Distribution Automation System Research Articles

New Trends in Pollution Prevention and Control Technology for Healthcare and Medical Waste Disposal in China

This study explores the progression of global healthcare and medical waste (HMW) disposal technologies and emerging practices in China including the COVID-19 pandemic period through patent technology innovation analysis. Trends were identified through both the Derwent Innovation Index database and bibliometric methods. Based on the bibliometric analysis of 4128 patents issued from 2002 to 2021, the development status and research trends of HMW disposal technology were revealed. Regarding patents, China significantly advanced post-2011. However, a large number of applications are filed only in China and are more focused on domestic rather than overseas markets. As the pandemic remains a threat, and increasing amounts of medical waste are generated, new technologies are being sought in China that will be safer for humans and the environment, and will also be in line with the zero waste technology trend. Incineration and waste crushing are core methodologies in medical waste disposal. Future directions pivot towards innovations in large-scale and distributed processing equipment, automation and unmanned systems and high-temperature steam disinfection collaborative disposal methods—including the “High temperature steam–municipal solid waste incineration collaborative technology” and the “High temperature steam–thermal magnetic gasification collaborative technology”. This patent analysis enhances our understanding of the impact of COVID-19 on HMW disposal practices, guiding improved policymaking and research in the HMW sector.

Power Supply Reliability Analysis of Distribution Systems Considering Data Transmission Quality of Distribution Automation Terminals

A distribution automation system is the integration of physical power distribution systems and information systems. Its information system guarantees the safe operation and reliable power supply of physical systems by monitoring, collecting and transmitting information. In the information system, the remote terminal unit of distribution automation is the hub of the information system, connecting it to the physical power system. Considering the unreliability of terminal information transmission in the information system, this paper aims to build a model to quantitatively evaluate the impact of unreliable transmission information on the power supply reliability of distribution systems. Firstly, the m-segment and n-connection unit model of distribution feeders is established, and then, the power supply reliability indices in the process of handling feeder terminal unit error are analyzed and calculated under the configuration modes of “three-remote” and “two-remote” of remote terminals. Then, considering the impact of a transmission error in the information system, the reliability index calibration model under the condition of unreliable information transmission is established. Finally, a case study is presented to illustrate how the proposed model is implemented.

Key technologies of active distribution networks control

Active Distribution Networks (ADNs) are modern and intelligent power distribution systems that integrate renewable energy sources and advanced control technologies to provide reliable, secure, and efficient electricity supply. The traditional power distribution networks are designed to deliver electricity in a one-way flow from the transmission system to the customers. In contrast, ADN enables two-way power flow between the distribution network and customers, allowing them to become active participants in the electricity system. The key technology behind ADN includes advanced metering infrastructure (AMI), Distribution Automation (DA), and energy storage systems (ESS). AMI provides real-time data on electricity consumption, generation, and distribution, enabling efficient load management and demand response. Other key technologies of ADN include renewable energy sources such as solar photovoltaic (PV), Wind turbines and small-scale hydroelectricity. These sources are connected to the distribution network through power electronic interfaces that convert the DC output of the renewable sources into AC for distribution. Smart grid technologies such as microgrids, virtual power plants, and energy management systems are also integrated into ADN to improve grid stability and resilience. ADNs have the potential to transform the electricity system by enabling more efficient, sustainable, and reliable energy systems that can better serve the needs of consumers and society. Thus, ADN is expected to become a critical technology in achieving a cleaner and more sustainable energy future.

Retracted: Optimization of Distribution Automation System Based on Artificial Intelligence Wireless Network Technology

Retracted: Optimization of Distribution Automation System Based on Artificial Intelligence Wireless Network Technology

Distribution networks reliability assessment considering distributed automation system with penetration of DG units and SOP devices

