System Test Cases Research Articles

Analytical expressions of the Q ‐factor for the complete resonant mode spectrum of the equilateral triangular waveguide cavity

This Letter presents the closed-form expressions of the unloaded Q -factor in metallic cavities with equilateral triangular cross section, computed from its analytical resonant mode solutions. The obtained analytical formulas for the Q -factor extend the very restricted range of problems with closed-form solutions, complementing the classic cases of the rectangular and circular cavities found in the literature. The presented derivation provides extremely rapid reference solutions for diverse applications such as filter design by test cases for microwave characterisation systems or numerical full-wave solvers. A universal Q -chart, valid for any aspect ratio, is given and the achieved analytical results for the first resonant modes are tested with numerical commercial software, showing excellent agreement.

Introducing Voltage-Level Dependent Parameters to Synthetic Grid Electrical Topology

Building synthetic power system test cases for testing, demonstrating, and cross-validating new innovations in smart grid applications is of great importance. In this paper, we propose a new two-phase methodology to enhance our random-topology synthetic grid modeling, called RT- nestedSmallWorld , by introducing voltage-level dependent parameters. Unlike the original per unit format of electrical topology in the model, the voltage-level dependent parameters will distinguish between transmission lines and transformers as we found different characteristics for them in terms of per unit and actual impedances. This could also help integrate relative geographical information to our synthetic grid model in the form of approximate line length and dependence on nominal voltage level. The interdependence of parameters and variables on the nominal voltage level is observed from actual power system data in North America. Next, the interdependence is mathematically formulated and verified using grid physical constraints derived from Kirchhoff’s and Ohm’s laws to serve in the building of random-topology transmission network for synthetic grids.

Safely Entering the Deep: A Review of Verification and Validation for Machine Learning and a Challenge Elicitation in the Automotive Industry

Deep neural networks (DNNs) will emerge as a cornerstone in automotive software engineering. However, developing systems with DNNs introduces novel challenges for safety assessments. This paper reviews the state-of-the-art in verification and validation of safety-critical systems that rely on machine learning. Furthermore, we report from a workshop series on DNNs for perception with automotive experts in Sweden, confirming that ISO 26262 largely contravenes the nature of DNNs. We recommend aerospace-to-automotive knowledge transfer and systems-based safety approaches, for example, safety cage architectures and simulated system test cases.

A Mathematical Programming Solution for Automatic Generation of Synthetic Power Flow Cases

A shortage of large power system data sets, as well as the frequent restrictions on sharing such models, have led to newfound interest in creating synthetic data that can be easily shared among researchers. This paper considers the problem of forming a power system test case from the constituent parts of realistic power grid samples. Starting from a topology, and samples of generation, load, and branches, we assemble systems while respecting the constraints imposed by a typical Optimal Power Flow problem. Expressed in this manner, the problem involves solving for permutations of the input data. Since permutations matrices are binary, the problem is linearized, allowing for a Mixed Integer Linear Problem formulation. The problem is further decomposed using the Alternating Direction Method of Multipliers as well as an Evolutionary Algorithm to facilitate scaling to larger system sizes. A post processing step is used to add shunt elements for reactive power planning. The resulting systems demonstrate statistically similar power flow behavior to reference systems. Finally, new analysis avenues, opened by synthesizing test cases according to the proposed method, are briefly introduced by creating fictitious systems with different topology models and examining how these affect power flow behavior.

Market‐based generator cost functions for power system test cases

Post-restructuring, generators are dispatched using cleared offers in the day-ahead market in the cyber-physical power system. This study proposes a novel method to design generator cost functions to emulate existing market costs for power system test cases. Cost functions on existing test cases are based on fuel costs, which do not represent organised markets. In such markets, the marginal cost of energy is determined by generator offers , not fuel costs. In this work, the authors classify real market generator offers from an independent system operator organised electricity market into generator types . Generator offers are used to develop market-based generator cost functions for use in power system test cases to emulate electricity market behaviour. The proposed method is illustrated using PJM data on eight standard power system test cases from a six bus 240 MW generation case to 2000 buses with 95,000 MW of generation. The marginal price of the proposed market-based generator costs shows on average 280% improvement in accuracy of simulating the day-ahead PJM marginal energy price over existing fuel-cost-based test cases from 2014 to 2016. By using the new market-based generator cost functions, power system simulation studies will better represent actual economic impacts.

