Biblio

This contribution provides the implementation of a digital twin-based assistance system to be used in future control rooms. By applying parameter estimation methods, the dynamic model in the digital twin is an accurate representation of the physical system. Therefore, a dynamic security assessment (DSA) that is highly dependent on a correctly parameterized dynamic model, can give more reliable information to a system operator in the control room. The assistance system is studied on the Cigré TB 536 benchmark system with an obscured set of machine parameters. Through the proposed parameter estimation approach the original parameters could be estimated, changing, and increasing the statement of the DSA in regard to imminent instabilities.

Power system robustness against high-impact low probability events is becoming a major concern. To depict distinct phases of a system response during these disturbances, an irregular polygon model is derived from the conventional trapezoid model and the model is analytically investigated for transmission system performance, based on which resiliency metrics are developed for the same. Furthermore, the system resiliency to windstorms is evaluated on the IEEE reliability test system (RTS) by performing steady-state and dynamic security assessment incorporating protection modelling and corrective action schemes using the Power System Simulator for Engineering (PSS®E) software. Based on the results of steady-state and dynamic analysis, modified resiliency metrics are quantified. Finally, this paper quantifies the interdependency of operational and infrastructure resiliency as they cannot be considered discrete characteristics of the system.

The load margin due to voltage instability and small-signal instability can be a valuable measure for the operator of the power system to ensure a continuous and safe supply of electricity. However, if this load margin was calculated without considering system operating requirements, then this margin may not be adequate. This article proposes an algorithm capable of providing the power system load margin considering the requirements of voltage stability, small-signal stability, and operational requirements, as limits of reactive power generation of synchronous generators in dynamic security assessment. Case studies were conducted in the 107-bus reduced order Brazilian system considering a list of contingencies and directions of load growth.

Dynamic security assessment (DSA) is to ensure the power system being operated under a secure condition that can withstand potential contingencies. DSA normally proceeds periodically on a 5 to 15 minutes basis, where the system security condition over a complete time interval is merely determined upon the system snapshot captured at the beginning of the interval. With high wind power penetration, the minute-to-minute variations of wind power can lead to more volatile power system states within a single DSA time interval. This paper investigates the intra-interval variation (IIV) phenomenon in power system online DSA and analyze whether the IIV problem is deserved attention in future DSA research and applications. An IIV-contaminated testing environment based on hierarchical Monte-Carlo simulation is developed to evaluate the practical IIV impacts on power system security and DSA performance. The testing results show increase in system insecurity risk and significant degradation in DSA accuracy in presence of IIV. This result draws attention to the IIV phenomenon in DSA of wind-energy power systems and calls for more robust DSA approach to mitigate the IIV impacts.

This contribution provides the implementation of a holistic operational security assessment process for both steady-state security and dynamic stability. The merging of steady-state and dynamic security assessment as a sequential process is presented. A steady-state and dynamic modeling of a VSC-HVDC was performed including curative and stabilizing measures as remedial actions. The assessment process was validated by a case study on a modified version of the Nordic 32 system. Simulation results showed that measure selection based on purely steady-state contingency analysis can lead to loss of stability in time domain. A subsequent selection of measures on the basis of the dynamic security assessment was able to guarantee the operational security for the stationary N-1 scenario as well as the power system stability.

In operation centers, it is important to know the power transfer limit to guarantee the safety operation of the power system. The Voltage Stability Margin (VSM) is a widely used measure and needs to definition of a load growth direction (LGD) to be computed. However, different definitions of LGD can provide different VSMs and then the VSM may not be reliable. Besides, the measure of this power transfer limit usually is related to the Saddle-Node Bifurcation. In dynamic security assessment (DSA) is highly desirable to identify limit regions where the power system can operate safely due to Hopf (HB) and Saddle-Node (SNB) Bifurcations. This paper presents a modeling of the power system incorporating the LGD variation based on participation factors to evaluate the effects on the stability margin estimation due to HB and SNB. A direct method is used to calculate the stability margin of the power system for a given load direction. The analysis was performed in the IEEE 39 bus system.

This paper presents a methodology for utilizing Phasor Measurement units (PMUs) for procuring real time synchronized measurements for assessing the security of the power system dynamically. The concept of wide-area dynamic security assessment considers transient instability in the proposed methodology. Intelligent framework based approach for online dynamic security assessment has been suggested wherein the database consisting of critical features associated with the system is generated for a wide range of contingencies, which is utilized to build the data mining model. This data mining model along with the synchronized phasor measurements is expected to assist the system operator in assessing the security of the system pertaining to a particular contingency, thereby also creating possibility of incorporating control and preventive measures in order to avoid any unforeseen instability in the system. The proposed technique has been implemented on IEEE 39 bus system for accurately indicating the security of the system and is found to be quite robust in the case of noise in the measurement data obtained from the PMUs.

This paper presents a computational platform for dynamic security assessment (DSA) of large electricity grids, developed as part of the iTesla project. It leverages High Performance Computing (HPC) to analyze large power systems, with many scenarios and possible contingencies, thus paving the way for pan-European operational stability analysis. The results of the DSA are summarized by decision trees of 11 stability indicators. The platform's workflow and parallel implementation architecture is described in detail, including the way commercial tools are integrated into a plug-in architecture. A case study of the French grid is presented, with over 8000 scenarios and 1980 contingencies. Performance data of the case study (using 10,000 parallel cores) is analyzed, including task timings and data flows. Finally, the generated decision trees are compared with test data to quantify the functional performance of the DSA platform.

Online Dynamic Security Assessment (DSA) is a dynamical system widely used for assessing and analyzing an electrical power system. The outcomes of DSA are used in many aspects of the operation of power system, from monitoring the system to determining remedial action schemes (e.g. the amount of generators to be shed at the event of a fault). Measurement from supervisory control and data acquisition (SCADA) and state estimation (SE) results are the inputs for online-DSA, however, the SE error, caused by sudden change in power flow or low convergence rate, could be unnoticed and skew the outcome. Therefore, generator shedding scheme cannot achieve optimum but must have some margin because we don't know how SE error caused by these problems will impact power system stability control. As a method for solving the problem, we developed SE error detection system (EDS), which is enabled by detecting the SE error that will impact power system transient stability. The method is comparing a threshold value and an index calculated by the difference between SE results and PMU observation data, using the distance from the fault point and the power flow value. Using the index, the reliability of the SE results can be verified. As a result, online-DSA can use the SE results while avoiding the bad SE results, assuring the outcome of the DSA assessment and analysis, such as the amount of generator shedding in order to prevent the power system's instability.

In this paper, parallelization and high performance computing are utilized to enable ultrafast transient stability analysis that can be used in a real-time environment to quickly perform “what-if” simulations involving system dynamics phenomena. EPRI's Extended Transient Midterm Simulation Program (ETMSP) is modified and enhanced for this work. The contingency analysis is scaled for large-scale contingency analysis using Message Passing Interface (MPI) based parallelization. Simulations of thousands of contingencies on a high performance computing machine are performed, and results show that parallelization over contingencies with MPI provides good scalability and computational gains. Different ways to reduce the Input/Output (I/O) bottleneck are explored, and findings indicate that architecting a machine with a larger local disk and maintaining a local file system significantly improve the scaling results. Thread-parallelization of the sparse linear solve is explored also through use of the SuperLU_MT library.