Dynamic Reconfigurable Systems Research Articles

Physics-informed Graph Neural Network for Dynamic Reconfiguration of power systems

To maintain a reliable grid we need fast decision-making algorithms for complex problems like Dynamic Reconfiguration (DyR). DyR optimizes distribution grid switch settings in real-time to minimize grid losses and dispatches resources to supply loads with available generation. DyR is a mixed-integer problem and can be computationally intractable to solve for large grids and at fast timescales. We propose GraPhyR, a Physics-Informed Graph Neural Network (GNNs) framework tailored for DyR. We incorporate essential operational and connectivity constraints directly within the GNN framework and train it end-to-end. Our results show that GraPhyR is able to learn to optimize the DyR task.

A DOD-SOH balancing control method for dynamic reconfigurable battery systems based on DQN algorithm

This article presents a DOD-SOH equalization method for a DRB system based on the Deep DQN algorithm. The proposed method utilizes DQN to learn the operational processes of the system. By integrating the advantages of DRB with SOH equalization theory and the DQN algorithm from the perspective of DOD, our method significantly improve battery performance and ensure cell balancing. To begin with, we present a dynamic reconfigurable battery system with a simple topological structure and outline its switching control process. Additionly, we provide an analysis of the SOH balancing principle and elaborate on the control process of DQN algorithm. Finally, subsequent simulations are carried out, and the simulation results demonstrate outstanding performances in reducing the variance of SOHs, which indicates an enhancement in the level of SOH balancing as well.

Implementation Of Dynamically Reconfigurable NoC Using Flexible Dimension Order Routing (FDOR) Algorithm on FPGA

NoC-Based Dynamic Reconfigurable Systems (DRSs) implemented over FPGA devices change their configuration at the run time by re-positioning or replacing the existing processing modules into the network. Several Dynamically Reconfigurable NoCs (DRNoCs) in the literature, propose adaptive routing algorithms in order to handle the network structure alteration. Nevertheless, their implementation cost is severe in terms of chip area and time required to reconfigure the routing scheme, which results in non-well scalable solutions for DRSs. In this work, we propose an alternative DRNoC approach, based on a traditional 2-D mesh, using a logic-based implementation of the Flexible Direction Order Routing (FDOR) algorithm, thus inheriting its simplicity and deadlock-freedom. Several scenarios have been considered in order to prove the applicability of the FDOR algorithm in the context of a DRNoC accompanied by performance and synthesis results. In conclusion, we demonstrate that FDOR is a suitable solution for DRNoCs. This project was aimed for implementing low-cost optimized FPGA architecture. Model sim 6.5f is used for simulating the NOC and synthesized using Xilinx ISE 14.7. Then the implementation is done in Spartan3 FPGA Kit.

Intelligent Optimization Approaches for a Secured Dynamic Partial Reconfigurable Architecture-Based Health Monitoring System

In this work, an intelligent multi-objective optimization technique is proposed to optimize various parameters such as power consumption ([Formula: see text]), computation time ([Formula: see text]) and area ([Formula: see text]) for a health monitoring system designed using the Secured Dynamic Partial Reconfiguration (SDPR) architecture. The cost-efficient Dynamic Partial Reconfiguration (DPR)-based field-programmable gate array (FPGA) is very useful for analyzing many applications such as automation and data processing. The novelty of this paper is to design a new intelligent SDPR (i-SDPR) module in order to achieve better performance in a health monitoring system by considering various performance parameters. The SDPR architecture is incorporated with two reconfigurable modules such as Encrypt and Authenticate, which results in an increase in the core power consumption ([Formula: see text]), computation time ([Formula: see text]) and area ([Formula: see text]). So, to improve the performance of the SDPR-based health monitoring system, there is a necessity to optimize the performance parameters and it is achieved through intelligent multi-objective evolutionary (MOEA) techniques. The intelligent multi-objective evolutionary techniques such as Niched-Pareto Genetic Algorithm (NPGA), Pareto Archived Evolution Strategy (PAES) and Pareto Envelope-based Selection Algorithm (PESA) have been considered for better optimization in the performance parameters. For the study, the free-to-use MIMIC-III dataset is taken, which contains critically admitted various intensive care unit patient data. The dataset is processed through any one of the multi-objective evolutionary operators till satisfying the conditions and then forwarded to implementation. The proposed architecture has been implemented and tested using Cyclone[Formula: see text] V SX SoC Development Kit. The comparative analysis of various performance parameters was done for the proposed i-SDPR with the existing techniques such as the DPR and SDPR approach to show the improvement. The results declare that the proposed techniques obtain better performance compared to the existing techniques.