The electric utility industry is moving towards a deregulated and competitive market to meet customer expectations. So, system performance and reliability assessments are getting targeted more than before. Several performance measures of reliability are developed in the literature. In this research, the NEPLAN Simulator reliability analysis module is used to determine all the reliability indices in different cases of study considering the effect of the Advanced Distributed Automation System (ADAS). The analysis also benefits from the presence of Penetration of Distributed Generation (DG) units and Soft Open Points (SOP) to enhance system reliability alongside power quality. Therefore, this paper provides a methodology based on a cost/benefit study for distribution networks to define the best location of DG units and SOP devices that leads to better reliability indices. The objectives of the study are demonstrated and investigated through Bus 4 of the standard reliability Roy Bollington Test System (RBTS). NEPLAN uses a tool to apply the Reliability Centered Maintenance (RCM) strategy, which leads to a substantial reduction of maintenance expenses. Simulation results indicate a significant reduction in system reliability cost by 65.8% with significant enhancement in the average of all reliability indices and at each load point too such as Customer Average Interruption Duration Index (CAIDI) which is improved from 40.899 to 29.883, Energy not supplied also is declined by 52.34%. It is also worth saying that, even using DG units or SOP devices separately leads to positive results but the best outcomes are obtained with an appropriate combination of both.

Research on power supply recovery control technology of distribution network embedding with DC links

The flexible interconnection device (FID) enables multiple distribution feeders in closed-loop mode to support a higher proportion of distributed generation (DG) and large-scale new loads connected to the distribution network (DN). Moreover, the closed-loop operation mode based on FIDs provides an effective technology roadmap for high-quality and highly reliable power users, especially the quick restoration of power supply after the failure of DN. This paper proposes a new supply shape in which the multi-terminal DC links are flexibly embedded in the AC DN (EDC-DN) to realize closed-loop operation, achieving lower investment costs than the existing mode that replaces tie switches with soft open points (SOPs). Meanwhile, a two-stage power supply quick recovery control technology is proposed for the EDC-DN, including the fast power supply recovery stage based on EDC and the optimizing restoration stage based on network reconfiguration. Firstly, the role of EDC in the process of power supply restoration of three different faults on AC feeder is analyzed. Secondly, a detailed power supply recovery process is proposed, which is based on a distribution automation system (DAS) and the real-time control capability of EDC. Thirdly, the power supply restoration second stage is implemented, which is based on network reconfiguration with switch combination and EDC continuous variable optimization. Finally, a 58-node DN with an EDC system was constructed using PSCAD/MTDC simulation software to verify the effectiveness of the two-stage strategy for EDC-DN power restoration.© 2017 Elsevier Inc. All rights reserved.

Operational cost minimization of a microgrid with optimum battery energy storage system and plug-in-hybrid electric vehicle charging impact using slime mould algorithm

Microgrid (MG) with battery energy storage system (BESS) is the best for distribution system automation and hosting renewable energies. The proliferation of plug-in hybrid electric vehicles (PHEV) in distribution networks without energy management (EM) puts additional pressure on the utility and creates challenges for MG. This research article proposes a stochastic expert method to minimize the total operational cost through proper EM of a grid-connected low-voltage MG by considering the charging impact of PHEVs with the optimal size of BESS. Three strategies are used to control the PHEV charging demand. Economically improved performance of MG is obtained as compared to previous research without considering the daily cost of the BESS (fBESS) and operation and maintenance cost of different distributed generation sources (OMcost). Then, the study is extended by incorporating these two parameters into the objective function of operational cost. Finally, this article analyzes to what extent the fBESS and OMcost factors raise the microgrid's operational cost. Due to non-linear optimization issues, the slime mould algorithm (SMA) is proposed, which performed better EM with a lower operational cost of MG than other methods.

Strategies for automating analytical and bioanalytical laboratories

Analytical measurement methods are used in different areas of production and quality control, diagnostics, environmental monitoring, or in research applications. If direct inline or online measurement methods are not possible, the samples taken have to be processed offline in the manual laboratory. Automated processes are increasingly being used to enhance throughput and improve the quality of results. In contrast to bioscreening, the degree of automation in (bio)analytical laboratories is still low. This is due in particular to the complexity of the processes, the required process conditions, and the complex matrices of the samples. The requirements of the process to be automated itself and numerous other parameters influence the selection of a suitable automation concept. Different automation strategies can be used to automate (bio)analytical processes. Classically, liquid handler-based systems are used. For more complex processes, systems with central robots are used to transport samples and labware. With the development of new collaborative robots, there will also be the possibility of distributed automation systems in the future, which will enable even more flexible automation and use of all subsystems. The complexity of the systems increases with the complexity of the processes to be automated.Graphical

