Distributed Real-time Systems Research Articles

Implementation of Technological Upgradation in Public Distribution System in India for Ensuring Availability, Accessibility and Affordability

The largest initiative to reduce poverty in India is the public distribution system (PDS), which uses a network of fair-pricing shops to supply highly subsidised food grains in order to fulfil necessities of households living below poverty line. PDS's primary objective is to buy food grains from farmers. This is to ensure that grain is distributed, stored, and transported so that people in need have access to food. The Indian government has thus upgraded the PDS's technology in an attempt to increase its transparency. To close this gap between technology and citizen benefits, e-government makes use of technical intermediaries like ration Integrated Weight Management System (IWMS), Management Information System (MIS), Inventory management system, etc. The focus of the government is to enact a number of administrative and technological changes under the centralised online real-time electronic public distribution system in order to empower end users of the PDS supply. In this context this paper deals with the number of difficulties when distribution system switches from manual to automated transactions, dealer of fair price shop, who employs the technologies. Based on secondary literature, the objective of this paper is to understand the challenges associated with implementing technology at the point of sale during distribution, as well as study the status of the implementation technological based distribution system. Int. J. Soc. Sc. Manage. Vol. 11, Issue-(1-2): 1-6.

A Deterministic Embedded End-System Tightly Coupled With TSN Schedule

Distributed real-time systems (DRTS) composed of many embedded end-systems have been widely adopted in the industrial fields. Time-sensitive Networking (TSN), as a promising communication infrastructure for DRTS, has shown great potential in industry and academia. TSN assumes that an end-system can release critical tasks to process critical packets strictly according to the pre-scheduled time. Unfortunately, two factors currently damage this assumption: (1) the jitter caused by system architecture during task release, task execution and packet transmission; (2) a TSN schedule result may exceed the execution capability of the end-system and cause conflicts. This paper proposed DetChip, a system-on-chip capable of deterministically implementing the TSN schedule result. DetChip supports time-triggered task release, time-predictable task execution and precise network transmission. Based on DetChip, this paper first formalizes the execution capability of the end-system as end-system constraints (ECs). Existing TSN scheduling algorithms integrating ECs can solve conflicts by co-scheduling end-systems and the TSN network. Compared with previous works, DetChip only introduces few clock cycles jitter for critical task execution according to the TSN schedule result. The proposed ECs obtain 2 8x more conflict-free solutions for advanced scheduling algorithms with a linear increase in time overhead. Compared with the general end-system, DetChip can reduce 6 20x processing jitter to achieve better clock synchronization.

A Novel Electric Vehicle Placement Index for Sustaining Power Quality in a Distribution Network: Proper Allocation of Electric Vehicle Charging Stations

Large-scale deployment of electric vehicles (EVs) has adverse effects on distribution network operations. Inappropriate installation of EV charging stations (EVCS) degrades the distribution network’s power quality, affecting smooth functioning. This article proposes a novel strategy for properly allocating EVCS in a distribution system by analyzing the impact of power quality issues, namely harmonics and loss of life of the distribution transformer. The analysis is carried out in a standard IEEE-33 bus radial distribution system and a real-time distribution system in Kerala, India. The impact of power quality issues is highlighted by perceiving the effect of slow/moderate and fast chargers in the system under study. The results substantiate the potency of the reliability index (RI) strategy. The severity level for planning the charging station (CS) in numerous buses in the distribution network without infrastructural upgrades is determined by employing a modified novel EV placement index (EVPI <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> _m </i> ). The novelty of the index lies in the fact that it incorporates all of the operational parameters with a specific focus on the power quality issues in the distribution network. The severity level of the EVPI <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> _m </i> maintains the power quality without increasing the rating of the components used or any infrastructural upgrades. The sensitivity analysis results prove the robustness of the modified EVPI-based strategy. Moreover, the proposed strategy is validated using real-time experiments on a hardware-in-loop real-time simulator, OPAL-RT OP4510. The results substantiate the efficacy of the strategy and the modified index.