Dynamic Distribution System Reconfiguration Considering Distributed Renewable Energy Sources and Energy Storage Systems

Electric power systems are in state of transition as they attempt to evolve to meet new challenges provided by growing environmental concerns, increases in the penetration of distributed renewable energy sources (DRES) as well as the challenges associated with integrating new technologies to enable smart grids. New techniques to improve the electrical power system, including the distribution system, are thus needed. One such technique is dynamic distribution system reconfiguration (DNSR), which involves altering the network topology during operation, providing significant benefits regarding the increased integration of DRES. This paper lays out an improved model which aimed to optimize the system operation in a coordinated way, where DRES, energy storage systems (ESS) and DNSR are considered as well as the uncertainty of these resources. The objective function was modeled to incentivize the uptake of DRES by considering the cost of emissions to incentivize the decarbonization of the power system. Also, the switching costs were modeled to consider not only the switching, but also the cost of degradation of these mechanisms in the system operation. Two systems are used to validate the model, the IEEE 119-bus system, and a real system in São Miguel Island. The results of this paper show that using DNSR, DRES, and ESS can lead to a significant 59% reduction in energy demand through a 24-hour period. In addition, using these technologies results in a healthier, more efficient, and higher quality system. This shows the benefits of using a variety of smart grid technologies in a coordinated manner.

Photovoltaic Array Reconfiguration under Partial Shading Conditions Based on Short-Circuit Current Estimated by Convolutional Neural Network

Partial shading conditions (PSC) have negative effects on the operation of photovoltaic (PV) systems. In this paper, a PV array reconfiguration method is developed to minimize power losses of PV arrays under partial shading conditions. The proposed reconfiguration method is based on equalizing the reduction of the short-circuit current of the PV modules in the PV array. Eight state-of-the-art Convolutional Neural Network models are employed to estimate the effect of shading on the short-circuit current of a PV module. These models include LeNet-5, AlexNet, VGG 11, VGG 19, Inception V3, ResNet 18, ResNet 34, and ResNet 50. Among eight models, the VGG 19 achieves the best accuracy on 1842 sample images. Therefore, this model is used to estimate the ratio of the actual short-circuit current and the estimated short-circuit current in four studied shading scenarios. This ratio decides the switching rule between PV modules throughout the PV array under PSC. A 2×2 experimental PV array shows that the proposed reconfiguration method improves the output power from 5.81% to 25.19% in four shading patterns. Accordingly, the power losses are reduced from 1.32% to 13.75%. The power improvement and the reduction of power losses of the proposed dynamic PV array reconfiguration system under four case studies demonstrates its effectiveness in addressing the effects of PSC on the PV array.

Dynamic nanosurface reconfiguration by host-guest supramolecular interactions.

The dynamic functionalization of the nanoparticle surface with biocompatible coatings is a critical step towards the development of functional nano-sized systems. While covalent approaches have been broadly exploited in the stabilization of nanoparticle colloidal systems, these strategies hinder the dynamic nanosurface chemical reconfiguration. Supramolecular strategies based on specific host-guest interactions hold promise due to their intrinsic reversibility, self-healing capabilities and modularity. Host/guest couples have recently been implemented in nanoparticle platforms for the exchange and release of effector molecules. However, the direct exchange of biocompatible hydrophilic oligomers (e.g. peptides) for the modulation of the surface charge and chemical properties of nanoparticles still remains a challenge. Here, we show the intracellular reconfiguration of nanoparticles by a host/guest mechanism with biocompatible oligomeric competitors. The surface of gold nanoparticles was functionalized with cyclodextrin hosts and the guest exchange was studied with biocompatible mono and divalent adamantyl competitors. The systematic characterization of the size and surface potential of the host/guest nanoparticles allowed the optimization of the binding and the stabilization properties of these supramolecular systems. The in cellulo host/guest-mediated direct reconfiguration of the peptide layer at the surface of nanoparticles is achieved by controlling the valence of adamantane-equipped peptides. This work demonstrates that host/guest supramolecular systems can be exploited for the direct exchange of pendants at the surface of nanoparticles and the intracellular dynamic chemical reconfiguration of biocompatible colloidal systems.