Index-3 divide-and-conquer algorithm for efficient multibody system dynamics simulations: theory and parallel implementation

There has been a growing attention to efficient simulations of multibody systems, which is apparently seen in many areas of computer-aided engineering and design both in academia and in industry. The need for efficient or real-time simulations requires high-fidelity techniques and formulations that should significantly minimize computational time. Parallel computing is one of the approaches to achieve this objective. This paper presents a novel index-3 divide-and-conquer algorithm for efficient multibody dynamics simulations that elegantly handles multibody systems in generalized topologies through the application of the augmented Lagrangian method. The proposed algorithm exploits a redundant set of absolute coordinates. The trapezoidal integration rule is embedded into the formulation and a set of nonlinear equations need to be solved every time instant. Consequently, the Newton–Raphson iterative scheme is applied to find the system coordinates and joint constraint loads in an efficient and highly parallelizable manner. Two divide-and-conquer-based mass-orthogonal projections are performed then to circumvent the effect of constraint violation errors at the velocity and acceleration level. Sample open- and closed-loop multibody system test cases are investigated in the paper to confirm the validity of the approach. Challenging simulations of multibody systems featuring long kinematic chains are also performed in the work to demonstrate the robustness of the algorithm. The details of OpenMP-based parallel implementation on an eight-core shared memory computer are presented in the text and the parallel performance results are extensively discussed. Significant speedups are obtained for the simulations of small- to large-scale multibody open-loop systems. The mentioned features make the proposed algorithm a good general purpose approach for high-fidelity, efficient or real-time multibody dynamics simulations.

Industrially Applicable System Regression Test Prioritization in Production Automation

When changes are performed on an automated production system (aPS), new faults can be accidentally introduced in the system, which are called regressions. A common method for finding these faults is regression testing. In most cases, this regression testing process is performed under high time pressure and on-site in a very uncomfortable environment. Until now, there is no automated support for finding and prioritizing system test cases regarding the fully integrated aPS that are suitable for finding regressions. Thus, the testing technician has to rely on personal intuition and experience, possibly choosing an inappropriate order of test cases, finding regressions at a very late stage of the test run. Using a suitable prioritization, this iterative process of finding and fixing regressions can be streamlined and a lot of time can be saved by executing test cases likely to identify new regressions earlier. Thus, an approach is presented in this paper that uses previously acquired runtime data from past test executions and performs a change identification and impact analysis to prioritize test cases that have a high probability to unveil regressions caused by side effects of a system change. The approach was developed in cooperation with reputable industrial partners active in the field of aPS engineering, ensuring a development in line with industrial requirements. An industrial case study and an expert evaluation were performed, showing promising results.

Power Systems Topology and State Estimation by Graph Blind Source Separation

In this paper, we consider the problem of blind estimation of states and topology (BEST) in power systems. We use the linearized DC model of real power measurements with unknown voltage phases (i.e. states) and an unknown admittance matrix (i.e. topology) and show that the BEST problem can be formulated as a blind source separation (BSS) problem with a weighted Laplacian mixing matrix. We develop the constrained maximum likelihood (ML) estimator of the Laplacian matrix for this graph BSS (GBSS) problem with Gaussian-distributed states. The ML-BEST is shown to be only a function of the states second-order statistics. Since the topology recovery stage of the ML-BEST approach results in a high-complexity optimization problem, we propose two low-complexity methods to implement it 1) Two- phase topology recovery, which is based on solving the relaxed convex optimization and then finding the closest Laplacian matrix, and 2) Augmented Lagrangian topology recovery. We derive a closed-form expression for the associated Cramer-Rao bound (CRB) on the topology matrix estimation. The performance of the proposed methods is evaluated for the IEEE-14 bus test-case system and for a random network. It is shown that, asymptotically, the state estimation performance of the proposed ML-BEST methods coincides with the oracles minimum mean-squared-error (MSE) state estimator, and the MSE of the topology estimation achieves the proposed CRB.

