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The photomultiplier tube (PMT) and silicon photomultiplier (SiPM) of small areas have the characteristics of fast time response, suitable for the detection of fast and extremely weak light signals, and the transit time spread (TTS) can be on the picosecond scale. The test system is generally divided into two types: one is the direct acquisition of the waveform (DAW), (DAW such as the high-sampling oscilloscope), and the other is an indirect acquisition of the waveform (IDAW). In this article, both DAW and IDAW will be used to carry out the comparative test of ultra-fast photodetectors to complete the calibration of the performance of ultra-fast detectors and the study on time test systems. This will be helpful for beam experiments to be carried out in the laboratory and provide effective support for the development of domestic fast PMT. [ABSTRACT FROM AUTHOR]

This paper describes the two test systems for voltage stability studies set up by the IEEE PES Task Force on “Test Systems for Voltage Stability Analysis and Security Assessment” under the auspices of the Power System Stability Subcommittee of the Power System Dynamic Performance Committee. These systems are based on previous test systems, making them more representative of voltage stability constraints. A set of representative results are provided for both systems, with emphasis on dynamic simulation. They illustrate various aspects such as long-term dynamics, voltage security assessment, real-time detection, and corrective control of instabilities. The value for educators, researchers and practitioners are emphasized. [ABSTRACT FROM AUTHOR]

The dc voltage and frequency $ (PVF)$ or modified dc voltage and frequency $ (PV^{2}F)$ double droop control is commended for its ability to regulate both the dc voltage and the frequency in a decentralized approach. However, a convincing response is not achieved due to an interaction between the droop characteristics of dc voltage and frequency. This interaction affects the dc voltage and frequency support of the ac-system-surrounded multiterminal HVdc (AC-MTdc) grid. To overcome this effect, a Duo control strategy is proposed in this article, which takes advantage of a bipolar voltage-source converter topology in the MTdc grid. The virtue of the proposed control technique is emphasized by comparing it with the existing $ PV^{2}F$ double droop control along with three case studies and two test systems. The validation of the interactionless Duo control strategy is carried out on a five-terminal CIGRE dc grid benchmark model integrated into a two-area power system (AC-MTdc grid-1) and a New England IEEE 39-bus system (AC-MTdc grid-2). These test systems are simulated in PSCAD/EMTdc software. [ABSTRACT FROM AUTHOR]

Harmonic state-space (HSS) theory has been an effective method for studying system stability with time-periodic characteristics, such as modular multilevel converters (MMCs) and renewable power generation under unbalanced grid conditions. However, the original state-space formulation of the HSS model comprises infinite-dimensional matrices. Truncation is necessary before practical computing application. Therefore, this letter proposes a truncation number selection method for the HSS model. The theoretical basis of the proposed method is based on the Floquet characteristic exponent of the linear time-periodic model, which has a straightforward physical meaning. Finally, a case study of an MMC grid-tied system with tests in RT-LAB illustrates the validity of the proposed method. [ABSTRACT FROM AUTHOR]

This letter presents a novel sequential black-start restoration model to improve the system resilience after a natural disaster in an active distribution network. Two challenges have been addressed: First, a new set of radiality constraints is designed as the network topology is changing along the restoration paths; Second, a black-start restoration model is proposed where multiple backup black-start units in the system are coordinated to find the best restoration paths. Case studies on two IEEE test systems verify the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

An efficient probabilistic energy flow (PEF) analysis method is proposed for integrated electricity and gas systems (IEGSs) in this letter. A network decoupling based deterministic energy flow (DEF) calculation method is developed. A PEF analysis method is presented based on stochastic response surface method (SRSM). The computational efficiency and convergence performance of DEF and PEF are largely improved. The correctness and effectiveness of the proposed method are verified by using three test systems. [ABSTRACT FROM AUTHOR]

Recently, the study of fault diagnosis and prognosis of discrete-event systems (DESs) has received considerable attention. This article aims to investigate the decentralized fault prognosis of stochastic DESs (SDESs). The notion of $m$ -step stochastic-coprognosability, called $S_{m} $ -coprognosability, is formalized to capture the capability of stochastic systems to predict a fault at least $m$ steps in advance under the decentralized framework. The verifier is constructed from the stochastic decentralized system, in which $n$ local prognosers are deployed to send the local prognostic decisions to a coordinator for calculating the final prognostic decision. In particular, a necessary and sufficient condition of $S_{m}$ -coprognosability of stochastic systems is derived, and an algorithm for testing $S_{m} $ -coprognosability is given, which is polynomial to the number of states and events but exponential to the number of local sites. Furthermore, the maximum number of $m$ for making the given SDES to be $S_{m} $ -coprognosable is discussed. Note to Practitioners—This article extends the fault prognosis methods of SDESs from centralized framework to decentralized framework, such that for many technologically complex systems whose information collection is scattered in physically separated different sites, every local site makes decision based on information collected by own sensors, without communicating with other local sites, which is more appropriate than the centralized method. [ABSTRACT FROM AUTHOR]

