System Topology Research Articles

Simultaneous optimization of capacity and topology of seismic isolation systems in multi-story buildings using a fuzzy reinforced differential evolution method

Inter-story isolation systems, as an alternative earthquake protection system, reduce in-building movement compared to base isolation systems. In this context, the current study focuses on simultaneously optimizing the topology and capacity of base and inter-story isolation systems for a multi-story building exposed to multiple earthquake scenarios. In addressing this challenge, an optimization model is developed that simultaneously considers both the topology (vertical arrangement) and capacity (required stiffness) of the seismic isolators as the decision variables of the model. To attain more practical and feasible solutions, the side constraints of the problem involve the inter-story drift and the total cost of seismic isolation systems. A gradient-free and self-adaptive search method, Fuzzy Differential Evolution incorporated Virtual Mutant (FDEVM), is employed to solve the optimization problem. The FDEVM approach applies a fuzzy mechanism to adopt its search behavior with governing condition(s) of the current problem. The selected method's performance is implicitly compared with its standard version. The obtained results indicate that optimally placing inter-story isolators with an optimal configuration and capacity not only improves the seismic performance of the systems but also its more cost-efficient approach compared with conventional based isolation systems. Also, the comparative outcomes indicate that the FDEVM method exhibits a high search capability for this class of problems.

Early Design Stage Evaluation of All Electric Aircraft Power Systems Focusing on Long-Term Behavior

In the aircraft industry, there is a shift towards more and all-electric power systems resulting in great research efforts on single components like batteries. At the same time there is an increasing need to investigate and evaluate the long-term behavior of the whole electric power system to ensure safe and sustainable aircraft operation. Focusing on this challenge, the objective of this article is to propose a framework for electric power system assessment in the early design stages. In particular, the focus is on identifying and handling uncertainties regarding failure behavior and degradation, both on the component and system level. The evaluation of different power system topologies is based on the integration of Model-Based Systems Engineering and robust design methods. In this context, another central aspect is the definition of system and component requirements derived from the flight mission profile. SysML diagrams are used to define use cases and possible system topologies. Sensitivity of degradation effects are evaluated using robust design methods. The application of the framework and these methods is illustrated using a short-range aircraft with an all-electric power system. The results highlight the applicability of the framework to cope with the uncertainties that occur in the early design stages and point out fields of further research.

Nash–Cournot Equilibrium and Its Impact on Network Transmission Congestion

This paper evaluates the impact of congestion on transmission lines when the operation cost is minimized using economic dispatch (ED), comparing the results obtained with the Nash–Cournot Equilibrium (NCE). A methodology is developed for the optimal power flow solution through the NCE, considering the network topology (upper and lower generation limits, upper and lower limits of the transmission lines, and power balance) for a nine-node system without and considering two bilateral power transactions. The results show that the operation cost is higher when the NCE is implemented than ED. However, the problem of congestion in the transmission lines is reduced due to the equilibrium obtained in the power dispatch against minimizing the operation cost in the dispatch; the transmission lines with the most significant participation tend to become congested when additional bilateral transactions occur. Finally, the above is verified by obtaining the mean and median of the transmission line percentages used in the two simulations.

Comprehensive case study on the technical feasibility of Green hydrogen production from photovoltaic and battery energy storage systems

AbstractThe growing demand for alternative energy sources to alleviate environmental impacts highlights the need to move from fossil fuels to renewable energy. This study demonstrated the technical feasibility of using a solar photovoltaic (PV) system for the production of green hydrogen. This research examined electrical and power data from a PV plant in Irecê, Bahia, using open data sources to provide insights into the production of green hydrogen from renewable sources. The system mainly depends on the use of a renewable source, PV solar energy, integrated with batteries, electrolyzers, and hydrogen tanks. Electrolyzer, battery, and hydrogen tank sizing analysis for optimal hydrogen production was effectively conducted using HOMER Energy software. The predicted system topology prioritizes a local DC network, optimizing efficiency for electrolyzers that have inherently low efficiency. The electrolyzer simulation involves initial Python‐based sizing and comprehensive sizing with HOMER Energy software, ensuring accuracy within a 10% discrepancy limit. This highlights the importance of analytical calculations and optimization software for sizing more complex systems.

