A novel algorithm for fast static security analysis during power grid interaction

With the UHV (Ultra High Voltage) power grid construction and the interconnection of regional power grids, the scale of power grids in China is increasing rapidly. At the same time, significant uncertainty and variability is being introduced into power grid operation with the integration of large-scale renewable energy in power systems. All of these pose an enormous challenge to the operation control of power systems in China. For a long time, online static security analysis, as an important part of EMS (Energy Management System), has been an effective tool for power grid operation. However, it is increasingly difficult for traditional static security analysis in serial computing mode to be online applied in bulk power grids in China. A new practical parallel approach for online static security analysis is put forward in this paper. A multithread parallelism is introduced into contingency screening, detailed contingency evaluation and decision support for reducing the execution time. By employing the multithread technology, the hardware resources of multi-processor/multi-core computer can be fully used and the program can be speeded up effectively. The performance of the parallel static security analysis is demonstrated by tests on two large-scale power systems. The test results show that the proposed method can be online applied in real bulk power grids.

Since security check for scheduling plans faces the problem of heavy computing burdens and inefficient utilization of parallel computation platform, a method based on contingency screening and parallel computation for multi-period cases is proposed to complete the calculation within a given time. Scheduling plans are divided into groups with adjacent time stamps based on core number of parallel computation platform and average number of screened contingencies to ensure that transient stability analysis, static security analysis and dynamic stability analysis can be finished in similar time. Security check results of day-ahead, intraday and real-time plan are designated with priority from low to high to form the queue for contingency screening. Queue of security check results will be updated once the security and stability analysis of a plan with higher priority is finished. Plans with available historical results will be chosen to reduce the number of plans needing security and stability analysis for all contingencies. The procedure of security check consists of three stages, including power flow data generation, security and stability analysis and decision-making. Dispatch strategy will finish the calculation of all plans at each stage and allocate cores by the submission time of plans to ensure load balance. Real engineering applications in actual power grid have fully confirmed the validity and rapidity of this method.

This paper introduces a new approach of power system static security analysis based on the vulnerability index (VI) and network contribution factor (NCF) method. Vulnerability index method provides quantitative vulnerability information about generation, transmission, load condition, and the whole system. NCF method gives fast approximate power flow results due to parameter change (contingency) based on the base load flow condition and network information. The contingency list can be chosen based on NCF method and VI evaluation. Comparison with the full AC power flow method shows that this approach is promising for fast and accurate static security analysis

The potential applications and challenges of uncertain data mining have recently attracted interests from researchers. Most uncertain data mining algorithms consider aleatory (random) uncertainty of data, i.e. these algorithms require that exact probability distributions or confidence values are attached to uncertain data. However, knowledge about uncertainty may be incomplete in the case of epistemic (incomplete) uncertainty of data, i.e. probabilities of uncertain data may be imprecise, coarse, or missing in some applications. The paper focuses on uncertain data which miss probabilities, specially, value-uncertain discrete objects which miss probabilities (for short uncertain objects). On the other hand, classification is one of the most important tasks in data mining. But, to the best of our knowledge, there is no method to learn Naïve Bayesian classifier from uncertain objects. So the paper studies Naïve Bayesian classification of uncertain objects. Firstly, the paper defines interval probabilities of uncertain objects from probabilistic cardinality point of view, and bridges the gap between uncertain objects and the theory of interval probability by proving that interval probabilities are F-probabilities. Secondly, based on the theory of interval probability, the paper defines conditional interval probabilities including the intuitive concept and the canonical concept, and the conditional independence of the intuitive concept. Further, the paper gives a formula to effectively compute the intuitive concept. Thirdly, the paper presents a Naïve Bayesian classifier with interval probability parameters which can handle both uncertain objects and certain objects. Finally, experiments with uncertain objects based on UCI data show satisfactory performances.

The article discusses the approach to application security analysis in the mobile store developed for LG Electronics webOS. There are investigated the features of static security analysis applied to the program written using Ja- vaScript. We propose the description of the model intended to the malicious software identification as a pattern recognition system. This model specifies the various methods of software static security analysis.

