Analysis Of Large-scale Systems Research Articles

Equivalence of Impedance Participation Analysis Methods for Hybrid AC/DC Power Systems

Participation analysis based on whole-system impedance models enables the root-cause stability analysis of large-scale power systems when state-space models are unavailable. To extend participation analysis to the hybrid AC/DC system, especially for the interlinking converter, this paper proposes two complementary methods, namely the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">direct method</i> and the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">indirect method</i> . The direct method treats the interlinking converter as hybrid AC-DC port apparatus and the participation factor can be defined with the terminal hybrid AC-DC impedance matrix correspondingly. As for the indirect method, system equivalence can be made at the AC or DC terminal of the interlinking converter when impedance models within subsystems are unavailable such that preliminary knowledge of systems can be simplified. Importantly, the equivalence of these two methods on the observability of system components is revealed through theoretical analysis. The proposed impedance participation analysis methods are illustrated with a 4-bus hybrid AC/DC system, a modified 28-bus hybrid AC/DC system and a modified 96-bus hybrid AC/DC system. Numerical calculations and time-domain simulations are performed to validate the theoretical analysis.

Small-signal Stability Analysis for Large-scale Power Electronics-based Power Systems

Small-signal Stability Analysis for Large-scale Power Electronics-based Power Systems

Critical Department Analysis for Large-Scale Outpatient Systems

Identifying critical department(s) to enhance the supply in large-scale systems is beneficial to support the system efficiency. Large-scale outpatient systems (LSOSs) are usually faced with crowdedness and, hence, require critical departmental improvement to maintain patient satisfaction under a limited budget. Besides, when demand surges (DSs) or physicians are absent supply loss (SL), critical department identification becomes one of the key steps to resilient clinical management. To improve the clinical services and mitigate the risk of disruptions efficiently, we conduct critical department analysis under three scenarios: one clinical improvement scenario supply enhancement (SE) and two clinical disruption scenarios (DS and SL). These scenarios can happen in different departments in varying time sessions (e.g., am or pm). We define the criticality of a department as the change of patient satisfaction with respect to the change of departmental supply and demand. We accordingly propose a simulation-based ranking method and implement a case study in an LSOS. The simulation results show that the criticality of the department highly depends on the time session. Surprisingly, SE may reduce patient satisfaction when the supply increases in several specific departments. Key findings and managerial insights are further discussed.

(Q, S, R)-Dissipativity Analysis of Large-Scale Networked Systems

This brief investigates the (Q,S,R)-dissipativity of large-scale networked systems in the discrete-time case. The networked system consists of a large number of subsystems, each of which can have different dynamic characteristics, and the connections among subsystems are arbitrary. When the number of subsystems is large, the traditional analysis method based on lumped description may have computational difficulties. To solve this problem, some computationally attractive conditions are derived, which essentially depend on the block-diagonal structure of the system parameter matrices and the sparseness of the subsystem connection matrix. Numerical simulations illustrate that compared with the existing results, the conditions suggested in this brief have higher computational efficiency in the dissipative analysis of large-scale networked systems.

Linear quadratic mean-field game-team analysis: A mixed coalition approach

Mean-field theory has been extensively explored in decision analysis of large-scale (LS) systems but traditionally in “pure” cooperative or competitive settings. This leads to the so-called mean-field game (MG) or mean-field team (MT). This paper introduces a new class of LS systems with cooperative inner layer and competitive outer layer, so a “mixed” mean-field analysis is proposed for distributed game-team strategy. A novel asymptotic mixed-equilibrium-optima is also proposed and verified.