Optimal placement of fault indicator and remote‐controlled switches for predetermined reliability of selected buses

AbstractFault indicators (FI) and remotely controlled switches (RCS) can reduce the power outage time in distribution network (DN) by finding and isolating the faulty area. Therefore, they play an important role in reducing the power outage cost and increasing the reliability of the DN. In DN, there may be high‐priority loads. One of the goals of improving and updating the DN is to increase the reliability of all network buses, especially buses feeding such loads. Here, the placement of FI and RCS, as the distribution system automation devices, is designed and modelled to increase the reliability of the buses supplying high‐priority loads. For the placement problem, two goals of cost and reliability have been considered. But the problem is not defined as a multi‐objective optimization. Rather, it is modelled as a one‐objective optimization (i.e. network cost) and constrained to a certain level of reliability in predetermined locations and buses. The IEEE‐33bus network is used as the sample network and different scenarios are simulated. The number of FI and RCS and the optimization cost of simulated scenarios are compared to evaluate the efficiency of the proposed model. The obtained results show the adequacy of the modelling.

A Modular Hardware Design of an Intelligent Distributed Feeder Terminal Unit

The development of a new power system is proposing new requirements for the function of the feeder terminal unit (FTU), which is the core equipment of the distribution automation system. At the same time, the improvement of FTU intelligence brings a new solution to the problem of line loss calculation. Aiming at the problems of complex structure and low measurement accuracy of current FTU, a hardware scheme combining ADC sampling chip and high-performance MCU is proposed in this paper to realize the integrated application of energy measurement function. Moreover, it is equipped with a line loss calculation module to achieve high precision line loss calculation when the metering chip cannot meet the precision requirements. At the same time, the modular design effectively improves the operation reliability and function expansion of the terminal.

Development of fault cause estimation method for distribution line

AbstractWe are planning to develop the new Advanced Distribution Automation System (ADAS) equipped with optical communication network and sectionalizer with sensor for more grid reliability and efficiency on maintenance operation. The new system is featured with the function of fault cause or damaged part estimation. The new sectionalizer captures the waveform of electrical line surge originated by fault and the system analyzes the waveform for this function. This paper mainly introduces the system configuration of ADAS and an early stage examination of fault cause estimation technology.

A Systematic Analysis of Network Bandwidth Sharing in Smart Grid Environment

The integration of Information and Communication Technology (ICT) into modern infrastructure systems has given birth to the concept of “Intelligent Infrastructure,” with the smart grid as a prominent example. The smart management and efficient application of important electricity burden during agricultural production process has been realized by disposing energy efficiency management platform in rural areas. This paper investigates the applicability of grid computing within the context of intelligent infrastructure, with a particular emphasis on the smart grid. Grid computing, a distributed computing paradigm that utilizes the combined computational power of interconnected resources, has the potential to significantly improve the effectiveness, dependability, and sustainability of smart grid operations. In addition, the allocation and distribution of network resources by the grid’s systems will be examined in depth. While downloading gigabyte to terabyte-sized files from the internet, we frequently encounter various technical issues such as ISP restrictions, link expiration, etc In the meantime, the information exchanging has been proposed among the energy efficiency management platform, the distributed energy systems, the distribution automation system and the data acquisition system. Therefore, the intelligent scheduling of distributed energy can be realized in rural production during the peak period of electricity load and the affluent period.

Information model of power distribution IoT terminal for high-rise building electrical fire monitoring

Fires caused by electrical reasons such as short circuits and leakage in low-voltage distribution network lines account for a relatively large proportion of the high-rise building fires. Building an electrical fire monitoring system for high-rise buildings based on the Internet of Things (IoTs) technology can monitor electrical circuits in real-time and reduce electrical fires. Aiming at the interconnection and intercommunication of the information exchange of the IoT terminals in the electrical fire monitoring system of high-rise buildings, this paper firstly analyzes the functional communication requirements of the electrical fire monitoring system of high-rise buildings, and combined with the requirements of functional communication, the information model required for electrical quantity collection and non-electricity collection functions is studied based on IEC 61850, which is conducive to the fusion and application of low-voltage distribution network monitoring data and existing distribution automation system data. At the same time, the location information logical node is established by supplementing, which realizes the determination of the spatial position of the terminal and the sensor, the location of the fire source can be determined by analyzing and calculating according to the spatial location information and the spatiotemporal sequence of the detection information. Finally, the information modeling of different types of monitoring terminal equipment is carried out and the configuration suggestion based on SCL language is proposed. By realizing the integration of low-voltage terminal unit (LTU) into the system and the configuration of LTU, the standard system of IEC 61850 can be actually operated. A monitoring terminal based on the proposed information model has been developed and applied to a building in Wuhan.