A neural network approach to power system's static security analysis Is presented. This security analysis includes both security assessment and enhancement. For security assessment, a three-layer feedlorward network has been developed for a small 5-bus system. This network represents the nonlinear nature of the power system accurately enough to identify severe security violations. The momentum method was used to train the network. For security control(enhancement) of power systems, a recurrent network approach Is proposed to replace the existing expert system technique. Given an insecure operating state, the proposed approach will produce the operating points which result in a secure operation of the system. The preliminary results Indicate that neural network approach (given neural network hardware availability) can be used for on-line security analysis in a power system's control center enviroment.

A random set approach to the optimization of uncertain structures

The growing demand for productivity in hardware development opens up new opportunities for applying programming language (PL) techniques to hardware description languages (HDLs). Chisel, a leading agile HDL, embraces this shift by leveraging modern PL features to enhance hardware design productivity. However, verification for Chisel remains a major productivity bottleneck, requiring substantial time and manual effort. To address this issue, we advocate the use of static analysis —a technique proven well-suited to agile development workflows in software—for lightweight Chisel verification. This work establishes a theoretical foundation for Chisel static analysis. At its core is λ C , a formal core calculus of ChAIR (a Chisel-specific intermediate representation for analysis). λ C is the first formalism that captures the essence of Chisel while being deliberately minimal to ease rigorous reasoning about static analysis built on λ C . We prove key properties of λ C that reflect real hardware characteristics, which in turn offer a form of retrospective validation for its design. On the basis of λ C , we define and formalize the hardware value flow analysis (HVFA) problem, which underpins our static analyses for critical Chisel verification tasks, including bug detection and security analysis. We then propose a synchronized fixed-point solution to the HVFA problem, featuring hardware-specific treatment of the synchronous behavior of clock-driven hardware registers—the essential feature of Chisel programs. We further prove key theorems establishing the guarantees and limitations of our solution. As a proof of concept, we develop ChiSA (30K+ LoC)—the first Chisel static analyzer that can analyze intricate hardware value flows to enable lightweight analyses for critical Chisel verification tasks such as bug detection and security analysis. To facilitate thorough evaluation of both ChiSA and future work, we provide ChiSABench (11M+ LoC), a comprehensive benchmark for Chisel static analysis. Our evaluation on ChiSABench demonstrates that ChiSA offers an effective and significantly more lightweight approach for critical Chisel verification tasks, especially on large and complex real-world designs. For example, ChiSA identified 69 violable developer-inserted assertions in large-scale Chisel designs (9.7M+ LoC) in under 200 seconds—eight of which were recognized by developers and scheduled for future fixes—and detected all 60 information-leak vulnerabilities in the well-known TrustHub benchmark (1.1M+ LoC) in just one second—outperforming state-of-the-art Chisel approaches like ChiselTest’s bounded model checking and ChiselFlow’s secure type system. These results underscore the high promise of static analysis for lightweight Chisel verification. To encourage continued research and innovation, we will fully open-source ChiSA (30K+ LoC) and ChiSABench (11M+ LoC).

Multi-channel multi-core CPU parallel and CPU+GPU heterogeneous parallel are effective means to enhance Network Analysis Application computing. To solve the job scheduling problem of Network Analysis Application with multi-level dispatching, multi-user, multi-task in CPU/GPU heterogeneous cluster environment, a multi-user concurrent job scheduling method for Network Analysis Application in CPU/GPU cluster is proposed. According to the characteristics of Network Analysis Application, it is suggested that state estimation and dispatcher power flow should be accelerated in parallel with CPU, while static security analysis, perturbation power flow calculation and interruption capacity scanning should be accelerated in parallel with CPU+GPU. The job scheduling method proposed in this paper can satisfy the high concurrent requests of multi-level Dispatching & Control Center in the isomorphic and heterogeneous computing environments.

The operation of electric power systems can be managed remote and automatically from control centers using energy management systems (EMS). In these control centers many on-line and off-line functions are carried out periodically. Among those functions, we can list: the automatic generation control, state estimation, topological analysis, and static security analysis.