Transceiver Beamforming for Over-the-Air Computation in Massive MIMO Systems

This paper investigates the transmitter and receiver beamforming (TB and RB) for over-the-air computation (AirComp) in massive multiple-inputs and multiple-outputs (MIMO) systems. First, we propose a two-phase hybrid beamforming algorithm to design TB and hybrid RB. In the first phase, we adopt a projected gradient descent with momentum (PGDM) algorithm to search for the optimal fully-digital TB matrices. Compared with the benchmarks on the mean square error (MSE) performances, PGDM can achieve up to 5 dB gain in signal-to-noise ratio (SNR) with less algorithm execution time when fully-digital RB is assumed. In the second phase, we plug the TB matrices obtained in PGDM as well as the optimal baseband RB (BBRB) matrix into the MSE objective, and adopt gradient descent to search for the optimal radio-frequency RB (RFRB) matrix. Compared with the state-of-the-arts, the proposed two-phase algorithm reduces up to 30% of the algorithm execution time and 18% of the MSE. Second, we propose a statistical TB algorithm to reduce the communication overheads, in which TB completely depends on statistical channel state information (CSI) and thus does not rely on the feedback from the base station (BS). We prove that orthonormal matrices are asymptotically optimal for statistical TB when uncorrelated <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Rayleigh</i> channels are assumed and the number of receiving antennas approaches to infinity. For correlated channels, experimental results show that the proposed statistical TB can achieve about 5 dB gain in SNR compared with orthonormal matrices in terms of the MSE performance. Third, a large scale system analysis is made in this paper. As the number of the receiving antennas approaches to infinity, asymptotically optimal choices for TB and RB are provided, and upper bounds of MSE are derived in terms of the number of clients and receiving antennas. For hybrid RB, an upper bound of the squared distance between the optimal hybrid RB and the optimal fully-digital RB is also derived.

Compositional Analysis of Probabilistic Timed Graph Transformation Systems

The analysis of behavioral models is of high importance for cyber-physical systems, as the systems often encompass complex behavior based on, e.g., concurrent components with mutual exclusion or probabilistic failures on demand. The rule-based formalism of Probabilistic Timed Graph Transformation Systems (PTGTSs) is a suitable choice when the models representing states of the system can be understood as graphs and timed and probabilistic behavior is important. However, model checking PTGTSs is limited to systems with rather small state spaces. We present an approach for the analysis of large-scale systems modeled as PTGTSs by systematically decomposing their state spaces into manageable fragments. To obtain qualitative and quantitative analysis results for a large-scale system, we verify that results obtained for its fragments serve as overapproximations for the corresponding results of the large-scale system. Hence, our approach allows for the detection of violations of qualitative and quantitative safety properties for the large-scale system under analysis. We consider a running example in which shuttles drive on tracks of a large-scale topology and autonomously coordinate their local behavior with other shuttles nearby. For this running example, we verify that (a) shuttles can always make the expected forward progress using several properties, (b) shuttles never collide, and (c) shuttles are unlikely to execute emergency brakes in two scenarios. In our evaluation, we apply an implementation of our approach in the tool AutoGraph to our running example.

Bifurcation Analysis Software and Chaotic Dynamics for Some Problems in Fluid Dynamics Laminar–Turbulent Transition

The analysis of bifurcations and chaotic dynamics for nonlinear systems of a large size is a difficult problem. Analytical and numerical approaches must be used to deal with this problem. Numerical methods include solving some of the hardest problems in computational mathematics, which include system spectral and algebraic problems, specific nonlinear numerical methods, and computational implementation on parallel architectures. The software structure that is required to perform numerical bifurcation analysis for large-scale systems was considered in the paper. The software structure, specific features that are used for successful bifurcation analysis, globalization strategies, stabilization, and high-precision implementations are discussed. We considered the bifurcation analysis in the initial boundary value problem for a system of partial differential equations that describes the dynamics of incompressible ABC flow (3D Navier–Stokes equations). The initial stationary solution is characterized by the stability and connectivity to the main solutions branches. Periodic solutions were considered in view of instability transition problems. Finally, some questions of higher dimensional attractors and chaotic regimes are discussed.

