Applications In Distributed Systems Research Articles

Enhanced distance-based protection for high impedance faults considering dynamic load modelling

The load can be represented by different models, including static and dynamic representations; each has different responses when analysing a power system, which also impacts the protection system's performance. For instance, in the distance relay, the estimated impedance can present overreach or underreach, affecting the selectivity of the protection and causing malfunction of triggering schemes. Under fault conditions, the load modelling effect can be magnified by the fault resistance effect, where the combination of both effects has not been addressed in the revisited bibliography. The present paper analyses the effect of load modelling for non-bolted faults in the distance relay impedance estimation. Distance relays are of interest due to their wide use in transmission systems and the emerging applications in distribution systems and microgrids. The fundamental contribution of the present paper is to propose a countermeasure for the effects of four different load types and fault resistance. The results demonstrate that the distance estimation is correctly enhanced, and then a close to the real positive sequence impedance is estimated from the relay point to the fault point. The proposal can be included in distance relays without requiring additional hardware, allowing countermeasure of the load type and fault resistance effects.

Enhanced authentication and device integrity protection for GDOI using blockchain

AbstractRecent device‐level cyber‐attacks have targeted IoT critical applications in power distribution systems integrated with the Internet communications infrastructure. These systems utilize group domain of interpretation (GDOI) as designated by International Electrotechnical Commission (IEC) power utility standards IEC 61850 and IEC 62351. However, GDOI cannot protect against novel threats, such as IoT device‐level attacks that can modify device firmware and configuration files to create command and control malicious communication. As a consequence, the attacks can compromise substations with potentially catastrophic consequences. With this in mind, this article proposes a permissioned/private blockchain‐based authentication framework that provides a solution to current security threats such as the IoT device‐level attacks. Our work improves the GDOI protocol applied in critical IoT applications by achieving decentralized and distributed device authentication. The security of our proposal is demonstrated against known attacks as well as through formal mechanisms via the joint use of the AVISPA and SPAN tools. The proposed approach adds negligible authentication latency, thus ensuring appropriate scalability as the number of nodes increases.

A double-ended third harmonic method for vegetation high impedance fault location in overhead distribution systems

Vegetation-related high-impedance faults (VHIFs) on overhead distribution systems can cause damage, maintenance issues, and even wildfires, impacting both utilities and ecosystems. Existing fault location techniques struggle to accurately locate VHIFs. In this paper, we propose a novel double-ended terminal location method based on the third harmonic component of the fault system. The proposed technique determines the distance of the VHIF by approximating the third harmonic voltage at the fault local, utilizing measurements from the remote terminal located at the far-end of the feeder. This method efficiently locates VHIFs with just two measurement terminals, cutting the need and cost of extensive sensor deployment. Moreover, the proposed method overcomes the limitations of traditional fault location techniques by using a third harmonic model of the faulted system, eliminating the need for complex mathematical models to approximate the fault behavior and voltage at the fault local. Simulation tests were conducted to validate the proposed method, demonstrating its effectiveness in accurately locating VHIFs. The technique achieved error rates below 1.6 %, making it a promising solution for real-world applications in power distribution systems. The ability to precisely locate VHIFs meets a proactive protection philosophy and contributes to improved power system protection and ensures uninterrupted power supply.

Numerical simulation of convective heat transfer in the discharging process of external ice-melting ice storage systems

The external ice-melting ice storage system was widely used because of its advantages of reducing peak power consumption, reducing energy consumption and emissions, and fast ice melting speed. However, designing the external ice-melting ice storage system proved to be a challenge, and the structure and flow of the water distribution system needed to be fully considered. In particular, the problem of unstable outlet water temperature limited the practical application of the external melting ice storage system. Aiming at the problem of unstable outlet water temperature, a three-dimensional CFD phase change model was constructed in this paper. By comparing with the experimental data, the impact of varying water flow rates on the thermal and cooling properties of the was investigated. The results indicated that when the water flow rate was 226 ml/min for the system with an ice thickness of 74 mm, the outlet temperature of the ice storage tank was consistently below 5°C, the Nusselt number of ice and water remained constant, and the convective heat transfer effect was improved. The numerical simulation results provided guidance for the design and practical application of the water distribution system of the external melting ice storage system.