Real-time wavelet-based distribution systems disturbances detection

Real-time wavelet-based distribution systems disturbances detection

Effective Power Loss Management in the Distribution System by the Hybrid Cuckoo Search Grey Wolf Optimizer

One of the most convoluted parts of an electrical power system is its distribution system. Compared to generation and transmission losses, distribution losses are very high in the vertically integrated power system. A modern smart grid involves bidirectional power flow due to Renewable Distributed Generations (RDGs). Integration of RDGs near the load points results in a reduction in the distribution losses. This paper proposes the new Hybrid Cuckoo Search Grey Wolf Optimizer (HCSGWO) to optimally place the RDGs such as Solar Photo Voltaic and Fuel Cells and Capacitor Banks (CBs) for the improvement of voltage profiles in each bus and minimization of losses. The hybrid algorithm utilizes the advantages of both the Cuckoo Search and Grey Wolf algorithm. The proposed approach is tested with the Standard IEEE 33-bus system and the real-time TN 84-bus distribution system at all load models such as constant current, constant power, and constant impedance. The HCSGWO minimizes the system losses by optimally placing both the RDGs and CBs when compared to other algorithms. Losses are reduced by installing CBs in the real-time system and significant improvement is achieved in the voltage levels of each bus in the system.

Simultaneous Robust State Estimation, Topology Error Processing, and Outage Detection for Unbalanced Distribution Systems

This paper proposes an efficient algorithmic approach that overcomes the critical challenges in real-time unbalanced distribution system state estimation, topology error processing, and outage identification simultaneously. These challenges include (1) limited locations of measurement devices and unsynchronized measurement data as well as missing and bad data, (2) complicated mixed-phase switch actions and mutual impedances and shunt admittances, and (3) the nonlinear nature of unbalanced distribution system power flow with distributed energy resources (DERs). A single snap-shot mixed-integer quadratic programming (MIQP) optimization framework is proposed to cope with these challenges, which simultaneously identifies real-time network topology, estimates system state, and detects the outages via analytical constraints. An AC optimal power flow (ACOPF) approach is proposed to accurately model unbalanced distribution systems. In the proposed MIQP formulation, nonlinearities due to the complicated mixed-phase switch operations and the ACOPF approach are linearized. The effectiveness of the proposed approach is verified on an actual distribution feeder in Arizona. The results illustrate that the proposed model is robust, accurate, and computationally efficient for implementation in a distribution management system (DMS).

The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients

Astrophysical transients with rapid developments on subhour timescales are intrinsically rare. Due to their short durations, events like stellar superflares, optical flashes from gamma-ray bursts, and shock breakouts from young supernovae are difficult to identify on timescales that enable spectroscopic follow-up. This paper presents the Evryscope Fast Transient Engine (EFTE), a new data reduction pipeline that is designed to provide low-latency transient alerts from the Evryscopes—a north–south pair of ultra-wide-field telescopes with an instantaneous footprint covering 38% of the entire sky—and tools for building long-term light curves from Evryscope data. EFTE leverages the optical stability of the Evryscopes by using a simple direct image subtraction routine that is suited to continuously monitoring the transient sky at a cadence of a minute. Candidates are produced within the base Evryscope 2 minute cadence for 98.5% of images, and internally filtered using vetnet, a convolutional neural network real–bogus classifier. EFTE provides an extensible and robust architecture for transient surveys probing similar timescales, and serves as the software test bed for the real-time analysis pipelines and public data distribution systems for the Argus Array, a next-generation all-sky observatory with a data rate 62 times higher than that of Evryscope.

Real-Time Topology Estimation for Active Distribution System Using Graph-Bank Tracking Bayesian Networks

Real-time topology estimation in distribution grid with high penetration of distributed energy resources remains a challenging task due to the insufficient high-precision measurements and frequent topology variations. This article proposes a real-time distribution system topology estimation approach building on the graph theory and Bayesian networks with sparse measurements. The graph theory develops the topology graph bank to effectively leverage the prior knowledge of topology models, including the topology structure and the switching relationship between different topologies. This allows the development of the Bayesian networks for topology tracking using real-time voltage and power injection measurements. A novel discrete method considering the similarity of data correlation information is proposed for the optimal placement of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i> PMUs to ensure the performance of topology estimation. Numerical results on the IEEE 33-node and 123-node systems show that the BN-based topology estimation model has better performance against incomplete information, i.e., missing data, than other alternatives.