Mapping the Effectiveness of Automated Test Suite Generation Techniques

Automated test suite generation (ATSG) is an important topic in software engineering, with a wide range of techniques and tools being used in academia and industry. While their usefulness is widely recognized, due to the labor-intensive nature of the task, the effectiveness of the different techniques in automatically generating test cases for different software systems is not thoroughly understood. Despite many studies introducing various ATSG techniques, much remains to be learned, however, about what makes a particular technique work well (or not) for a specific software system. In this paper, we seek an answer to the question: “What features of a software system impact the effectiveness of ATSG techniques?” Once these features are identified, can they be used to select the most effective ATSG technique for a particular software system? To this end, we have implemented the mapping the effectiveness of test automation (META) tool, a new framework that identifies important software features that can be used to select suitable ATSG techniques to apply to new software systems. We evaluate the framework on a large set of open-source software projects and three ATSG techniques. The evaluation indicates that the number of methods in a class, the coupling between object classes, and the response for a class are the most indicative of what makes a software system hard to test by different techniques. The decision tree for ATSG technique selection generated by the META framework has an 88% accuracy, as shown by n-fold cross validation.

Optimizing DER Participation in Inertial and Primary-Frequency Response

This paper develops an approach to enable the optimal participation of distributed energy resources (DERs) in inertial- and primary-frequency response alongside conventional synchronous generators. Leveraging a reduced-order model description of frequency dynamics, DERs’ synthetic inertias and droop coefficients are designed to meet time-domain performance objectives of frequency overshoot and steady-state regulation. Furthermore, an optimization-based method centered around classical economic dispatch is developed to ensure that DERs share the power injections for inertial- and primary-frequency response in proportion to their power ratings. Simulations for a modified New England test-case system composed of ten synchronous generators and six instances of the IEEE 37-node test feeder with frequency-responsive DERs validate the design strategy.

An improved ghost-cell sharp interface immersed boundary method with direct forcing for particle laden flows

In this paper, an accurate and stable sharp interface immersed boundary method(IBM) is presented for the direct numerical simulation of particle laden flows. The current IBM method is based on the direct-forcing method by incorporating the ghost-cell approach implicitly. An important feature of this IBM is the sharp representation of the solid surface, contrary to other variants of IBM for freely moving particles in which the solid surface is diffuse. Moreover, a correction of the diameter is not necessary for obtaining accurate results. The current ghost-cell IBM is stable because spurious oscillations incurred due to discontinuity in the pressure and velocity field in moving particle simulations is avoided. An algorithm for accurate torque computation is developed. The proposed algorithm is verified by comparison to an analytical expression and is shown to give a substantial improvement over the existing method. Finally, the present IBM is validated for various test cases of single and multi-particle systems and is shown to be accurate and robust for a wide range of flow conditions.

Optimizing Power–Frequency Droop Characteristics of Distributed Energy Resources

This paper outlines a procedure to design power–frequency droop slopes for distributed energy resources (DERs) installed in distribution networks to optimally participate in primary frequency response. In particular, the droop slopes are engineered such that DERs respond in proportion to their power ratings and they are not unfairly penalized in power provisioning based on their location in the distribution network. The main contribution of our approach is that a guaranteed level of frequency regulation can be obtained at the feeder head, while ensuring that the outputs of individual DERs conform to some well-defined notion of fairness. The approach we adopt leverages an optimization-based perspective and suitable linearizations of the power-flow equations to embed notions of fairness and information regarding the physics of the power flows within the distribution network into the droop slopes. Time-domain simulations from a differential algebraic equation model of the 39-bus New England test-case system augmented with three instances of the IEEE 37-node distribution network with frequency-sensitive DERs are provided to validate our approach.