Development of an afterpulse effect model of InGaAs/InP single-photon avalanche diodes for application in quantum key distribution systems

Development of an afterpulse effect model of InGaAs/InP single-photon avalanche diodes for application in quantum key distribution systems

Application of Internet of Things in Residential Distribution Systems

Enabling an internet of things (IoT) application in residential distribution systems by integrating houses with IoT windows and occupant behavior can provide numerous advantages to the power grid, including, but not limited to, demand diminution, congestion reduction, and capacity deferral. This paper presents a new framework that mathematically enables an IoT application in residential distribution systems by integrating IoT windows and occupant behavior with houses for load management and energy conservation. With the proposed framework, we model residential loads considering the IoT concept, and then develop a mathematical optimization model that facilitates the integration of IoT-based houses into the residential distribution system. Different case studies considering a 33-bus distribution network are presented and discussed to demonstrate the effectiveness of penetrating IoT-based houses on distribution system operations and household profitability. It is observed that the profit of the local distribution company decreases when houses are transformed to IoT-based houses due to the fact that less energy is sold to the households. On the other hand, the operation cost of the IoT-based house is lower than that of the conventional house because of the better-managed house energy use, thereby resulting in saving money. It is found that 10% and 20% penetrations of IoT-based houses help reduce the maximum power imported through the distribution substation by 30 kW and 60 kW, respectively. It is also found that the load of IoT-based houses and power availability of a rooftop photovoltaic generation are not compatible, and hence, without an action from the customer and/or utility to coordinate them through a demand response program, IoT-based houses would not contribute to increasing the connectivity of PV-distributed generation in the smart grid.

Artificial Intelligence Solutions and Applications for Distributed Systems in Smart Spaces

This editorial presents a summary of the Special Issue on Artificial Intelligence Solutions and Applications for Distributed Systems in Smart Spaces, presented in the “Computer Science & Engineering” section of Electronics (ISSN 2079-9292) [...]

Towards adoption of GNNs for power flow applications in distribution systems

An essential component of smart grid applications is the ability to solve the power flow (PF) problem in real-time. As numerical methods are too slow, the use of neural networks (NNs) is rapidly increasing. Graph Neural Networks (GNNs) and their variants have become one of the leading methods to learn graph representations. Power systems and in particular, distribution systems can be represented as graphs, and are characterized by often topology changes, which makes the consideration of the topology structure to be an important aspect when searching for a solution approach. Although GNNs have promising results for certain applications such as computer vision ones, considering its limitations, it still has a long way to go until becoming a leading candidate for PF based applications. This paper highlights the existing gaps and challenges in fully accepting ANNs and particularly GNNs as real-time solution engines for the PF problem in DSs. These gaps are analyzed under three categories: suitable architectures for the solution of the PF problem in DS, explicit vs. implicit incorporation of the DS topology information impact on the models’ generalization, and the limiting factors for GNNs implementation aimed at the solution of the PF problem in DSs. The paper also includes a discussion, suggestions and insights of overcoming these gaps in future research.

Application of a Cold-Chain Logistics Distribution System Based on Cloud Computing and Web Delivery Date Management

The cold chain maintains and transports fresh food in the correct temperature range for slow biological decay processes and delivers safe, high-quality food to customers. Ensuring that quality and efficiency are not affected by the supply chain of cold chain products is a goal. Therefore, this paper proposes the intelligent time scheduling management model (ITSMM) based on cloud computing and a web-based platform for cold-chain logistics and distribution systems. This paper establishes a time scheduling model to reduce the overall order operation cost, diminish the variance among the expected and actual time of finalizing the service orders, and improve useful logistics service providers' satisfaction. Data, including all cold chain phases (distributors, industry, consumers, and retailers), have been gathered. This paper examines the distribution cost and time refrigerated vehicles, thus instituting a cold chain distribution vehicle path optimization.

State estimation based on enhanced Bayesian approach: Application in water distribution systems

Hydraulic models have been regarded as an essential tool for controlling and operating water distribution systems (WDSs). With the rapid development of communication networks, real-time control is becoming a hot issue. The nodal water demand as the state variable should be estimated for the control and management of WDS. Due to the lack of sufficient observed data to determine the nodal water demand, the hydraulic model may result in unreasonable model outputs, which are undesirable in actual engineering. We develop a Bayesian inference method to fuse nodal pressure prior information into the state estimation process to address this problem. The developed approach can constrain the nodal water demand estimation process and keep the model outputs (e.g., nodal water pressure) in the feasible domain. This approach is applied to a simple network and a realistic large-scale network. Results show that prior nodal pressure information can significantly increase estimation accuracy and decrease the uncertainty, and the estimated nodal pressure can be confined to a feasible domain.