Composable distributed real-time systems with deterministic network channels

A system that needs to interact with the physical world in a timely manner is called a real-time system. When such a system is composed of multiple subsystems, or nodes, each of which is a geographically separate system, such a system of systems is called a distributed real-time system. The computation at each node must adhere to the timing requirements, and the connecting communication channels must never cause delays that trigger further timing violations. In this paper, we introduce Deterministic Network Channels, a network construct using Time Sensitive Networking QoS mechanisms that add reliable and deterministic communication for distributed tasks. Introducing such network channels as a construct allows designers to focus on higher-level primitives when building distributed systems. We describe our reference implementation and evaluate it by extending Timed C with network channels. Building on this, we also perform a thorough performance evaluation to determine practical bounds for both Linux and TSN under heavy workloads and adverse network conditions to show how the proposed reference implementation performs in real-world scenarios. In our tests, we can synchronize two separate machines running commercial off-the-shelf hardware to within 15μs of each other under severe internal and external interference.

PMU-based Real-time Distribution System State Estimation Considering Anomaly Detection, Discrimination and Identification

In this paper, a real-time state estimation platform for distribution grids monitored by Phasor Measurement Units (PMUs) is developed, tested, and validated using Real Time Digital Simulator (RTDS). The developed platform serves as a proof-of-concept for potential implementation in an existing 50 kV ring network of the Dutch distribution utility Stedin medium voltage distribution grid located in the southwest (Zeeland area) of the Netherlands. To catch up with the fast sampling rates of PMUs, the platform incorporates computationally efficient techniques for state estimation and detection, discrimination and identification of anomalies like bad data and sudden load changes. Forecasting Aided State Estimation has been utilized to enable measurement innovations needed for fast anomaly detection, discrimination, and identification, whilst the Extended Kalman Filter (EKF) algorithm is selected to provide fast state forecasting and filtering. The platform has been tested under various normal and abnormal operating conditions considering different statistical properties of measurement noise as well as different bad data and sudden load change scenarios. To demonstrate advantages and disadvantages for embedding EKF into the platform, EKF is compared with Unscented Kalman Filter (UKF) in terms of estimation accuracy, computational efficiency, and compatibility with the module for anomaly detection, discrimination, and identification. The results of extensive simulations provide good hints about the feasibility of PMU-based real-time state estimation for the Stedin distribution grid.

Industrial Shared Wireless Communication Systems—Use Case of Autonomous Guided Vehicles with Collaborative Robot

Dedicated fieldbuses were developed to provide temporal determinisms for industrial distributed real-time systems. In the early stages, communication systems were dedicated to a single protocol and generally supported a single service. Industrial Ethernet, which is used today, supports many concurrent services, but usually only one real-time protocol at a time. However, shop-floor communication must support a range of different traffic from messages with strict real-time requirements such as time-driven messages with process data and event-driven security messages to diagnostic messages that have more relaxed temporal requirements. Thus, it is necessary to combine different real-time protocols into one communication network. This raises many challenges, especially when the goal is to use wireless communication. There is no research work on that area and this paper attempts to fill in that gap. It is a result of some experiments that were conducted while connecting a Collaborative Robot CoBotAGV with a production station for which two real-time protocols, Profinet and OPC UA, had to be combined into one wireless network interface. The first protocol was for the exchange of processing data, while the latter integrated the vehicle with Manufacturing Execution System (MES) and Transport Management System (TMS). The paper presents the real-time capabilities of such a combination-an achievable communication cycle and jitter.

How windows size and number can influence the schedulability of hierarchically-scheduled time-partitioned distributed real-time systems

Partitioning techniques are implemented in the development of safety-critical applications to ensure isolation among components. An adequate scheduling of the execution of such partitions is a key challenge so that applications meet the hard deadlines imposed. In this work, we study the effect of different partition window configuration parameters, with the aim of analyzing their impact in the worst-case response times of system tasks. This is the first step in the development of an algorithm for optimizing partition windows in hierarchically-scheduled time partitioned distributed systems.

A Mathematical Approach of Voltage Sag Analysis Incorporating Bivariate Probability Distribution in a Meshed System

In this paper, different mathematical expressions are derived to compute the residual magnitude of voltage caused by faults along the line and on the bus. Symmetrical and unsymmetrical faults are taken into consideration, and the consequences of the various fault distributions are considered. A new way of assessing a sag is proposed that incorporates the method of fault position and mathematical expression based on sequence currents and voltages. The fault impedance is introduced to obtain a better result. A fast and efficient load flow analysis technique produces quick computational results. In addition, the sag analysis is performed using the bivariate joint discrete probability distribution method that gives a clear idea about the probability of occurrence of sag in a meshed network. The suggested approach is applied in the IEEE 39-bus system and with an existing real-time electrical power distribution system in India.