Comprehensibility of system models during test design: a controlled experiment comparing UML activity diagrams and state machines

UML activity diagrams and state machines are both used for modeling system behavior from the user perspective and are frequently the basis for deriving system test cases. In practice, system test cases are often derived manually from UML activity diagrams or state machines. For this task, comprehensibility of respective models is essential and a relevant question for practice to support model selection and design, as well as subsequent test derivation. Therefore, the objective of this paper is to compare the comprehensibility of UML activity diagrams and state machines during manual test case derivation. We investigate the comprehensibility of UML activity diagrams and state machines in a controlled student experiment. Three measures for comprehensibility have been investigated: (1) the self-assessed comprehensibility, (2) the actual comprehensibility measured by the correctness of answers to comprehensibility questions, and (3) the number of errors made during test case derivation. The experiment was performed and internally replicated with overall 84 participants divided into three groups at two institutions. Our experiment indicates that activity diagrams are more comprehensible but also more error-prone with regard to manual test case derivation and discusses how these results can improve system modeling and test case design.

"Specification Technique for Virtual Testbeds in Space Robotics"

Systems Development for Space Missions is an engineering challenge that requires a highly integrated systems design approach. Multidisciplinary dependencies, project size, technology novelty, and diverse operational environment conditions increase overall systems complexity. Therefore, systematic validation and verification techniques that consider environmental and operational conditions are crucial for mission success. However, verification and validation of system requirements is hard to achieve under real conditions since physical prototyping tests in space environment are hardly possible. Virtual Testbeds are a promising approach for the early identification of technical risks by simulating the overall system with approximate real conditions, and thus, increase the overall engineering efficiency. They enable early feasibility studies and virtual commissioning of the system during integration phase. The application of virtual testbeds requires not only a formal specification of the System Under Development (SUD) but also a formal Specification Technique for Validation and Verification (V&V). However, existing MBSE approaches provide only poor concepts for a holistic specification of system Test Cases and Virtual Testbeds. In this paper, we propose an integrated Model-Based Specification Technique that facilitates an integrated specification of the system and relevant V&V aspects. We first analyze existing norms like VDI 2206 and ECSS-Std. in order to identify relevant V&V aspects. Second, we describe a specification approach for Virtual Testbeds. Third, we present a modeling language for the specification of those aspects. Finally, we apply the presented technique on an example from the space robotics domain. Our findings show that the presented technique helps to capture relevant V&V aspects according to the existing norms in the space robotics domain. However it is not limited to space and can easily be used for industrial and other complex mechatronic systems.

Optimal Fuzzy Controller Based on Chaotic Invasive Weed Optimization for Damping Power System Oscillation

This paper proposed an optimal fuzzy controller for damping the power system oscillation in multi-machine environment. In this strategy, the proposed controller is optimized by new chaotic invasive weed optimization algorithm. Furthermore, a new objective function has been considered to test the proposed controller in different load conditions which increase the stability of system after disturbances. For this purpose, the damping factor, damping ratio, and a combination of the damping factor and damping ratio were analyzed and compared with the proposed objective function. The effectiveness of the proposed strategy has been applied in two multi-machine power system test cases as three machine 9-bus IEEE standard and 10-machine 39-bus New England power systems. The eigenvalue analysis and nonlinear time-domain simulation results proof the effectiveness of the proposed strategy.

Reduction of Power System Dynamic Models Using Sparse Representations

This paper proposes a model reduction technique that simplifies the dynamic equations of complex power networks, using sparse representations of the system matrices. Instead of removing components from the state vector, elements from the system matrices are eliminated such that these matrices become sparse. This is achieved by three different numeric algorithms that approximate the original system model using fewer nonzero elements. These algorithms lead to simpler models, since the complexity of operations involving sparse matrices is primarily affected by the matrices density. Furthermore, this approach enables to identify significant dynamic relations between units in the network. The proposed methods are demonstrated on several test-case systems with 9 and 2383-buses. In these examples, more than ${\text{90}}$ % of the elements in the system matrices are eliminated.