Coordinated control and application of multi-terminal DC distribution system

Because of the rapid development of power electronics, DC loads, and distributed energy resources, the advantages of DC distribution systems are increasingly prominent. This paper provides a brief description of the concepts and functional advantages of DC distribution systems, introducing the main equipment of multi-terminal DC (MTDC) distribution system, the topologies, and the typical application scenarios of each topology. The coordinated control technology of MTDC distribution system is analysed and summarized in terms of control architecture, coordinated control, damping control, and operation mode. The existing MTDC distribution demonstration projects are summarized, and recent typical projects are introduced. Finally, the issues that can be studied regarding to the innovation and application of MTDC distribution system are pointed out.

Adaptive Particle Filter With Randomized Quasi-Monte Carlo Sampling for Unbalanced Distribution System State Estimation

Particle filter (PF) is an effective state estimation method for nonlinear unbalanced distribution systems with non-Gaussian noises. However, the computational inefficiency limits its real-time application in large-scale distribution systems. This paper proposes an adaptive PF (APF) method by using randomized quasi-Monte Carlo (RQMC) sampling to enhance computational efficiency. Firstly, an RQMC sampling method is introduced to enable uniform sampling based on the low discrepancy Sobol’ sequence. This even sampling accelerates the convergence rate of numerical integrations. Secondly, the standard PF is extended to be an RQMC-PF estimator by using the RQMC sampling instead of the MC sampling. Benefiting from the higher convergence rate, fewer particles are required to obtain precise state estimates, thus notably improving computation efficiency. Thirdly, to further make a trade-off between estimation accuracy and computational efficiency, the number of particles used in the RQMC-PF is adaptively determined with the root mean square of the estimated state covariance, yielding an APF. Test results on unbalanced distribution systems with different scales demonstrate that the proposed method can efficiently provide accurate estimates as well as achieve good scalability.

Finite-key analysis of decoy model semi-quantum key distribution based on four-state protocol

Semi-quantum key distribution allows a full quantum user Alice and a classical user Bob to share a pair of security keys guaranteed by physical principles. Semi-quantum key distribution is proposed while verifying its robustness. Subsequently, its unconditional security of semi-quantum key distribution system is verified theoretically. In 2021, the feasibility of semi-quantum key distribution system based on mirror protocol was verified experimentally. However, the feasibility experimental system still uses the laser pulse with strong attenuation. It has been proved in the literature that the semi-quantum key distribution system still encounters the risk of secret key leakage under photon number splitting attack. Therefore, the actual security of key distribution can be further reasonably evaluated by introducing the temptation state and conducting the finite-key analysis in the key distribution process. In this work, for the model of adding one-decoy state only to Alice at the sending based on a four state semi-quantum key distribution system, the length of the security key in the case of finite-key is analyzed by using Hoeffding inequality, and then the formula of the security key rate is obtained. It is found in the numerical simulation that when the sample size is <inline-formula><tex-math id="M3">\begin{document}$ {10}^{5} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="22-20230849_M3.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="22-20230849_M3.png"/></alternatives></inline-formula>, the security key rate of <inline-formula><tex-math id="M4">\begin{document}$ {10}^{-4} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="22-20230849_M4.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="22-20230849_M4.png"/></alternatives></inline-formula>, which is close to the security key rate of the asymptotic limits, can be obtained in the case of close range. It is very important for the practical application of semi-quantum key distribution system.