EDF scheduling for distributed systems built upon the IEEE 802.1AS clock - A theoretical-practical comparison

Existing response time analysis and optimization techniques for real-time distributed systems show that EDF schedulers feature better scheduling capabilities when a global clock reference can be used; this form of scheduling is known as global-clock EDF. In this context, precise clock synchronization is an enabling technology for future distributed real-time systems that want to leverage EDF scheduling. The IEEE 802.1AS protocol can be considered a stable technology for this purpose, as it is part of the Time-Sensitive Networking (TSN) family of standards to provide real-time communication over Ethernet. This paper presents a system architecture for applying global-clock EDF scheduling in distributed systems with soft real-time requirements. It also presents experiments to (1) assess the synchronization capabilities of the clock synchronization mechanism in the proposed architecture, (2) evaluate the performance of different scheduling deadline assignment techniques, and (3) contrast the theoretical results obtained by the schedulability analysis against those obtained through the execution of these experiments.

RDC-SLAM: A Real-Time Distributed Cooperative SLAM System Based on 3D LiDAR

To improve the accuracy and efficiency of 3D LiDAR mapping, real-time cooperative SLAM has been considered to explore large and complex areas. To merge the individual maps from multiple robots, it is crucial to identify the common areas and obtain alternative matches between them. However, data transmission, especially in sparse networks with narrow bandwidth and limited range, is a challenging issue for the above problem. Since the distribution manner is suitable for limited communication, we proposed a common framework of 3D real-time distributed cooperative SLAM to fill the community gap. Assuming that each robot can communicate with others, the presented framework consists of four key modules: place recognition, relative pose estimation, distributed graph optimization, and communication. Meanwhile, we developed a complete real-time distributed cooperative SLAM system, called RDC-SLAM, by integrating state-of-the-art components into the framework. For computation and data transmission efficiency, descriptor-based registration is used instead of the conventional point cloud matching. An intensity-based descriptor is developed to perform the place recognition and obtain the alternative matches, while an eigenvalue-based segment descriptor is applied to further refine the relative pose estimations between these alternative matches. A distributed graph optimization method is utilized to obtain the maximum likelihood of multi-trajectory estimation. A communication protocol is also designed to associate data among robots that are easy to deploy and have low network requirements. The RDC-SLAM is validated by real-world experiments and exhibits superior performance concerning accuracy, computation efficiency, and data efficiency.

Partition window assignment in hierarchically scheduled time-partitioned distributed real-time systems with multipath flows

Time and space partitioning techniques are implemented in the development of safety-critical applications to ensure isolation among components. A suitable arrangement of the execution of such partitions is a key challenge so that applications meet the timing requirements imposed to software. In this work, the effect of window sizes and context switch overheads in the partition window configuration is studied, with the aim of analyzing their impact when the response-time analysis and priority assignment techniques are applied. Then, a heuristic algorithm is proposed, in order to obtain a partition window configuration that enables the schedulability of partition-based safety critical systems. This algorithm is evaluated in synthetic test scenarios and it is also applied to a safety-critical use-case in the railway domain.

High Accuracy Software-Based Clock Synchronization Over CAN

In distributed real-time communication systems, common knowledge of the global time is crucial. It prevents message violations on the bus and allows independent components to collaborate within a real-time system on a timely basis. Systems with hard real-time requirements need to have high precision and accuracy of time. This is achieved by hardware-supported frame time-stamping mechanisms as found in dedicated protocols, such as time-triggered CAN (TTCAN), Flexray, and time-sensitive networking (TSN)-enabled Ethernet. However, many microcontroller units are not specifically designed to provide such a hardware-based solution at the communication interface. Therefore, a software-based implementation of the time synchronization algorithm is needed. Nevertheless, some commercial off-the-shelf (COTS) microcontroller units already provide an IEEE 1588-enabled Ethernet interface, including a high-precision timer module with rate correction. This module can be used for time synchronization purposes to align a set of distributed clocks via various communication interfaces. This article investigates the accuracy of software-based and hardware-supported time synchronization algorithm over the controller area network (CAN) protocol using a COTS microcontroller. As a result, we present identified jitter and delay sources as well as the achieved time accuracy. We show that using an advanced timer module combined with additional system knowledge allows submicrosecond precision and accuracies.