Thermo-electro-mechanical vibration analysis of nonlocal piezoelectric nanoplates involving material uncertainties

Traditional static functional connectivity analyses have shown distinct functional network alterations in patients with anti-N-methyl-d-aspartate receptor encephalitis. Here, we use a dynamic functional connectivity approach that increases the temporal resolution of connectivity analyses from minutes to seconds. We hereby explore the spatiotemporal variability of large-scale brain network activity in anti-N-methyl-d-aspartate receptor encephalitis and assess the discriminatory power of functional brain states in a supervised classification approach. We included resting-state functional magnetic resonance imaging data from 57 patients and 61 controls to extract four discrete connectivity states and assess state-wise group differences in functional connectivity, dwell time, transition frequency, fraction time and occurrence rate. Additionally, for each state, logistic regression models with embedded feature selection were trained to predict group status in a leave-one-out cross-validation scheme. Compared to controls, patients exhibited diverging dynamic functional connectivity patterns in three out of four states mainly encompassing the default-mode network and frontal areas. This was accompanied by a characteristic shift in the dwell time pattern and higher volatility of state transitions in patients. Moreover, dynamic functional connectivity measures were associated with disease severity and positive and negative schizophrenia-like symptoms. Predictive power was highest in dynamic functional connectivity models and outperformed static analyses, reaching up to 78.6% classification accuracy. By applying time-resolved analyses, we disentangle state-specific functional connectivity impairments and characteristic changes in temporal dynamics not detected in static analyses, offering new perspectives on the functional reorganization underlying anti-N-methyl-d-aspartate receptor encephalitis. Finally, the correlation of dynamic functional connectivity measures with disease symptoms and severity demonstrates a clinical relevance of spatiotemporal connectivity dynamics in anti-N-methyl-d-aspartate receptor encephalitis.

Robots are expected to come in direct contact with human at care facilities and/or homes soon. Motivated by the application of holding and/or transferring a patient applying a robot, this paper introduces the dynamic model, static analysis and control algorithm for nonprehensile manipulation of a two-rigid-link object applying two cooperative arms. Newton-Euler equations are applied for formulating the object dynamics while a visco-elastic model is applied for modeling the interaction between the object links and the arms. Static analysis specifying the equilibrium points based on the derived dynamical model is introduced. A PD controller with a disturbance observer is designed to control the object lifting-up motion. Static analysis as well as controlled object lifting-up motion simulation results is presented which show the validity of the proposed analysis and control algorithm.

To realize the on-line quick analysis of the steady-state stability margin for the weak section of a power grid, a method of dividing the important generator groups according to the impact of the system equivalent impedance on the static stability limits of the section is presented. By using the dynamic information provided by the Wide Area Measurement System (WAMS), the center of inertia (COI) of the section of the two sides system is determined. Then the steady-state stability limits of the transmission section and the static stability margin can be calculated. The algorithm is verified by taking the out-play cross-section of West Inner Mongolia as an example, the results show that the static stability power limit and the steady-state stability margin of the section can be obtained accurately according to the presented algorithm. This algorithm can provide an effective analytical method for the online static stability security analysis of a power system.

Owing to its advantages such as high reliability for power supply, flexible operating and dispatching mechanism and convenient transfer breaker, the 3/2 mode of connection has been greatly put into use in 500kv power stations and some 200kv load-center substations. However, more equipment may be subjected to power cut caused by some fault modes as long as the mode of connection is linked with primary equipment or the breaker is under the prophylactic repair mode. Based on the analysis of network topology and on-line identification technology to deal with equipment risk for protection and operation logic, it enables itself to automatically identify the latent fault mode which is contained within power-failure equipment with N-2 qualification or more and remind relevant dispatching working staff in accordance of the prophylactic repair of primary equipment or breaker under the mode of connection, meanwhile, through the combination of static and dynamic security analysis and maintenance scheduling, it will achieve the on-line prevention and control mechanism for equipment risk in large power grid.