrating renewable energy sources and ensuring reliable electrification in underserved regions. This paper presents a detailed mathematical representation of power flow within the CCS-CNT system, emphasizing the control of both active and reactive power through the adjustment of voltage levels and phase angles. A control algorithm is developed to dynamically manage power flow, ensuring optimal performance by minimizing losses and maintaining voltage stability across the network. The proposed CCS-CNT system demonstrates significant potential in enhancing the efficiency and reliability of power distribution, making it particularly suited for rural electrification and other applications where traditional methods fall short. The findings underscore the system's capability to adapt to varying operational conditions, offering a robust solution for modern power distribution challenges.

Robust H∞ Networked Control for Uncertain Fuzzy Systems with Time-delay

柔韧的 H 联网了控制方法因为有无常和时间的模糊系统推迟的 Takagi-Sugeno (T-S ) 被介绍。一个州的反馈控制器经由联网的控制系统(NCS ) 被设计理论。为有 H 性能的柔韧的稳定性的足够的状况被获得。在网络传播和包退学学生的导致网络的延期被分析。模拟结果显示出这个控制计划的有效性。

Design, Analysis and Real-time Implementation of Networked Predictive Control Systems

这份报纸用预兆的控制策略涉及设计，分析和联网的控制系统的即时实现。联网的控制系统的特征的分析被详细说明，它证明一个联网的控制系统与常规控制系统不同。完成靠近环的联网的控制系统的需要的性能，联网的预兆的控制计划被介绍。设计，稳定性分析和联网的预兆的控制系统的即时实现被学习。它被联网的预兆的控制计划能补偿随机的网络通讯延期和数据退学学生的模拟和实际实验说明，完成需要的控制性能并且有好靠近环的稳定性。

Stability analysis and controller design for a class of delay systems via observer based on network

This paper focuses on the problem of stability analysis and controller design for a class of delay systems based on networked control systems. By introducing some free matrix variables, some criteria for stability analysis and observer-based control law design can be obtained by the solving of linear matrix inequalities. A numerical example is also offered to prove the effectiveness of the proposed method.

Developing a comprehensive evaluation method for Interconnected River System Network assessment:A case study in Tangxun Lake group

The Interconnected River System Network (IRSN) plays a crucial role in water resource allocation, water ecological restoration and water quality improvement. It has become a key part of the urban lake management. An evaluation methodology system for IRSN project can provide important guidance for the selection of different water diversion schemes. However, few if any comprehensive evaluation systems have been developed to evaluate the hydrodynamics and water quality of connected lakes. This study developed a comprehensive evaluation system based on multi-indexes including aspects of water hydrodynamics, water quality and socioeconomics. A two-dimensional (2-D) mathematical hydrodynamics and water quality model was built, using NH3-N, TN and TP as water quality index. The IRSN project in Tangxun Lake group was used as a testbed here, and five water diversion schemes were simulated and evaluated. Results showed that the IRSN project can improve the water fluidity and the water quality obviously after a short time of water diversion, while the improvement rates decreased gradually as the water diversion went on. Among these five schemes, Scheme V showed the most noticeable improvement in hydrodynamics and water quality, and brought the most economic benefits. This comprehensive evaluation method can provide useful reference for the implementation of other similar IRSN projects.

Robust control for a class of nonlinear networked systems with stochastic communication delays via sliding mode conception

This paper deals with the robust control problem for a class of uncertain nonlinear networked systems with stochastic communication delays via sliding mode conception （SMC）. A sequence of variables obeying Bernoulli distribution are employed to model the randomly occurring communication delays which could be different for different state variables. A discrete switching function that is different from those in the existing literature is first proposed. Then, expressed as the feasibility of a linear matrix inequality （LMI） with an equality constraint, sufficient conditions are derived in order to ensure the globally mean-square asymptotic stability of the system dynamics on the sliding surface. A discrete-time SMC controller is then synthesized to guarantee the discrete-time sliding mode reaching condition with the specified sliding surface. Finally, a simulation example is given to show the effectiveness of the proposed method.

Survey on the stability of networked control systems

The insertion of the communication network in the feedback control loop makes the analysis and design of a network control system more complex, and induces some issues that degrade the control system＇s performance and even cause system instability. The main aspects are focused on the stability analysis of Network Control Systems （NCSs） with network-induced delays, data packet dropouts, and multiple-packet transmission. These issues must be considered in the design of an NCS. This work summarizes the main research results, and remarks on some related handling approaches and techniques. The main purpose of the survey is to present the new research state of NCSs and to point out some fields of future work.

SDNMS: A Software Defined Network Measurement System for NFV Networks

As a promising technology to completely transform how we architect, deploy, operate and manage various networks, software-based Network Function Virtualization(NFV) enables hardware-independent, flexible, fast and efficient network service provision. With the increasing popularity of NFV paradigm, the Internet has also transformed to be a hybrid environment where NFV-based network entities coexist with traditional network devices. To facilitate our understanding, design, evaluate and manage of such novel network environment, there is a great need for a new NFV-compatible network measurement system which is still in absent so far. To bridge this gap, a system, named Software Defined Network Measurement System(SDNMS), is presented in this paper. Firstly, the architecture of SDNMS is proposed. In this architecture, a formal method to describe the working mode of the network measurement is defined. This method can also be utilized to generate a network measurement middle box(NMMB) in a specific location of the NFV network according to the customized description file, and to flexibly deploy the network measurement function. Secondly, the technology of virtual network measurement function(VNMF) combined with LXC is studied to form NMMB function. Thirdly, a control method is presented to control the start, stop, and update NMMB to form a specific network measurement system function. Finally, a prototype of SDNMS with network monitoring function to monitor network performance anomalies and locate faults is introduced. Experimental results have shown that SDNMS architecture and related technologies are feasible and effective to deploy and control network measurement functions in NFV networks. We hope SDNMS could provide a new method for practitioners to conduct network management and research at the age of NFV.

Stochastic stability of networked control systems with network-induced delay and data dropout

This paper deals with the stochastic stability of networked control systems with the presence of network- induced delay and transmitted data dropout. Based on the Lyapunov approach, sufficient conditions for the mean-square stability of the networked control system are derived subject that the sequence of transmission interval is driven by an identically independently distributed sequence and by a finite state Markov chain, respectively. Stabilization controllers are constructed in terms of linear matrix inequalities correspondingly. An example is provided to illustrate our results.

Robust stability analysis of networked control systems

This paper is concerned with the problem of robust stability analysis for networked control systems （NCSs）. A new NCS model is proposed under consideration of both the network-induced delay and parameter uncertainties. The parameter uncertainties appearing in NCSs are norm-bounded, and possibly time-varying. The conventional method and the descriptor system method are used to obtain maximum allowable delay bound （MADB） guaranteeing robust stability and stability of the NCSs, respectively, where the stability criteria are formulated in terms of linear matrix inequalities （LMIs）. And the MADB can be derived by solving the feasibility problem of the corresponding LMI. Some numerical examples are provided to illustrate the effectiveness of the proposed method.