Dual-stage constructed random graph algorithm to generate random graphs featuring the same topological characteristics with power grids

It is a common practice to simulate some historical or test systems to validate the efficiency of new methods or concepts. However, there are only a small number of existing power system test cases, and validation and evaluation results, obtained using such a limited number of test cases, may not be deemed sufficient or convincing. In order to provide more available test cases, a new random graph generation algorithm, named “dual-stage constructed random graph” algorithm, is proposed to effectively model the power grid topology. The algorithm generates a spanning tree to guarantee the connectivity of random graphs and is capable of controlling the number of lines precisely. No matter how much the average degree is, whether sparse or not, random graphs can be quickly formed to satisfy the requirements. An approach is developed to generate random graphs with prescribed numbers of connected components, in order to simulate the power grid topology under fault conditions. Our experimental study on several realistic power grid topologies proves that the proposed algorithm can quickly generate a large number of random graphs with the topology characteristics of real-world power grid.

A Metric-Based Validation Process to Assess the Realism of Synthetic Power Grids

Public power system test cases that are of high quality benefit the power systems research community with expanded resources for testing, demonstrating, and cross-validating new innovations. Building synthetic grid models for this purpose is a relatively new problem, for which a challenge is to show that created cases are sufficiently realistic. This paper puts forth a validation process based on a set of metrics observed from actual power system cases. These metrics follow the structure, proportions, and parameters of key power system elements, which can be used in assessing and validating the quality of synthetic power grids. Though wide diversity exists in the characteristics of power systems, the paper focuses on an initial set of common quantitative metrics to capture the distribution of typical values from real power systems. The process is applied to two new public test cases, which are shown to meet the criteria specified in the metrics of this paper.

Open-water and under-ice seasonal variations in trace element content and physicochemical associations in fluvial bed sediment.

Across the circumpolar world, intensive anthropogenic activities in the southern reaches of many large, northward-flowing rivers can cause sediment contamination in the downstream depositional environment. The influence of ice cover on concentrations of inorganic contaminants in bed sediment (i.e., sediment quality) is unknown in these rivers, where winter is the dominant season. A geomorphic response unit approach was used to select hydraulically diverse sampling sites across a northern test-case system, the Slave River and delta (Northwest Territories, Canada). Surface sediment samples (top 1 cm) were collected from 6 predefined geomorphic response units (12 sites) to assess the relationships between bed sediment physicochemistry (particle size distribution and total organic carbon content) and trace element content (mercury and 18 other trace elements) during open-water conditions. A subset of sites was resampled under-ice to assess the influence of season on these relationships and on total trace element content. Concentrations of the majority of trace elements were strongly correlated with percent fines and proxies for grain size (aluminum and iron), with similar trace element grain size/grain size proxy relationships between seasons. However, finer materials were deposited under ice with associated increases in sediment total organic carbon content and the concentrations of most trace elements investigated. The geomorphic response unit approach was effective at identifying diverse hydrological environments for sampling prior to field operations. Our data demonstrate the need for under-ice sampling to confirm year-round consistency in trace element-geochemical relationships in fluvial systems and to define the upper extremes of these relationships. Whether contaminated or not, under-ice bed sediment can represent a "worst-case" scenario in terms of trace element concentrations and exposure for sediment-associated organisms in northern fluvial systems. Environ Toxicol Chem 2017;36:2916-2924. © 2017 SETAC.

Grid Structural Characteristics as Validation Criteria for Synthetic Networks

This paper presents a methodology and set of validation criteria for the systematic creation of synthetic power system test cases. The synthesized grids do not correspond to any real grid and are, thus, free from confidentiality requirements. The cases are built to match statistical characteristics found in actual power grids. First, substations are geographically placed on a selected territory, synthesized from public information about the underlying population and generation plants. A clustering technique is employed, which ensures the synthetic substations meet realistic proportions of load and generation, among other constraints. Next, a network of transmission lines is added. This paper describes several structural statistics to be used in characterizing real power system networks, including connectivity, Delaunay triangulation overlap, dc power flow analysis, and line intersection rate. The paper presents a methodology to generate synthetic line topologies with realistic parameters that satisfy these criteria. Then, the test cases can be augmented with additional complexities to build large, realistic cases. The methodology is illustrated in building a 2000 bus public test case that meets the criteria specified.