Towards Sustainable Systems Reconfiguration by an IoT-driven System of Systems Engineering Lifecycle Approach

By the ever-progressing smartization of products, their embedded environment systems are getting more and more crossed, and so-called System of Systems (SoS) are arising from this to deliver overreaching and new innovative services and functionalities, especially for the customer of those systems. In the future, it will be more and more beneficial to implement these services and product-based functionality under pertinent aspects of sustainability (e.g. carbon footprint or other critical resources along the product engineering process). In this context, this contribution presents a System of Systems Engineering Lifecycle Concept for the dynamic reconfiguration of systems within a smart Product-based System of Systems to ensure certain sustainability aspects during the system of systems operation using an Internet of Things (IoT) based platform. Part of the concept is, on the one hand, the integration of relevant data from the usage of several systems into the early model-based development phases (like Model-based Systems Engineering (MBSE)) by using the so-called IoT-driven smart Product-based System of Systems Reconfiguration Approach to ensure different sustainability aspects in future development phases of a system or a system of systems. To meet compliance and promotion of sustainability aspects in the operation of a smart product-based system of systems, on the other hand, the approach shows under consideration of the current operating data of the participating systems and their corresponding dynamic adaptation using the example of a sustainable autonomous construction site scenario and an appropriate IoT-based platform.

Dynamic Service Restoration for Integrated Energy Systems Under Seismic Stress

Seismic events and following aftershocks can cause devastating impacts on overground and underground energy system infrastructures. This paper designs a novel approach to restore the system functionality in response to seismic stress by using coordinated dynamic system reconfiguration and operation. First, seismic impact on system infrastructures is evluated, considering substations, pipes and distribution lines. Load curtailment is assumed to be caused by the overloading of system branches, buckling towers, reversed gas flows, and isolated sub-circuits. Smart system operation and reconfiguration are coordinatedly applied by using combined soft open points (SOP) and energy storage units, aiming to restore system service by minimizing load curtailment and system recovering time. Service index is quantified considering both load curtailment and recovering time. A representative integrated electricity and gas system is employed to demonstrate the effectiveness of the proposed method. Results illustrate that the adverse impact of seismic on systems can be effectively reduced by the proposed dynamic service restoration method. The model provides system operators with a powerful tool to restore the functionality of distribution systems under seismic events.

A framework for the specification and validation of dynamic reconfigurable systems

We study a framework for the specification and validation of dynamic reconfigurable systems. The framework is based on configuration logic for the description of architecture styles which are families of architectures sharing common connectivity features. We express specifications in the Temporal Configuration Logic (TCL), a linear time temporal logic built from atomic formulas characterizing system configurations and temporal modalities. Two non-trivial benchmarks are introduced to show the adequacy of TCL for the specification of dynamic reconfigurable systems. We study an effective model-checking procedure based on SMT techniques for a non-trivial fragment of TCL which has been implemented in a prototype runtime verification tool. We provide preliminary experimental results illustrating the capabilities of the tool on the considered benchmark systems.

A novel adaptive dynamic photovoltaic reconfiguration system to mitigate mismatch effects

Unequal solar irradiance of the Photovoltaic (PV) modules diminishes the PV array's maximum power output; this effect is due to Partial Shading Conditions (PSCs). There are a few technical options to fix this issue. One of these is the dynamic reconfiguration technique, which means that the electrical connections between the PV modules in the array are dynamically modified to spread shading effects and increase the power output. This paper proposed a novel adaptive reconfiguration method for 3×3 Total-Cross-Tied (TCT) PV array to enhance the maximum power under partial shading conditions. In this work, the PV module's electrical connections are altered dynamically with the proposed logic algorithm's help to maintain the identical row currents in the array. This technique is implemented on 3×3 size of an array using MATLAB and validated experimentally using OPAL-RT software. Further, the proposed technique performance is compared with the existing PV array connections such as Series-Parallel (SP), Total-Cross-Tied (TCT), Bridge-Link (BL), Honey-Comb (HC), and Shade Dispersion Positioning (SDP). Additionally, for different reconfiguration methods, revenue generation from energy savings is estimated. Based on the observations from the results, it is understood that the proposed technique enhanced the maximum power of the TCT array at a higher level as compared to the other PV array connections under PSCs.

RETRACTED: Design of embedded digital image processing system based on ZYNQ

Zynq- real time edge detection system based on execution of the image reconstructed from the sequence. Although the object edge detection is an essential tool in computer vision, edge detection results in the negative image frame noise significantly. Further, due to the high computational complexity of an image filtering operation, implemented in the hardware configuration of the re-configurable hardware it is necessary. In this portion, the proposed dynamic Zynq embedded system reconfiguration capability to detect according to the input image frame to the noise level of the different density filters perform during runtime bit stream re Configuration.The results show that the accuracy of edge detection is highly evaluated. We analyze various noise density levels, and the results show that the edge detection results of the proposed filter bit stream are more accurate, while effectively providing computing capacity to support the real-time processing of the image frame. In the configuration time, CPU usage, and hardware resource utilization performance test results were compared.