Gaussian-modulated continuous-variable quantum key distribution based on untrusted entanglement source

In a practical quantum communication system, the security of signal source of continuous-variable quantum key distribution may be jeopardized due to device flaws and hidden attacks. In this paper, an improved scheme for Gaussian-modulated continuous-variable quantum key distribution based on an untrusted entangled source is proposed. In particular, the entanglement source is placed in an untrusted quantum channel to simulate that it is controlled by an eavesdropper, thereby verifying the security of Gaussian-modulated continuous-variable quantum key distribution in a complex environment. This work in detail analyzes the influence of untrusted entanglement source on practical Gaussian-modulated continuous-variable quantum key distribution system, and the numerical simulation shows that the performance of Gaussian-modulated continuous-variable quantum key distribution will dramatically decrease once the entanglement source has moved out of the sender, and it will slightly rise as the untrusted entanglement source slowly moves away from the sender. This paper further introduces two kinds of optical amplifiers, which are phase-sensitive amplifier and phase-insensitive amplifier, to compensate for the imperfection of the coherent detector. These amplifiers are beneficial to enhancing the quantum efficiency of the receiver’s detector. Specifically, the security key rate of Gaussian-modulated continuous-variable quantum key distribution with homodyne detection can be well improved by phase-sensitive amplifier, and the security key rate of Gaussian-modulated continuous-variable quantum key distribution with heterodyne detection can be well improved by phase-insensitive amplifier. To summary, this paper proposes a scheme for Gaussian-modulated continuous-variable quantum key distribution with untrusted entanglement source, experimental results show that the proposed scheme can generate secure quantum keys even if the Gaussian entanglement source is untrusted, and the two optical amplifiers can effectively improve the quantum efficiency of the detector at the receiver. This work aims to promote the practical process of the Gaussian-modulated continuous-variable quantum key distribution system and provide theoretical guidance for the practical implementation and application of the Gaussian-modulated continuous-variable quantum key distribution system.

Rancang Bangun Aplikasi Pendistribusian Sparepart Motor Berbasis Web

CV. Wahana Baru is engaged in the distribution of spare parts specifically for two-wheeled vehicles. Wahana Baru has been established since 18 years ago or more precisely on March 29, 2003 with a name that has never changed, namely Wahana Baru. The business world that is lived in this modern era is very dependent on computerization which is growing and becomes a supporter in various activities within the company or organization. In distribution activities, a motorcycle spare part distribution system application is needed to make it easier for customers to order spare parts on CV. Wahana Baru to support activities is becoming more developed. To realize a motorcycle spare part distribution information system, a web-based motorcycle spare parts distribution information system application was designed at CV. New Rides. In defining requirements and analyzing system development, data collection methods were carried out by means of observation, interviews, and literature review from various sources of information. For the method of analysis and design using Unifield Modeling language (UML). The Motor Parts Distribution Information System uses the Hypertext Preprocessor (PHP) programming language and MySQL as its database. With the Motorcycle Spare Parts Distribution Information System, the processes involved in the distribution of motorcycle spare parts are easier to use, accurate, and integrated.

A Coordinated Multi-Element Current Differential Protection Scheme for Active Distribution Systems

This paper introduces a current differential protection scheme, appropriate for application in medium voltage active distribution systems, where it is desired to keep the greatest possible number of loads and DG units energized during a fault. Conventional two-terminal percentage current differential relays are used to form successive, time-current-coordinated, differential protection zones. Multiple time-delayed differential elements in each protection zone guarantee coordination with the zone's lateral protection devices, as well as between successive differential protection zones. Sensitive time-delayed differential elements protect against relatively high-resistance faults, while instantaneous differential elements minimize protection speed whenever possible. Additional emergency differential elements deal with post-fault topology changes and breaker failure conditions enhancing the overall scheme's performance. The proposed scheme is applied to a model of real medium voltage distribution system with distributed generation, considering a ring topology operation. A detailed simulation-based study proves the applicability and enhanced performance of the proposed scheme.

Uncertainty quantification in low voltage distribution grids: Comparing Monte Carlo and general polynomial chaos approaches