Saturable Voltage-Behind-Reactance Models of Induction Machines Including Air-Gap Flux Harmonics

Accurate and numerically efficient models of induction machines are of critical importance for reliable analysis and simulation of large-scale power systems. Specifically, modeling magnetic saturation that causes air-gap flux harmonics, which can significantly affect machine dynamics, has been the focus of many research efforts. In this paper, two voltage-behind-reactance (VBR) models are proposed for induction machines which formulate the air-gap flux harmonics caused by the main flux saturation. Specifically, the proposed constant-parameter VBR (CPVBR) model can be conveniently interfaced with the external network using constant <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RL</i> branches and controlled voltage sources. The numerical performance of the two proposed VBR models is validated and benchmarked against the state-of-the-art models of induction machines with saturation and air-gap flux harmonics. It is shown that the proposed models offer superior numerical performance (i.e., higher accuracy and simulation speed) compared to the existing models, which would be beneficial for offline and/or real-time simulations of power systems.

Research on Scale Effect of Resistance Components for Full-Formed Ship Based on Large-Scale Model Towing Test

In recent years, the International Maritime Organization (IMO) has gradually introduced more stringent new Ship Energy Efficiency Design Index (EEDI) bills, and transport ships are more inclined to reduce the speed and increase the length and square coefficient to meet the design requirements. However, the size of the ship model that can be accommodated in the towing tank is seriously limited. Under the action of the scale effect, the accuracy of the prediction results of the resistance performance of large ships is particularly prominent. To break through the limitations of the test site, a large-scale ship model resistance towing test system and data analysis method in the port were established. By comparing with the results of small-scale model tests in the towing tank, the applicability of the 1957 ITTC friction line and Grigson friction line in the resistance prediction of the full-formed ship was analyzed, and the scale effects of resistance components were also examined. The results show that the scale effect of the form factor of full-formed ships is weak. The three-dimension method based on the empirical formula of mixed-form friction resistance of ITTC-Grigson is more suitable for predicting the resistance performance of full-formed ships.

Large-scale correlation network construction for unraveling the coordination of complex biological systems

Advanced measurement and data storage technologies have enabled high-dimensional profiling of complex biological systems. For this, modern multiomics studies regularly produce datasets with hundreds of thousands of measurements per sample, enabling a new era of precision medicine. Correlation analysis is an important first step to gain deeper insights into the coordination and underlying processes of such complex systems. However, the construction of large correlation networks in modern high-dimensional datasets remains a major computational challenge owing to rapidly growing runtime and memory requirements. Here we address this challenge by introducing CorALS (Correlation Analysis of Large-scale (biological) Systems), an open-source framework for the construction and analysis of large-scale parametric as well as non-parametric correlation networks for high-dimensional biological data. It features off-the-shelf algorithms suitable for both personal and high-performance computers, enabling workflows and downstream analysis approaches. We illustrate the broad scope and potential of CorALS by exploring perspectives on complex biological processes in large-scale multiomics and single-cell studies.

Dissipativity Analysis of Large-Scale Networked Systems

This paper investigates the dissipativity analysis of large-scale networked systems with linear time-invariant dynamics. The networked system is composed of a large number of subsystems whose connections are arbitrary, and each subsystem can have different dynamics. A sufficient and necessary condition for the strict dissipativity analysis of the networked system is derived, which takes advantage of the block-diagonal structure of the system parameter matrix and the sparseness characteristics of the subsystem interconnections. Then, a necessary condition and a sufficient condition that depend only on a single subsystem parameter are given separately. Numerical simulations illustrate that compared with the existing results, the conditions suggested in this paper have higher computational efficiency in the dissipative analysis of large-scale networked systems.

Scalable risk assessment of large infrastructure systems with spatially correlated components

Risk assessment of spatially distributed infrastructure systems under natural hazards shall treat the performance of individual components as stochastically correlated due to the common engineering practice in the community including similarities in building design code, regulatory practices, construction materials, construction technologies, and the practices of local contractors. Modelling the spatially correlated damages of an infrastructure system with many components can be computationally expensive. This study addresses the scalability issue of risk analysis of large-scale systems by developing an interpolation technique. The basic idea is to sample a portion of components in the systems and evaluate their correlated damages accurately, while the damages of remaining components are interpolated from the sampled components. The new method can handle not only linear systems, but also systems with complex connectivity such as utility networks. Two examples are presented to demonstrate the proposed method, including cyclone loss assessment of the building portfolios in a virtual community, and connectivity analysis of an electric power system under a scenario cyclone event.