Quasiperiodic disorder induced critical phases in a periodically driven dimerized p-wave Kitaev chain

The intricate relationship between topology and disorder in non-equilibrium quantum systems presents a captivating avenue for exploring localization phenomenon. Here, we look for a suitable platform that enables an in-depth investigation of the topic. To this end, we delve into the nuanced analysis of the topological and localization characteristics exhibited by a one-dimensional dimerized Kitaev chain under periodic driving and perform detailed analyses of the Floquet Majorana modes. Such a non-equilibrium scenario is made further interesting by including a spatially varying quasiperiodic potential with a temporally modulated amplitude. Apriori, the motivation is to explore an interplay between dimerization and a quasiperiodic disorder in a topological setting which is also known to demonstrate unique (re-entrant) localization properties. While the topological properties of the driven system confirm the presence of zero and π\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pi $$\\end{document} Majorana modes, the phase diagram obtained by constructing a pair of topological invariants (Z×Z\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathbb {Z} \ imes \\mathbb {Z} $$\\end{document}), also referred to as the real space winding numbers, at different driving frequencies reveal intriguing features that are distinct from the static scenario. In particular, at either low or intermediate frequency regimes, the phase diagram concerning the zero mode involves two distinct phase transitions, one from a topologically trivial to a non-trivial phase, and another from a topological phase to an Anderson localized phase. On the other hand, the study of the Majorana π\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pi $$\\end{document} mode unveils the emergence of a unique topological phase, characterized by complete localization of both the bulk and the edge modes, which may be called as the Floquet topological Anderson phase. Moreover, different frequency regimes showcase distinct localization features which can be examined via the localization toolbox, namely, the inverse and the normalized participation ratios. Specifically, the low and high-frequency regimes demonstrate the existence of completely extended and localized phases, respectively. While at intermediate frequencies, we observe the critical (multifractal) phase of the model which is further investigated via a finite-size scaling analysis of the fractal dimension. Finally, to add depth into our study, we have performed a mean level spacing analyses and computed the Hausdorff dimension which yields specific characteristics inherent to the critical phase, offering profound insights into its underlying properties.

Gradient Scale Monitoring for Federated Learning Systems

As the computational and communicational capabilities of edge and IoT devices grow, so do the opportunities for novel Machine Learning solutions. This leads to an increase in popularity of Federated Learning (FL), especially in cross-device settings. However, while there is a multitude of ongoing research works analyzing various aspects of the FL process, most of them do not focus on issues of operationalization and monitoring. For instance, there is a noticeable lack of research in the topic of effective problem diagnosis in FL systems. This work begins with a case study, in which we have intended to compare the performance of four selected approaches to the topology of FL systems. For this purpose, we have constructed and executed simulations of their training process in a controlled environment. We have analyzed the obtained results and encountered concerning periodic drops in the accuracy for some of the scenarios. We have performed a successful reexamination of the experiments, which led us to diagnose the problem as caused by exploding gradients. In view of those findings, we have formulated a potential new method for the continuous monitoring of the FL training process. The method would hinge on regular local computation of a handpicked metric - the gradient scale coefficient (GSC). We then extend our prior research to include a preliminary analysis of the effectiveness of GSC and average gradients per layer as potentially suitable for FL diagnostics metrics. In order to perform a more thorough examination of their usefulness in different FL scenarios, we simulate the occurrence of the exploding gradient problem, vanishing gradient problem and stable gradient serving as a baseline. We then evaluate the resulting visualizations based on their clarity and computational requirements. We introduce a gradient monitoring suite for the FL training process based on our results.

Immune algorithm-based optimal design of collector system topology for offshore wind farm

Immune algorithm-based optimal design of collector system topology for offshore wind farm

Integration of MPPT algorithms with spacecraft applications: Review, classification and future development outlook

The electric power system is one of the key subsystems of a spacecraft and is responsible for the acquisition, conversion, storage and control of energy during the spacecraft mission. Therefore, ensuring the adequacy and stability of energy sources has become an important part of the spacecraft design process. Currently, most spacecraft acquire energy through the solar cell arrays they carry, but the actual output power of the photovoltaic system is difficult to reach the peak power due to the influence of the on-orbit space environment such as alternating temperature changes and radiation. In order to improve the output efficiency of PV systems, researchers have proposed the maximum power point tracking method based on the operating characteristics of the PV cells, and the classical methods include the incremental conductance method, hill-climbing method, constant voltage method, and perturbation observation method. On its basis, in order to further improve the control accuracy and adaptability of MPPT under complex environment, related scholars have proposed several new MPPT algorithms, such as fuzzy algorithm and neural network algorithm based on the principle of intelligence, particle swarm optimization algorithm based on the principle of optimization, gray wolf algorithm and hybrid optimization algorithm based on multiple algorithms.This paper provides a comprehensive review of the topology, hardware architecture, mathematical models, and multiple DC-DC circuits of maximum power tracking PV systems; and reviews and summarizes the classical, intelligent, optimization, and hybrid types of maximum power point tracking methods, describing the principles, advantages, disadvantages, and applications of the different methods, respectively. Finally, an outlook on the future development and novel applications of maximum power point tracking methods for photovoltaic systems in aerospace is presented.