Changes in load and distributed generation in low voltage distribution systems (LVDS) have made the individual consumer offtake highly uncertain for the system operator. In order to accurately determine hosting capacity of such systems, congestion related stochastic indices, e.g. probability of undervoltage and overvoltage, must be calculated. These require either too many deterministic calculations (simulation-based methods) or the use of analytical probabilistic power flow. Numerical simulation-based methods often use a Monte Carlo (MC) based approach due to its simplicity. Recently, analytical methods such as general polynomial chaos (gPC) expansion have gained increasing interest. This paper develops a non-intrusive gPC formulation for congestion determination in LVDS and illustrates its effectiveness compared to the MC methods. Both MC and gPC methods are compared for computational time, and accuracy, for a set of realistic feeders with high photovoltaic (PV) penetration. The PV power injection uncertainty is characterized by a univariate continuous distribution. The paper illustrates the merits of using the general polynomial chaos expansion with degree 2 and Sobol sequences based testing points for the probabilistic assessment of LVDS with many uncertainty sources. • Monte Carlo, Quasi-Monte Carlo and general Polynomial Chaos are compared. • The comparisons are made for low voltage distribution system applications. • The different variant of general Polynomial Chaos is compared for the tail and mean events to obtain the best variant. • The influence of the number of uncertainty sources in choosing the right approach is evaluated. • Analysis helps to select the most appropriate probabilistic power flow tool for distribution systems.

Adoption of Artificial Intelligence Along with Gesture Interactive Robot in Musical Perception Education Based on Deep Learning Method

The present work aims to improve students’ interest in music teaching and promote modern teaching. A distributed application system of artificial intelligence gesture interactive robot is designed through deep learning technology and applied to music perception education. First, the user’s gesture instruction data is collected through the double channel convolution neural network (DCCNN). It uses the double-size convolution kernel to extract feature information in the image and collect the video frame’s gesture instruction. Secondly, a two-stream convolutional neural network (two-stream CNN) recognizes the collected gesture instruction data. The spatial and temporal information is extracted from RGB color mode (RGB) images and optical flow images and input into the two-stream CNN to fuse the prediction results of each network as the final detection result. Then, the distributed system used by the interactive robot is introduced. This structure can improve the stability of the interactive systems and reduce the requirements for local hardware performance. Finally, experiments are conducted to test the gesture command acquisition and recognition network, and the performance of the gesture interactive robot in practice. The results indicate that combining convolution kernels of [Formula: see text] and [Formula: see text] can increase the recognition accuracy of DCCNN to 98% and effectively collect gesture instruction data. The gesture recognition accuracy of two-stream CNN after training reaches 90%, higher than the mainstream dynamic gesture recognition algorithm trained with the same data set. Finally, the recognition test of gesture instructions is carried out on the gesture interactive robot reported here. The results show that the recognition accuracy of the gesture interactive robots is more than 90%, meeting the routine interaction needs. Therefore, the interactive gesture robot has good reliability and stability and is applicable to music perception teaching. The research reported here has guiding significance for establishing music teaching with multiple perception modes.

Power Electronics Converters for the Internet of Energy: A Review

This paper presents a comprehensive review of multi-port power electronics converters used for application in AC, DC, or hybrid distribution systems in an Internet of Energy scenario. In particular, multi-port solid-state transformer (SST) topologies have been addressed and classified according to their isolation capabilities and their conversion stages configurations. Non-conventional configurations have been considered. A comparison of the most relevant features and design specifications between popular topologies has been provided through a comprehensive and effective table. Potential benefits of SSTs in distribution applications have been highlighted even with reference to a network active nodes usage. This review also highlights standards and technical regulations in force for connecting SSTs to the electrical distribution system. Finally, two case studies of multi-port topologies have been presented and discussed. The first one is an isolated multi-port bidirectional dual active bridge DC-DC converter useful in fast-charging applications. The second case of study deals with a three-port AC-AC multi-level power converter in H-Bridge configuration able to replicate a network active node and capable of routing and controlling energy under different operating conditions.

Enhanced Support Recovery for PMU Measurements Based on Taylor–Fourier Compressive Sensing Approach

Modern distribution networks are characterized by higher distortion and faster variability of voltages and currents. Accurate synchrophasor, frequency and ROCOF measurements thus ask for new techniques trying to reduce latency while limiting the impact of spurious components. In this respect, Taylor-Fourier Multifrequency approach is a good candidate for Phasor Measurement Units intended for distribution system applications. In the present paper, we propose an enhanced version of this approach based on the joint application of window functions and iterative support refinement by means of the phasor first order derivative. The performance of the algorithm is thoroughly characterized through extensive numerical simulation of non-standard test conditions that reproduce the challenges of real-world scenarios, with fundamental dynamics superimposed to interfering tones. The reported results confirm the enhanced spectral support recovery, resulting in a remarkable improvement of estimation accuracy.