Exhaustive modal analysis of large-scale power systems using model order reduction

This paper presents an efficient modal analysis methodology that computes all modes of any given large-scale power system in exhaustive manner using the model order reduction techniques. For this, a reduced order model is generated using the Balanced Truncation (BT) method for which the controllability and observability gramians are approximated using the low-rank Cholesky factors. This leads to a rapid identification of classes of coupled dynamic devices of the original system. Next, approximated oscillatory modes are computed for each class. Finally, the exact values of the oscillatory modes of the overall power system are determined by iterative computations (the Modified Arnoldi method) initialized to the approximated modes found at the first step. The proposed methodology is able to put into evidence all coupling modes of any given large-scale power system (containing power electronics or any other specific dynamic devices). No a priori knowledge about the pattern of oscillations is needed. The accuracy and efficiency of the proposed methodology are thoroughly validated on several power systems with different orders, including a large scale model of the interconnected European power system.

Green hydrogen production: Analysis for different single or combined large-scale photovoltaic and wind renewable systems

Hydrogen is a promising energy carrier to provide sustainable energy use throughout the world. Researchers and policy-makers have focused on investigations in three areas of hydrogen-related technologies in the energy market: (1) alternative fuel production based on hydrogen and carbon dioxide; (2) hydrogen injection to the natural gas pipeline networks; (3) usage of hydrogen in transportation applications. One of the most important challenges facing hydrogen technology development is the production of green hydrogen, which can be achieved through water electrolysis coupled with renewable power generation. Although many studies have been conducted, there is still a need for further development, which requires open-source big data and models and standardization of the processes to compare different renewable-based hydrogen production systems. To fill this research gap, the performance of a grid-connected hybrid wind turbine and solar photovoltaic-based water electrolysis systems for large-scale green hydrogen production were investigated. The objective is to propose an accurate methodology to compare wind and solar systems, or hybrid ones, for green hydrogen production worldwide. A large dataset describing the hybrid wind turbine-photovoltaic hydrogen production in various locations was created by performing dynamic simulations using TRNSYS and analyzed using MATLAB and Excel. Several dimensionless indicators were employed and assessed for standardizing the performance evaluation procedure of renewable-based hydrogen production systems, including the electrolyser load portion satisfied by the wind turbine and photovoltaic, the generated wind turbine and photovoltaic energy portion supplied to the electrolyser load and the quantity of energy exported to and imported from the grid. The annual and monthly values of these indicators together with the total amount of green hydrogen production were estimated for 28 global locations. The procedure applied can be easily used to test small-scale applications like residential users or large-scale applications like industrial users, as well as for any hydrogen demand and climatic conditions.

Foundations and Applications of Information Systems Dynamics

Although numerous advances have been made in information technology in the past decades, there is still a lack of progress in information systems dynamics (ISD), owing to the lack of a mathematical foundation needed to describe information and the lack of an analytical framework to evaluate information systems. The value of ISD lies in its ability to guide the design, development, application, and evaluation of large-scale information system-of-systems (SoSs), just as mechanical dynamics theories guide mechanical systems engineering. This paper reports on a breakthrough in these fundamental challenges by proposing a framework for information space, improving a mathematical theory for information measurement, and proposing a dynamic configuration model for information systems. In this way, it establishes a basic theoretical framework for ISD. The proposed theoretical methodologies have been successfully applied and verified in the Smart Court SoSs Engineering Project of China and have achieved significant improvements in the quality and efficiency of Chinese court informatization. The proposed ISD provides an innovative paradigm for the analysis, design, development, and evaluation of large-scale complex information systems, such as electronic government and smart cities.