Programming dynamic reconfigurable systems

DR-BIP is an extension of the BIP component framework intended for programming reconfigurable systems encompassing various aspects of dynamism. It relies on architectural motifs to structure the architecture of a system and to coordinate its reconfiguration at runtime. An architectural motif defines a set of interacting components that evolve according to reconfiguration rules. With DR-BIP, the dynamism can be captured as the inter-play of dynamic changes in three independent directions: (1) the organization of interactions between instances of components in a given configuration; (2) the reconfiguration mechanisms allowing creation/deletion of components and management of their interaction according to a given architectural motif; and (3) the migration of components between predefined architectural motifs which characterizes dynamic execution environments. The paper lays down the formal foundation of DR-BIP, illustrates its expressiveness on few examples and discusses avenues for dynamic reconfigurable system design.

Review on optimization methodologies in transmission network reconfiguration of power systems for grid resilience

Background When a power system blackout occurs, it affects the economy of the country and every aspect of human life. Cascading failures can easily occur and cause a major blackout in the power grid due to the breakdown or failure of important nodes or links. Recently, transmission network reconfiguration (TNR) becomes a hot topic and has made many concerns after major blackouts of power systems. Aims TNR is the second-stage action plan to restore power systems and plays a major role in the process of power system restoration. On the other hand, grid resilience involves a quick dynamic reconfiguration of power systems to minimize the propagation of attack influences on the grid. The motivations to include the works in this survey are based on the quality of the research performed in the transmission network reconfiguration problem for grid resilience. In this article, the state-of-the-art review of recent progress in the network reconfiguration problem of the transmission system for grid resilience is discussed with practical challenges, technical issues, and power industry practices. Materials & Methods In this paper, complex network theory-based indices with advantages, disadvantages, and their applications have been discussed to assess the important nodes and lines for network reconfiguration problem during sudden disturbances in power systems. Furthermore, optimization models have been presented with objective functions as well as their constraints. Taken together, optimization methodologies have been discussed to solve network reconfiguration problem with merits and demerits. Results This survey paper presents current trends in research and future research directions concerning transmission network reconfiguration for academic researchers and practicing engineers. Furthermore, the most current studies in improving transmission network reconfiguration problem are reviewed by highlighting their advantages and limitations. Discussion Based on a thorough comparison of literature some future perspectives are also discussed for transmission network reconfiguration problem for grid resilience. Conclusion This review paper provides a comprehensive review of current practices applied to transmission network reconfiguration. The core focus of this paper will remain on complex network theory-based indices, optimization models, optimization methodologies, challenges, and technical issues, and discusses future direction for transmission network reconfiguration problem for grid resilience. Furthermore, the most current studies in improving transmission network reconfiguration problem are reviewed by highlighting their advantages and limitations.

Design of a flexible reconfigurable mobile robot localization system using FPGA technology

Mobile robot activities have variable computational requirements according to various parameters related to the robotic applications behaviour and the robot dynamic environment. This high variability puts many challenges for a complete robot navigation system design. With their high flexibility, reconfigurable architectures are a suitable choice to design such dynamic system. Mobile robot navigation steps (perception, localization, obstacle avoidance and path planning) are extremely complex to be embedded in a complete navigation controller. In this paper, we presented a generic and a flexible platform based on FPGA technology, for studying and prototyping complete unified robot navigation system. We exploited the dynamic reconfiguration mechanism that allows modifying the navigation controller according to different navigation algorithm requirements. We showed the effectiveness of this platform in the localization step. We have a dynamic reconfigurable system that switches between three different localization techniques to satisfy energy/surface ratio and exploit the released resources to implement other robot tasks.

Dynamic Reconfiguration Systems for PV Plant: Technical and Economic Analysis

Solar plants suffer of partial shading and mismatch problems. Without considering the generation of hot spots and the resulting security issues, a monitoring system for the health of a PV plant should be useful to drive a dynamic reconfiguration system (DRS) to solve bottlenecks due to different panels’ shading. Over the years different DRS architectures have been proposed, but no suggestions about costs and benefits have been provided. Starting from technical subjects such as differences of the topologies driving the hardware complexity and number of components, this paper identifies the cost of DRS and its lifetime, and based on these issues it provides an economic analysis for a 6 kWp PV plant in different European Union countries, in which the dissimilar incentive policies have been considered.