Design and Implementation of a Non-Destructive AC Heating System for Lithium-Ion Battery Modules

The electrification of transportation is experiencing rapid development. Electric bicycles (e-bikes) are commonly employed as convenient modes of transportation. Thanks to the advantages of long life and high energy density, lithium-ion batteries (LIBs) are widely used in e-bikes. In certain business models, e-bikes can utilize rental LIBs, which are centrally managed at charging stations. The low-temperature charging and discharging performance of the LIB system poses a significant challenge during usage. Among various heating methods, alternating current (AC) heating has garnered attention due to its high efficiency and has been applied to quickly warm up the LIB system. To address this issue, an AC heating model was established to determine the appropriate frequency and magnitude of the current, and a prototype AC heating system for the LIB modules used in e-bikes was designed. A full-bridge topology system model was established, and an experimental platform was constructed to test the effectiveness of the proposed AC heating topology and thermoelectric model under different AC heating frequencies and currents. The results show that the proposed AC heating system can heat an 18650 battery module within 20 min. Under an ambient temperature of −20 °C, using a 10 A, a 100 Hz excitation current achieves a heating rate of 1.3 °C per minute, with minimum power losses. The prototype also has a fast response time of only 70 ms. Finally, the strategies of LIB heating and insulation are proposed for the scenario of a battery swapping station. This research holds great significance in resolving the problem of low-temperature heating for e-bikes in cold regions.

FDIA localization and classification detection in smart grids using multi-modal data and deep learning technique

False data injection attacks (FDIA) exploit the vulnerabilities of bad data detection in energy management systems to maliciously tamper with state estimation results, seriously jeopardizing the safe and reliable operation of power systems. In order to promptly detect FDIA, recent studies have used machine learning techniques to extract attack characteristics and detect FDIA based on changes in these characteristics. Current research predominantly focuses on detecting a single type of FDIA attack model and topology. However, the increasing diversification of FDIA construction methods and the variability of topological structures in power systems can reduce or even invalidate detection effectiveness. To cope with the abovementioned difficulties, this study introduces a multimodal deep learning detection model based on variational graph auto-encoders (VGAE), temporal convolutional networks (TCN), and gated recurrent units (GRU). The topological features of power systems are obtained through VGAE to adapt to the detection needs of various topological structures and performance enhancement. These features are then integrated with preprocessed measurement data via BDD to form multimodal data. Furthermore, this multimodal data is used to locate and classify FDIA with complete information, FDIA with incomplete information, and topology attack after applying a multi-label classification algorithm based on TCN-GRU for temporal feature extraction. Experiments carried out on the IEEE 14 and IEEE 118 bus systems show that the proposed method is robust and has high detection performance. The results indicate that the proposed detection method achieves AUC values that are, on average, 0.085, 0.145, and 0.04 higher than those of CNN, LSTM, and CNN-LSTM, respectively. Moreover, under various noise and attack intensities, recall, precision, F1 score, and RACC remain above 0.859, 0.877, 0.867, and 0.818, respectively, with a classification accuracy greater than 0.912. This study provides a unique perspective on detecting FDIA across various attack models and power system topologies.

Anticipation of Large Intrinsic Spin Hall Conductivity in Mercury Chalcogenides: A First‐Principles Study

AbstractThe report carried out detailed first‐principle calculations of Mercury chalcogenides (HgX; X = Te, Se and S) using density functional theory, verifying the bulk band inversion property with different exchange‐correlation functionals. The Wannier function method is used to study the non‐trivial topology of HgX systems, spin Berry curvature, and intrinsic spin Hall conductivity. Quantized intrinsic spin Hall conductivity is observed in the HgX systems. Large intrinsic spin Hall conductivity is found in the systems due to a strong spin Berry curvature accumulation near the triply degenerate points in the Brillouin zone. Calculation shows that the intrinsic spin Hall conductivity for all three HgX systems has stable plateaus, with Mercury Telluride having a maximum width of up to 1.05 eV. The maximum intrinsic spin Hall conductivity of –931/e () is obtained in mercury sulfide, higher than the reported values for spin Hall conductivity and the plateau width in typical topological insulators such as , , and as well as in transition metal pnictides (TaX, X = As, P and N) and transition metal iridates.