Anomaly-Aware Adaptive Sampling for Electrical Signal Compression

Intelligent electronic devices for power systems often entail high frequency sampling of electric signals, enabled to capture anomalous signal behavior. However, in normal operation this oversampling is redundant and leads to excessive data being stored or transmitted. This gives rise to a new compression problem where the collected samples should be further subsampled and quantized based on the presence of an anomaly in the underlying signal. We propose an Anomaly-aware Compressive Sampler (ACS) which tests the signal for the presence of an anomaly in a block of samples, and subsamples in a hierarchical manner to retain the desired sampling rate. ACS has been designed keeping hardware constraints in mind, using integer operations, an appropriate bit-packing, a simple iterated delta filter, and a streaming data pipeline. We present a mathematical formulation of the problem and analyze the performance of ACS, establishing theoretically its ability to identify anomalies in the signal and adapt the sampling rate. ACS competes with the state-of-the-art algorithm for the better-behaved transmission system data from DOE/EPRI, and outperforms it significantly on real-time distribution system data recorded in our laboratory. Finally, ACS is lightweight and was implemented on an ARM processor.

Validation of Embedded State Estimator Modules for Decentralized Monitoring of Power Distribution Systems Using IoT Components.

Recent theoretical studies demonstrate the advantages of using decentralized architectures over traditional centralized architectures for real-time Power Distribution Systems (PDSs) operation. These advantages include the reduction of the amount of data to be transmitted and processed when performing state estimation in PDSs. The main contribution of this paper is to provide lab validation of the advantages and feasibility of decentralized monitoring of PDSs. Therefore, this paper presents an advanced trial emulating realistic conditions and hardware setup. More specifically, the paper proposes: (i) The laboratory development and implementation of an Advanced Measurement Infrastructure (AMI) prototype to enable the simulation of a smart grid. To emulate the information traffic between smart meters and distribution operation centers, communication modules, that enable the use of wireless networks for sending messages in real-time, are used, bridging concepts from both IoT and Edge Computing. (ii) The laboratory development and implementation of a decentralized architecture based on Embedded State Estimator Modules (ESEMs) are carried out. ESEMs manage information from smart meters at lower voltage networks, performing real-time state estimation in PDSs. Simulations performed on a real PDS with 208 buses (considering both medium and low voltage buses) have met the aims of this paper. The results show that by using ESEMs in a decentralized architecture, both the data transit through the communication network, as well as the computational requirements involved in monitoring PDSs in real-time, are reduced considerably without any loss of accuracy.

Staged energy and water quality optimization for large water distribution systems.

Simultaneous optimization of energy and water quality in real-time large-sized water distribution systems is a daunting task for water suppliers. The complexity of energy optimization increases with a large number of pipes, scheduling of several pumps, and adjustments of tanks' water levels. Most of the simultaneous energy and water quality optimization approaches evaluate small (or hypothetical) networks or compromise water quality. In the proposed staged approach, Stage 1 uses a risk-based approach to optimally locate the chlorine boosters in a large distribution system based on residual chlorine failures and the associated consequences in different land uses of the service area. Integrating EPANET and CPLEX software, Stage 2 uses mixed integer goal programming for optimizing the day-ahead pump scheduling. The objective function minimizes the pumping energy cost as well as the undesirable deviations from goal constraints, such as expected water demand. Stage 3 evaluates the combined hydraulics and water quality performances at the network level. The implementation of the proposed approach on a real-time large-sized network of Al-Khobar City in Saudi Arabia, with 44 groundwater wells, 12 reservoirs, 2 storage tanks, 191 mains, 141 junctions, and 17 pumps, illustrated the practicality of the framework. Simulating the network with an optimal pumping schedule and chlorine boosters' locations shows a 40% improvement in water quality performance, desired hydraulics performance with optimal pump scheduling, and an average 20% energy cost reduction compared to the normal (unoptimized) base case scenario.