Monitoring of the residual life of galvanic batteries

The development of distributed automation systems built on the use of wireless communication channels has led to an increase in the role of autonomous power systems. These systems use so-called CCS - chemical current sources, both rechargeable (accumulators) and non-rechargeable (batteries, or galvanic batteries). Depending on the purpose and operating conditions, the battery life of the same type may be different, and for some automation systems, knowing its current value is critical. An example of such a system is an automated telemetry system for drilling oil and gas wells, in which its constituent modules are powered from an autonomous source based on lithium-thionyl chloride cells. A feature of the system is the presence of several modes of operation, which differ significantly from each other in duration and energy consumption. The article proposes an algorithm for monitoring the residual resource of galvanic batteries, which provides a correct account of the consumed resource for modes of any duration. A feature of the algorithm is the accounting of the consumed resource through the formation and calculation of conditional single portions, the so-called basic electric charge. For this, a double integration of the voltage proportional to the consumed current is used. Checking the proposed algorithm for monitoring the residual life of the CCS in the program for modeling electrical circuits Electronics Workbench confirmed its feasibility.

Condition assessment of distribution automation remote terminal units based on double-layer improved cloud model

Distribution automation remote terminal units (DRTUs) are the most important devices to sample voltage and current signals, identify the fault position, isolate the fault, and restore the power supply along distribution lines. We cannot adopt time-based maintenance because of the contradiction between the limited manpower and the plenty of DRTUs distributed in broad regions. In this paper, a double-layer improved cloud model (ICM) is proposed for the first time to realize the condition assessment of DRTUs for condition-based maintenance. The first-layer ICM is applied in the main station of whole distribution automation system (DAS) to evaluate the condition of all DRTUs based on the upload limited condition parameters by DRTUs in real time. And the second-layer ICM is applied in field to evaluate one DRTU which belongs to the abnormal DRTUs obtained after the first-layer evaluation. The DRTU test device are used to obtain detailed condition parameters, and these parameters are used in second-layer ICM to obtain accurate condition assessment score. The results in second-layer ICM would be used to optimize the evaluation algorithm in the first-layer evaluation. In the meantime, our proposed ICM combines the normal cloud model and the trapezoidal cloud model to deal with the optimal, negative, and intermediate indicators more effectively. The comparison with traditional evaluation methods shows that our proposed method is more suitable to realize the condition assessment of DRTUs in the distribution power networks.

Edge Computing Based Fault Sensing of the Distribution Cables Based on Time-Domain Analysis of Grounding Line Current Signals

Due to the complex structures and fault conditions, accurate fault sensing of the underground distribution cables is a difficult task. The distribution automation system (DAS) and fault indicator system (FIS) are only applicable to the severe faults. In addition, the current DAS and FIS are all based on the centralized data processing system (CDS), increasing the communication pressure and data processing time of the main station. Considering the advantages of edge computing, this paper investigates using the grounding line currents to sense the fault in distribution cable networks. First, an edge computing based fault sensing system (ECS) is designed. The equivalent time-domain distribution cable models considering multi-conductor mutual couplings are then established in both normal and fault cases. The time-domain features of the cable grounding line currents prior to and after the fault are analyzed to create the fault detection criterion. Combining the network topology, locations of the measurement units (MUs), and direction factor of the ground line current, a space matrix based algorithm is created to achieve fault cable section location at edge. Finally, a distribution cable network is created by PSCAD/EMTDC. Various simulations are conducted to validate the effectiveness and robustness of the algorithm.