Electric vehicle (EV) has been widely used in our life, one of the key technologies is the batteries, power accumulator battery test system (PABTS), which is initiated for evaluating the performance of the EV batteries, has been used in many battery-manufacture companies. The parallel operation of the PABTS forms a dc-microgrid, owing to the low inertia of the dc-link capacitance, the charging and discharging tests of the batteries can easily cause dc-bus voltage fluctuations, which may jeopardize the system stability. To increase the system inertia and achieve good system stability, a fractional-order model-predictive-control (FOMPC) and fractional-order virtual-inertia-control (FOVIC) strategy (namely, FOMPC-FOVIC method) is proposed for the bidirectional grid-connected converter. First, the fractional-order virtual inertial link is used to replace the integral-order virtual inertial link, which significantly improves the system stability. Second, combined with fractional-order model-predictive-control, virtual dc current compensation is proposed to further suppress the dc-bus voltage fluctuations. Finally, the fractional-order discrete state-space equation of the virtual inertial link is derived, and the cost function design and its optimal solution are elaborated. To demonstrate the effectiveness of the proposed FOMPC-FOVIC scheme, experimental results indicate that the proposed method is superior to the existing methods in terms of inertial support and dc-bus voltage regulation. [ABSTRACT FROM AUTHOR]

The existing research on voltage-source converter HVDC (VSC-HVDC) system stability mostly focuses on small-signal stability analysis methods. However, when large-signal disturbances occur, the intrinsic nonlinearity of the VSC-HVDC system becomes inevitable so that the small-signal studies are no longer valid. In this paper, a large-signal stability analysis method of the VSC-HVDC system is proposed based on the estimation of domain of attraction (DOA). This method can not only analyze the asymptotic stability of the operating point, but also answer the question of how large deviations from the operating point can be tolerated by the system. By using Takagi-Sugeno (T-S) fuzzy model and Lyapunov stability theorem, the DOA of the VSC-HVDC System at the operating point is estimated, and the large-signal stability of VSC-HVDC System is analyzed. On this foundation, the influence of system parameters on the large-signal stability is studied. The results can be used to guide the adjustment of system parameters to solve the problem of system instability. The time-domain simulations conducted in Matlab/Simulink are used to test the stability of the system under large-signal disturbance in the range of DOA. The simulation results verify the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

It is possible to launch undetectable load-redistribution (LR) attacks against power systems even in systems with protection schemes. Therefore, it is imperative to detect LR attacks in power systems and establish corrective actions to provide secure dispatch points. This paper develops a systematic real-time LR threat analysis (RTLRTA) tool to flag LR attacks and identify all affected transmission assets. Since attackers might introduce some forms of random strategies to create LR attacks, we introduce different optimization models to generate random LR attacks to determine accurate thresholds for our detection index and test the tool’s functionality. Additionally, based on an estimation for the actual loads in the post-attack stage, we design a set of physical line flow security constraints (PLFSCs) that can be added to the existing security-constrained economic dispatch (SCED) models. This leads to appropriate responses to the identified LR attacks and provides secure dispatch points. We generate multiple scenarios of LR attacks and random errors for different target lines in the 2383-bus Polish test system to validate our proposed methods’ accuracy and functionality in detecting LR attacks and responding to them. [ABSTRACT FROM AUTHOR]

The increasing complexity and high cost of integrated systems have placed immense pressure on root-cause analysis and diagnosis. In light of artificial intelligence and machine learning, a large amount of intelligent root-cause analysis methods have been proposed. However, most of them need historical test data with root-cause labels from repair history, which are often difficult and expensive to obtain. We propose a two-stage unsupervised root-cause-analysis method in which no repair history is needed. In the first stage, a decision-tree model is trained with system test information to cluster the data in a coarse-grained manner. In the second stage, frequent-pattern mining is applied to extract frequent patterns in each decision-tree node to precisely cluster the data so that each cluster represents only a small number of root causes. The proposed method can accommodate both numerical and categorical test items. A combination of the L-method, cross validation, and Silhouette score enables us to automatically determine all hyperparameters. Two industry case studies with system test data demonstrate that the proposed approach significantly outperforms the state-of-the-art unsupervised root-cause-analysis method. [ABSTRACT FROM AUTHOR]

