Feedback Control Strategy for Transient Stability Application

Several major blackouts in the past have shown the need for advanced wide‐area monitoring and control (WAMC) techniques. Advanced synchrophasor visualization and monitoring can be realized with time‐referenced power system data that are collected by phasor measurement units (PMUs) using synchronized clocks. Presently, PMUs are being deployed around the world at a rapid rate for various power system applications. When a necessary number of PMUs are installed at optimal locations throughout the network, the complete state of the system can be observed. PMUs take real‐time measurements to determine the state of the power system and can be used to enhance state estimation efficiency. With PMUs in place, there are many control and protection schemes that can be implemented successfully to take preventive and corrective actions. These remedial action schemes (RASs) are classified by the IEEE Power System Relaying Committee (PSRC) as system integrity protection schemes (SIPSs). This work involved the development of a real‐time hardware test bed in order to analyze the transient stability of a simulated power system by using synchrophasors to visualize system stress across a transmission line with and without load‐shedding schemes. The real time digital simulator (RTDS®) was used to model the power system in real time. PMUs, a satellite‐synchronized clock, and a synchrophasor vector processor (SVP) were used to test the synchrophasor application. Copyright © 2010 John Wiley & Sons, Ltd.

With the development of science and technology, the cost of offshore wind power development and transmission has gradually decreased, making offshore wind power technology a research hotspot. The installed capacity has been increasing year by year. China has abundant offshore wind energy resources, which are much richer than those on land and are available for exploitation. Offshore wind speeds are stable and do not produce harmful substances. Therefore, studying the transient voltage stability of offshore wind power grid-connected systems to improve the utilization efficiency of offshore wind power and protect the ecological environment is critical. After large-scale wind power is connected to the grid, ensuring the stability of the system's transient voltage becomes crucial. This paper aims to deeply study the transient voltage stability of offshore wind farm grid-connected systems, providing theoretical support for the subsequent design and operation of offshore wind farms. A simulation model of a typical power system integrated with offshore wind farms was established using PSAT. Relevant transient voltage stability indices were calculated, and the impact of varying wind speeds on the transient voltage stability of the grid-connected system was investigated. Static Var Compensators (SVC) and Static Synchronous Compensators (STATCOM) were installed for comparative analysis. The results demonstrate that excessively low wind speeds degrade the system's transient stability, and the installation of SVC provides superior improvement in transient voltage stability compared to STATCOM.

The power transient stability analysis is one of the basis for determining the control strategy of power system security and stability. Considering the influence of power grid topology on the transient stability of power system, the transient stability evaluation model is constructed based on the graph attention neural network. The electrical components and their transient operation data are mapped to the graph data with the spatial topology characteristics of power system for model training, so as to improve the topological generalization performance of the model. The marginal contribution of input characteristics to the output of transient power angle stability evaluation model is quantitatively calculated based on Shapley additive explanation (SHAP), so as to improve the interpretability of data-driven method for transient power angle stability evaluation. The effectiveness of the proposed method is verified by the IEEE 39-bus system.

The Remedial Action Scheme (RAS) is designed to take corrective actions after detecting predetermined conditions to maintain system transient stability in large interconnected power grids. However, since RAS is usually designed based on a few selected typical operating conditions, it is not optimal in operating conditions that are not considered in the offline design, especially under frequently and dramatically varying operating conditions due to the increasing integration of intermittent renewables. The deep learning-based RAS is proposed to enhance the adaptivity of RAS to varying operating conditions. During the training, a customized loss function is developed to penalize the negative loss and suggest corrective actions with a security margin to avoid triggering under-frequency and over-frequency relays. Simulation results of the reduced United States Western Interconnection system model demonstrate that the proposed deep learning–based RAS can provide optimal corrective actions for unseen operating conditions while maintaining a sufficient security margin.