Security Analysis for Distributed IoT-Based Industrial Automation

Internet of Things (IoT) technologies enable development of reconfigurable manufacturing systems—a new generation of modularized industrial equipment suitable for highly customized manufacturing. Sequential control in these systems is largely based on discrete events, whereas their formal execution semantics is specified as control interpreted Petri nets (CIPN). Despite industry-wide use of programming languages based on the CIPN formalism, formal verification of such control applications in the presence of adversarial activity is not supported. Consequently, in this article, we introduce security-aware modeling and verification techniques for CIPN-based sequential control applications. Specifically, we show how CIPN models of networked industrial IoT controllers can be transformed into time Petri net (TPN)-based models and composed with plant and security-aware channel models in order to enable system-level verification of safety properties in the presence of network-based attacks. Additionally, we introduce realistic channel-specific attack models that capture adversarial behavior using nondeterminism. Moreover, we show how verification results can be utilized to introduce security patches and facilitate design of attack detectors that improve system resiliency and enable satisfaction of critical safety properties. Finally, we evaluate our framework on an industrial case study. Note to Practitioners—Our main goal is to provide formal security guarantees for distributed sequential controllers. Specifically, we target smart automation controllers geared toward Industrial IoT applications that are typically programed in C/C++ and are running applications originally designed in, for example, GRAFCET (IEC 60848)/SFC (IEC 61131-3) automation programming languages. Since existing tools for the design of distributed automation do not support system-level verification of relevant safety properties, we show how security-aware transceiver and communication models can be developed and composed with distributed controller models. Then, we show how existing tools for verification of time Petri nets can be used to verify relevant properties including safety and liveness of the distributed automation system in the presence of network-based attacks. To provide an end-to-end analysis as well as security patching, results of our analysis can be used to deploy suitable firmware updates during the stage when executable code for target controllers (e.g., in C/C++) is generated based on GRAFCET/SFC control models. We also show that security guarantees can be improved as the relevant safety/liveness properties can be verified after corresponding security patches are deployed. Finally, we show applicability of our framework on a realistic distributed pneumatic manipulator.

Development of Fault Cause Estimation Method for Distribution Line

We are planning to develop the new Advanced Distribution Automation System (ADAS) equipped with optical communication network and sectionalizer with sensor for more grid reliability and efficiency on maintenance operation. The new system is featured with the function of fault cause or damaged part estimation. The new sectionalizer captures the waveform of electrical line surge originated by fault and the system analyzes the waveform for this function. This paper mainly introduces the system configuration of ADAS and an early stage examination of fault cause estimation technology.

Optimization of Distribution Automation System Based on Artificial Intelligence Wireless Network Technology

In order to further improve the automation setting of distribution system, this paper proposes an optimization research of distribution automation system based on artificial intelligence wireless network technology. This method uses artificial intelligence wireless network technology to optimize the automation of distribution system and improve the automation ability of distribution system. The experimental results show that when the number of iterations in the training process reaches 338, the mean square error is 0.001. Conclusion. The optimization research method of distribution automation system based on artificial intelligence wireless network technology can more effectively improve the automation level of distribution system.

An automatic fault section identification method based on distributed traveling wave sensors

As electrification deepens and the society relies more and more on electricity, dependability and safety standard of the power distribution system becomes higher and higher. What is more, to minimize carbon emission, high percentage of renewable energy resources penetration is becoming a reality, which further complicates the distribution system. Because of equipment failure, construction mistake and other causes, power system faults are inevitable. Fault section identification and fault isolation is a critical mission in distribution system operation [1]. As the distribution system develops and evolves, two main ways to accomplish this goal were established: (a) Substation overcurrent relay detects the fault and the corresponding substation breaker isolates the fault. Then trial-and-error method is used to identify and isolate the fault section; (b) Distributed sensors are deployed in the distribution system. Distribution system automation software in the operation center then collects fault information sent from all the distributed sensors. Operation stuff make a judgement on the fault section and fault isolation is done on a remote control or manual operation fashion. These methods leave a lot of room for improvements, which will be elaborated in section II. In this paper, integrated usage of fundamental frequency signals and traveling waves signals is done for fault detection and fault type identification in distributed sensors. And then an automatic fault section identification algorithm is introduced. This algorithm does not require human intervention, which reduces outage time, saves manual efforts and also lays the foundation for automatic electricity restoration.