Dynamic Reconfiguration of Active Distribution System Based on Matrix Shifting Operation and Interval Merger

Dynamic distribution system reconfiguration (DDSR) is a complex NP-hard combinatorial optimization problem when the time varying nature of loads and distribution generation power output are taken into account. Solving the DDSR problem is challenging in terms of computational burden and solution quantity. In this paper, a matrix shifting and interval merger based DDSR algorithm is proposed for line loss reduction. First of all, the matrix of branch power and the vector of line resistance are formulated, and the matrix shifting operation is defined for static reconfiguration in an interval. Then, the reconfiguration is firstly operated in each hour, and the adjacent intervals are selected to be merged into one new interval constantly, which ensures the validity of the interval merger. Meanwhile, a hash table is established to store the exiting reconfiguration schedules to avoid repeated power flow calculations and reduce the compute burden. Finally, the proposed dynamic reconfiguration algorithm is applied to three test systems. The simulation results show that the proposed reconfiguration algorithm can achieve optimal solutions with acceptable computational cost.

Elastic Load Balancing for Dynamic Virtual Machine Reconfiguration Based on Vertical and Horizontal Scaling

Today, cloud computing applications are rapidly constructed by services belonging to different cloud providers and service owners. This work presents the inter-cloud elasticity framework, which focuses on cloud load balancing based on dynamic virtual machine reconfiguration when variations on load or on user requests volume are observed. We design a dynamic reconfiguration system, called inter-cloud load balancer (ICLB), that allows scaling up or down the virtual resources (thus providing automatized elasticity), by eliminating service downtimes and communication failures. It includes an inter-cloud load balancer for distributing incoming user HTTP traffic across multiple instances of inter-cloud applications and services and we perform dynamic reconfiguration of resources according to the real time requirements. The experimental analysis includes different topologies by showing how real-time traffic variation (using real world workloads) affects resource utilization and by achieving better resource usage in inter-cloud.

Reconfiguration Control of Dynamic Reconfigurable Discrete Event Systems Based on NCESs

In order to satisfy system specifications persistently in the cases of component failure, partial communication blocks, or energy deficiency, safety-critical systems need to apply system reconfigurations at runtime. Such systems can be considered as dynamic reconfigurable discrete event systems (DRDESs) if their logic behaviors are concerned only. A reconfiguration of a DRDES includes the switch of system structures and the update of system states. Based on the assumption that all configurations of a DRDES are designed in advance and dynamic reconfigurations can be implemented only at a few predefined reconfigurable states, a novel reconfiguration control method is proposed in this paper. The aim is to implement a required dynamic reconfiguration smoothly and rapidly. A DRDES is modeled by net condition/event systems (NCESs) under the firing rule “maximal single spontaneous transition steps.” An integer linear programming-based method is developed to compute a shortest legal firing sequence (SLFS) from the state where a reconfiguration requirement arises to a reconfigurable state. Accordingly, a virtual controller for guiding the system to evolve along the obtained SLFS is proposed. The proposed method is able to implement a required reconfiguration before the maximum permissible reconfiguration delay if an SLFS exists. A simple reconfigurable assembly system is adopted to illustrate the method.

Reconfigurable optical‐radio wireless networks: Meeting the most stringent requirements of future communication systems

AbstractIn this paper, we propose a reconfigurable optical‐radio wireless network characterized by high flexibility and performance. The hybrid network can be dynamically configured, adapting itself to the changing requirements of users or operating environments, dynamics of the transmission medium, and availability of resources. First, the basic concept, system architecture, and key operating modes are introduced. Possible operating scenarios and their relationship to the operating modes are discussed. Then, a practical implementation of the hybrid network is introduced, describing the network components, architecture, modulation scheme, and implementation technologies. Implementation was carried out using mostly off‐the‐shelf components and universal software radio peripheral blocks. Particular attention has been put in implementing a fast handover mechanism between modes, an essential requirement for seamless network reconfiguration. Network performance is evaluated and different switching approaches are compared. The paper demonstrates practically the proposed concept based on dynamic system reconfiguration. For the implementation, a mode switching algorithm was developed making decisions based on the quality of the wireless channels. The system was tested with live video packets transmitted through the network. System performance was assessed through data throughput and packet loss measured for different modulation parameters. The proposed concept, essentially a software‐defined hybrid network, is flexible and makes efficient use of radio resources. Moreover, the network has the potential to achieve high performance. All these characteristics make reconfigurable optical‐radio networks an attractive candidate for fifth generation and beyond.