Machine learning (ML) has automated a multitude of our day-to-day decision-making domains, such as education, employment, and driving automation. The continued success of ML largely depends on our ability to trust the model we are using. Recently, a new class of attacks called backdoor attacks have been developed. These attacks undermine the user’s trust in ML models. In this article, we present Neo, a model agnostic framework to detect and mitigate such backdoor attacks in image classification ML models. For a given image classification model, our approach analyzes the inputs it receives and determines if the model is backdoored. In addition to this feature, we also mitigate these attacks by determining the correct predictions of the poisoned images. We have implemented Neo and evaluated it against three state-of-the-art poisoned models. In our evaluation, we show that Neo can detect $\approx$ 88% of the poisoned inputs on average and it is as fast as 4.4 ms per input image. We also compare our Neo approach with the state-of-the-art defence methodologies proposed for backdoor attacks. Our evaluation reveals that despite being a blackbox approach, Neo is more effective in thwarting backdoor attacks than the existing techniques. Finally, we also reconstruct the exact poisoned input for the user to effectively test their systems. [ABSTRACT FROM AUTHOR]

This paper presents a novel methodology for the construction of a transient stability boundary (TSB) that overcomes the lack of TSB analytical description for multiple operating states and contingencies in power systems. The proposed approach models the TSB as a nonlinear mapping between the system parameters of interest and the corresponding critical clearing time (CCT). This compact mathematical expression is built based on an efficient discriminative network, broad learning system (BLS). While keeping a high accuracy and generalization ability, the newly introduced construction method provides an efficient update strategy that does not require an entire retraining cycle. These properties make this method suitable for online transient stability assessment (TSA). The prospects of the developed method are verified via case studies by employing the IEEE 9-bus, IEEE 39-bus (New England) test systems and a real system of China Southern Power Grid. In comparison with existing methods, the newly introduced algorithm has a higher prediction accuracy and improved robustness. The demonstrated characteristics indicate that the proposed method may serve as a valuable tool in the framework of online TSA. [ABSTRACT FROM AUTHOR]

The strength has a large impact on the commutation failure (CF) in hybrid multi-infeed HVdc (HMIDC) systems including both voltage-source converters and line-commutated converters. However, this impact has always been quantified by the simulation-based method in earlier works, which is very time-consuming and cannot lend the exhaustively theoretical perspective. Thus, in this letter, the mathematical expression of the CF immunity index as the analytical function of the hybrid multi-infeed interactive effective short-circuit ratio strength index is first developed based on the quasi-steady-state model of HMIDC systems. Thereafter, the developed expression is used for analytically quantifying the impact of the strength on the CF in a much more efficient manner with more sufficiently theoretical perspective compared to the simulation-based method in earlier works. Finally, the theoretical developments are validated by the experimental results of the hardware-in-the-loop platform based on a hybrid six-infeed HVdc test system. [ABSTRACT FROM AUTHOR]

Fundamental sensor feedback limitations for improving rotor angle stability using local frequency or phase angle measurement are derived. Using a two-machine power system model, it is shown that improved damping of inter-area oscillations must come at the cost of reduced transient stability margins, regardless of the control design method. The control limitations stem from that the excitation of an inter-area mode by external disturbances cannot be estimated with certainty using local frequency information. The results are validated on a modified Kundur four-machine two-area test system where the active power is modulated on an embedded high-voltage dc link. Damping control using local phase angle measurements, unavoidably leads to an increased rotor angle deviation following certain load disturbances. For a highly stressed system, it is shown that this may lead to transient instability. The limitations derived in the paper may motivate the need for wide-area measurements in power oscillation damping control. [ABSTRACT FROM AUTHOR]

In hybrid multi-infeed HVdc (HMIDC) systems comprising both voltage-source and line-commutated converters’ inverters, the strength has a significant effect on the temporary overvoltage (TOV). However, this effect has always been assessed by the simulated approach in earlier works. It is unable to provide the sufficiently theoretical perspectives and also time-consuming as onerous electromagnetic transient simulations are required. Therefore, in this letter, the mathematical expression of the TOV is first derived as the analytical function of the hybrid multi-infeed interactive effective short-circuit ratio (HMIESCR) strength index. This derivation is achieved by using the quasi-steady-state analytical model of HMIDC systems with the interinverter interactions considered. Then, the derived expression is utilized for analytically assessing the effect of the HMIESCR on the TOV versus various system parameters and operation variables. Compared to the simulated approach, the proposed analytical approach here can offer more sufficiently theoretical perspectives and is also more efficient as simulations are no more required. Finally, the experimental results of a hybrid tri-infeed HVdc test system based on the hardware-in-the-loop platform validate the analytical approach. [ABSTRACT FROM AUTHOR]