Evaluation of different scale-up strategies for Haematococcus pluvialis cultivation in airlift photobioreactors

Large scale algal biomass production can be very challenging due to the potential issues of sustainability, environmental ethics, and economic concerns. A strategic approach to the transition from the laboratory to the industrial scale allows the prediction of process characteristics, design and analysis of large scale systems, and reduction of extra costs. In this study, a scale-up procedure that considered different approaches was carried out by selecting the Haematococcus pluvialis as a model organism. Three scale-up parameters (constant mixing time (tm), volumetric power consumption rate (P/V), and oxygen mass transfer coefficient (kL a)) were tested for biomass production in a 2-L airlift photobioreactor and they were compared with those obtained from a 1-L aerated cultivation bottle. Among three strategies, the maximum cell concentration, 4.60±0.20×105 cells/mL, was obtained in a constant volumetric power consumption rate experiment. Also, total carotenoid amount showed similar changes with the cell concentration and reached the maximum concentration of 2.02±0.11 mg/L under constant P/V experiment. However, the cultivation bottle presented the highest biomass amount of 0.62 g/L and specific growth rate of 0.38 day-1 of all of the photobioreactors. This result might be attributed to the low aeration rates or improper configuration of the system, which created a non-homogenous culture medium and led to ineffective mass transfer.&nbsp;

Surrogate modeling for dynamic analysis of an uncertain notched rotor system and roles of Chebyshev parameters

The non-intrusive Chebyshev surrogate coupled with the harmonic balance method is developed to calculate harmonics and super-harmonic responses of an uncertain notched rotor, i.e., rotor with an open crack. The deterministic rotor model is formulated by the finite element method and an open crack in the elastic shaft introduces the asymmetry fault. A large size crack in the middle span of the shaft is considered, which makes the system susceptible to variations of parameters. The scanning approach is used to validate the accuracy of the surrogate function. Importantly, roles of Chebyshev parameters on performance are studied and proved. It is found that the Chebyshev order is the crucial factor to reduce the spurious peaks and overestimation near critical speeds of the rotor model. An improved surrogate function with fewer collocations is formulated to solve uncertain problems with many uncertainties and high orders are required in surrogate models. It is found that the surrogate function can efficiently and accurately estimate the uncertain responses of the notched rotor with multi-interval variables. The results will benefit interval uncertainty analysis of general large-scale and sensitive mechanical systems.

A flexible and reliable method for spectrum analysis of large-scale power systems

With interfacing various equipment in modern power systems, oscillation stability is the prior requirement for safe operation of power systems. For oscillation analysis, eigenvalue computation by state space model of power systems is a well-developed method, but still worthy of studying due to existing issues in practical application. Especially, for large-scale systems, high dimension of state space model, undesired distribution of eigenvalues and finite computing resources make eigenvalue computation challenging. This paper proposes a method for searching eigenvalues in user-specified spectrum region of interest. The method is designed with two layers, which are search navigator in upper layer and kernel solver in lower layer, respectively. The search navigator divides computation of all target eigenvalues into a sequence of search tasks, and enables flexibility on specifying search region and adaptivity to computing platforms. The kernel solver is implemented by Krylov-Schur algorithm with restarting strategy highly adaptive to various distributions of eigenvalues. The restarting strategy contributes well reliability on finding eigenvalues without omission. Effectiveness and reliability of the proposed method are validated by numerical experiments on three test power systems.

A general framework of Bayesian network for system reliability analysis using junction tree

To perform the reliability analysis of complex and large-scale systems, Bayesian network (BN) can be useful as it facilitates modelling the causal relationship between multiple types of variables, e.g. hazards, material properties, and inspection results. However, its conventional approach shows limitations in handling large-scale systems and advanced inference tasks such as continuous distributions and approximate inference. On the other hand, these issues have been successfully addressed by system reliability analysis (SRA) theory, while the complexity of system reliability methods (SRMs) makes it challenging to handle multiple types of variables collectively. Accordingly, to facilitate the reliability analysis of real-world problems, this paper develops a general framework to implement BN for SRA by employing junction tree (JT). The connection between BN and SRA is further consolidated by summarizing common computational challenges and proposing heuristics to resolve them. While it provides a systematic way to implement SRMs within the BN framework, such generalization can also be used to enhance the functionality of the general-purpose software programs developed for BN as demonstrated by the companion Matlab®-based toolkit BNS-JT. The applicability and efficiency of the proposed framework are demonstrated by numerical examples.