Zebra: A cluster-aware blockchain consensus algorithm

The Consensus algorithm is the core of the permissioned blockchain, it directly affects the performance and scalability of the system. Performance is limited by the computing power and network bandwidth of a single leader node. Most existing blockchain systems adopt mesh or star topology. Blockchain performance decreases rapidly as the number of nodes increases. To solve this problem, we first design the n-k cluster tree and corresponding generation algorithm, which supports rapid reconfiguration of nodes. Then we propose the Zebra consensus algorithm, which is a cluster tree-based consensus algorithm. Compared to the PBFT, it has higher throughput and supports more nodes under the same hardware conditions. However, the tree network topology enhances scalability while also increasing latency among nodes. To reduce transaction latency, we designed the Pipeline-Zebra consensus algorithm that further improves the performance of blockchain systems in a tree network topology through parallel message propagation and block validation. The message complexity of the algorithm is O(n). Experimental results show that the performance of the algorithm proposed in this paper can reach 2.25 times that of the PBFT algorithm, and it supports four times the number of nodes under the same hardware.

Optimal Design of Resonance Circuit Topology for a Wireless Power Transmission System Using HTS Coils

Optimal Design of Resonance Circuit Topology for a Wireless Power Transmission System Using HTS Coils

Dual receiver series topology for bipolar segmented DWPT system

For a segmented dynamic wireless power transfer (DWPT) system, when electric vehicles (EVs) move over two adjacent transmitting coils, the received power fluctuates greatly and has some loss. Arming at this problem, this paper proposes a dual receiver segmented DWPT topology to reduce the received power fluctuation of the receiving coil passing through the rail junction during the moving process of the EV. Through magnetic field analysis in this paper, tuning the current phase difference between two adjacent transmitting coils to 180° can enhance the magnetic field. In this paper, a dual receiver series topology (DRST) is designed to pick up power, which consists of four fully controlled components and four diodes. According to EVs’ real-time position, the segment DWPT system has three working modes and six working states under the control of DRST. Finally, experiments are carried out. Compared to the single-receiving-coil system, DRST is effective in improving the average output power from 2.007 to 5.657 W and significantly reducing the power fluctuation.

Distributed fixed-time control for high-order multi-agent systems with FTESO and feasibility constraints

In this study, a fixed-time distributed anti-disturbance control strategy is designed for a class of higher-order multi-agent systems in an undirected static topology. Inspired by the existing literature, the strategy introduces a unique way of defining neighborhood errors during the design process to deal with the connectivity maintenance and collision avoidance problems among the neighbor agents in the system. The control strategy not only solves the full state constraint and transient steady state performance constraint control problems simultaneously, but also considers the effects of internal uncertainties and external disturbances of the system, which enhances the difficulty of controller design. To address these challenges, a fixed-time extended state observer is introduced to obtain the estimation of uncertainty and disturbance . Subsequently, an integrated backstepping control scheme is designed to feed-forward compensate for uncertainties and disturbances, while constraining the transient steady-state performance of the system to remain within a predefined performance boundaries. This is achieved by combining the fixed-time prescribed performance and the barrier Lyapunov function. Finally, a simulation case is presented to verify the effectiveness of the designed control strategy.

Comparative study of electric power structure of hydrogen fuel cell electric propulsion ship system

Abstract Aiming at the problem of the applicability of active and semi-active structures of hybrid energy storage units to the complex working conditions of ships in the hydrogen fuel cell electric propulsion system of ships, a comparative study of such structures is carried out in terms of the control strategy, capacity design and optimization effect, respectively. The hybrid energy storage unit in the active structure, supercapacitor and battery, are both connected to the DC bus through the converter. In the hybrid energy storage unit in the semi-active structure, the battery is connected to the low-voltage DC bus through the converter flow in parallel with the supercapacitor, and then connected to the DC bus through the converter. Two kinds of hydrogen fuel cell electric propulsion ship system topology simulation models were established by MATLAB/Simulink respectively, and simulation verification was carried out. The simulation results show that the hybrid energy storage unit with an active structure has stronger adaptability in complex working conditions during ship operation.

Global topological synchronization of weighted simplicial complexes.