In order to quantify the impact of uncertainties on power systems resulted from renewable energy, a novel interval power flow method based on multi-dimensional holomorphic embedding method (MDHEM) and tight semidefinite relaxation technique are proposed. First, the MDHEM is used to address the spatial correlation of renewable energy basis, and the analytical expressions of bus voltages and active branch flows are derived. Second, the general interval power flow (IPF) model can be cast as a box constrained polynomial optimization problem. Third, a tight semidefinite relaxation is designed to solve this special optimization problem. Simulation results on several large-scale test systems show the effectiveness and computational tractability of the proposed model. [ABSTRACT FROM AUTHOR]

This paper proposes a new distributed dispatch scheme to realize efficient coordinated real-time dispatch of the coupled transmission grid and active distribution grids (ADGs). In the proposed scheme, on the one hand, the concept of optimal power exchange interval is introduced to coordinate the transmission grid and ADGs so that the reserve capacity support from ADGs can be incorporated in the dispatch optimization of the transmission grid. On the other hand, uncertainties of renewable distributions are considered to ensure the robustness of dispatch decisions. With the analytical target cascading (ATC) method, the centralized distributionally robust dispatch model for the integrated transmission-distribution system is decoupled, leading to a number of independent small local optimization problems for the transmission grid and ADGs. Meanwhile, the diagonal quadratic approximation is adopted to develop an iterative coordination strategy where all local optimization problems are solved in a parallel manner, increasing the computational efficiency. By using the constrained cost variable technique (CCV) and a new affine policy, the original non-convex dispatch model is reformulated as a linear optimization problem, which ensures the convergence of the iterative process and further reduces the computational burden. Case studies on three test systems verify the effectiveness and efficiency of the proposed scheme. [ABSTRACT FROM AUTHOR]

The coordinated multi-area economic dispatch enables optimal resource utilization in a larger spatial range. To overcome drawbacks such as heavy communication burden, convergence failure, and weak scalability of iterative coordination methods, this paper proposes a fully non-iterative multi-area coordination framework. The proposed framework is based on a novel system reduction technique termed as the condensed system representation (CSR). The CSR makes external equivalence of the dispatch problem of each area by exploiting power system operating characteristics, i.e., only a small number of generators may become marginal units and only a minority of security constraints may be active. An algorithm based on the optimality condition analysis is developed to identify the CSR by fixing non-marginal units to their output bounds, eliminating redundant security constraints, and making Norton equivalence of the internal network. With CSRs submitted by local areas, the multi-area system can be optimized without iterative information exchange. Case studies based on a 3-area 9-bus system verify the effectiveness of the CSR-based coordination framework. Larger-scale test systems are constructed to validate the computational efficiency, robustness, and scalability of the proposed method. [ABSTRACT FROM AUTHOR]

The flexibility of power systems to manage variability and uncertainties is becoming increasingly important as the penetration of variable renewable energy continues to raise. Synergies from all parts of the existing system and new flexibility providers are required to balance demand and supply. However, because of fundamental limitations, existing test systems cannot fully support detailed and realistic studies. To fill this gap, this paper presents a 213-bus benchmark, called the FTS-213 system, dedicated for power system flexibility studies. This system has more than 38% of VRE penetration and includes real data at 15 minutes and 1 minute resolutions. The resources considered in the system cover all aspects of the generation, network, demand, energy storage and market. Specifically, to capture the intrinsic relationship between flexibility and renewable energy accommodation, the system contains integration grids, regional transmission grids and inter-regional tie lines. These assets reflect the full stack of utility-scale integration, transmission and consumption within and among regions. They cover multiple voltage levels, from 110 to 750 kV AC and $\pm$ 400 to $\pm$ 800 kV DC. The impacts of and the interactions between these flexibility factors are analyzed and three sets of planning results are provided. [ABSTRACT FROM AUTHOR]

This paper proposes a data-driven adjustable robust unit commitment (UC) model for integrated electric-heat systems (IEHSs), where the data-driven, and robustness adjustable features are endowed by the novel uncertainty modeling method. The devised uncertainty set is the intersections of a series of hyperplanes. It combines the merits of the traditional box-like uncertainty set, whose underlying computation burden is moderate, and the convex hull formed by historical data, which would lead to less conservative operation strategies. The boundaries of the bounding high-dimensional rectangle of the uncertainty set are set as decision variables to achieve the balance between the operation costs, and risk. The two-stage decision-making framework is employed in the robust UC model of IEHSs, in which the district heating networks are operated at the variable-flow-variable-temperature mode. The modified column-and-constraint generation (C, and CG) algorithm is employed to solve the proposed robust program, where an additional feasible region reduction step is embedded to decrease the computation burden of the worst case identification. Simulation results on two test systems verify the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]