Higher-order networks are able to capture the many-body interactions present in complex systems and to unveil fundamental phenomena revealing the rich interplay between topology, geometry, and dynamics. Simplicial complexes are higher-order networks that encode higher-order topology and dynamics of complex systems. Specifically, simplicial complexes can sustain topological signals, i.e., dynamical variables not only defined on nodes of the network but also on their edges, triangles, and so on. Topological signals can undergo collective phenomena such as synchronization, however, only some higher-order network topologies can sustain global synchronization of topological signals. Here we consider global topological synchronization of topological signals on weighted simplicial complexes. We demonstrate that topological signals can globally synchronize on weighted simplicial complexes, even if they are odd-dimensional, e.g., edge signals, thus overcoming a limitation of the unweighted case. These results thus demonstrate that weighted simplicial complexes are more advantageous for observing these collective phenomena than their unweighted counterpart. In particular, we present two weighted simplicial complexes: the weighted triangulated torus and the weighted waffle. We completely characterize their higher-order spectral properties and demonstrate that, under suitable conditions on their weights, they can sustain global synchronization of edge signals. Our results are interpreted geometrically by showing, among the other results, that in some cases edge weights can be associated with the lengths of the sides of curved simplices.

Enhanced hybrid energy storage system combining battery and supercapacitor to extend nanosatellite lifespan

The power limitations of nanosatellites, particularly during peak demand periods such as data transmission and maneuvering, hinder their operational capabilities. Traditional Electrical Power Subsystems relying solely on batteries face challenges in delivering the necessary power density and maintaining battery life, especially during eclipses. This study proposes an innovative Hybrid Energy Storage System for a 3U nanosatellite, integrating high-energy-density batteries with high-power-density supercapacitors, using an active parallel hybrid topology with two bidirectional converters and an optimal power management strategy. Using MATLAB and Simulink models, the study optimizes the Hybrid Energy Storage System by focusing on minimizing the capacity rate and depth of discharge to extend battery life. Simulation results show a 53.42% reduction in depth of discharge compared to a battery-only system, indicating a significant extension of battery life. Additionally, the proposed system allows for a minimal 2.08% increase in overall mass while maintaining enhanced performance. This research fills a critical gap in the literature by exploring active Hybrid Energy Storage System topologies for spacecraft applications, beyond the traditional passive and semi-active configurations. The innovative power management strategy ensures efficient energy utilization, significantly enhancing the reliability and efficiency of nanosatellite missions. The findings offer a practical solution to improve mission performance and extend the operational lifespan of nanosatellites, paving the way for more robust and capable small satellite deployments.

Convergence analysis of state estimation for UAV formation under GPS‐denied environments

AbstractIn this article, we focus on the state estimation and formation control problem for a multi‐UAV system, where only parts of UAVs have GPS measurements, that is, the anchors, and the other UAVs measure their relative positions with anchors. With a second‐order discrete‐time model of each UAV in the formation, we analyze the convergence of state estimation (including its expectation and covariance) for commonly used consensus‐based formation control protocols, under the effect of control and measurement noise. More specifically, based on the discrete‐time stability analysis, we obtain the sufficient and necessary conditions for the expectation stability of the formation control. Using the fixed point theorem in positive symmetric matrix subspace and observability analysis, we rigorously prove that the covariance of estimation is bounded if and only if the anchor node set is globally reachable. Based on our analysis, the formation control parameters and system topology can be designed to satisfy sufficient conditions, such that the desired formation pattern can be achieved for the multi‐UAV dynamic system under GPS‐denied environments. Simulation results corroborate the effectiveness of our theoretical results.

Wireless Power Transfer System with Constant Voltage/Constant Current Output Performance

Aiming at the problem of unstable output voltage and output current caused by load fluctuation, this paper starts from the perspective of system topology and control strategy for analysis. First, the output characteristics of LCL-S (inductor-capacitor-inductor and series), LCL-P (inductor-capacitor-inductor and parallel), LCL-LCL (inductor-capacitor-inductor and inductor-capacitor-inductor), and LCL-LCC (inductor-capacitor-inductor and inductor-capacitor-capacitor) compensation topologies are analyzed. Combining the advantages of LCL-S and LCL-LCL compensation topology output characteristics, an LCL-LCL/S compensation topology is constructed, and its topology is optimized. Then the influence of parasitic resistance on the output characteristics of LCL-LCL/S compensation topology is derived. A control strategy of primary side regulation is proposed to address the issue of unstable output voltage and current caused by parasitic resistance in the system under variable loads. This method can effectively improve the stability of the output voltage and output current of the wireless power transfer system in the LCL-LCL/S compensation topology under load fluctuations. Finally, a set of experimental prototypes is built to verify the correctness of the theoretical analysis.