Transient voltage stability assessment of renewable energy grid based on residual SDE-Net

Intermittency of wind energy pose a great challenge for power system operation and control. Wind curtailment might be necessary at certain operating condition to keep the line flow within limit. Remedial Action Scheme (RAS) offers quick control action mechanism to keep reliability and security of the power system operation with high wind energy integration. In this paper, a new RAS is developed to maximize the wind energy integration without compromising the security and reliability of the power system based on a specific utility requirements. A new Distributed Linear State Estimation (DLSE) is also developed to provide the fast and accurate input data for the proposed RAS. A distributed computational architecture is designed to guarantee the robustness of cyber system to support RAS and DLSE implementation. The proposed RAS and DLSE is validated using modified IEEE-118 Bus system. Simulation results demonstrate the satisfactory performance of the DLSE and effectiveness of RAS.

Nowadays, integration of large-scale wind farms (WFs) into power systems is experiencing rapid growth. As this rapid integration can affect transient stability significantly, employing doubly fed induction generator (DFIG)-based wind turbines, which have shown better behavior regarding system stability, has attracted much attention. This research contributes to the literature by investigating the transient stability of the power system with increasing penetration of DFIG-based WFs. In the proposed framework, the current-balance form is utilized for the network equations, and in this way, transient stability is performed using time-domain simulation. According to the simulation results, when the rate of wind power generation exceeds 0.7 per-unit, the increasing trend of the critical clearing time (CCT) is reversed and the CCT decreases greatly with the increased wind power penetration. In addition, the reactive power compensation by DFIG, the gearbox ratio, the power system strength, and DFIG parameters are comprehensively investigated as effective parameters on transient stability. Since the rated rotor speed of DFIG significantly impacts the electrical torque and machine currents, the reduction of the rated rotor speed due to the change of the gearbox ratio has been investigated as one of the effective factors to improve the transient stability. The simulation results demonstrate the effectiveness of the proposed approach in improving power system transient stability.

Deployment of Remedial Action Schemes (RAS) is a cost-effective alternative when taking pre-contingency actions or building new infrastructure are not desirable. However, if not modeled adequately in operation and planning studies, RAS can impose a risk to systems reliability by unintended activation or interactions with other protection systems. In this paper, we explain the implementation and testing procedure of RAS models for real-time transient stability assessment tool at Peak Reliability. First, we implemented 11 RAS models in Western Interconnection using user-defined models (UDM) and tested their functionality through off-line and online studies. Then, we performed a one-day study to evaluate the impact of adding RAS models on transient stability limits and limiting contingencies. Our study demonstrates that incorporating RAS models in transient stability analysis provide a more accurate representation of system operating conditions. This can enhance operators situational awareness and their ability to take timely, effective actions.

This paper describes an index for judging the severity of transient events of power systems in simulation. The proposed transient stability index, known as the area‐based COI‐referred rotor angle index, is developed by considering the fact that a large‐sized power system is divided into several areas according to the coherency of generators in a particular area. It can be assumed that an equivalent single large machine can represent all the generators in that area. Thus, the assessment of rotor angles for all generators can be simplified by only assessing the index of areas in a power system. The effectiveness of the proposed index in assessing the stability of power systems and its ability in pinpointing the weakest area in the power system is analyzed. Furthermore, this paper developed an emergency control scheme known as the combined UFLS and generator tripping in order to stabilize the system when unstable faults occurred in a power system. The proposed index is used to identify the generator to be tripped when the developed emergency control scheme operates. The performance of the proposed index and the combined UFLS and generator tripping scheme are evaluated on the IEEE 39‐bus test system.

With widespread application of voltage source converter (VSC) as a key energy-conversion power electronic device by using the phase-locked loop (PLL) technique for synchronization, the system dynamics has become much complicated. In this paper, the nonlinear dynamics and transient stability of the PLL-based VSC system are investigated, within a unified framework of the (normalized) generalized swing equation. It is found that there are three different types of bifurcation, including the generalized saddle-node, Hopf, and homoclinic bifurcations. Within the coexistence parameter region, the basin boundary of the stable equilibrium point shows either a closed-loop or a fish-like pattern. With the help of the equal area criterion (EAC), the transient stabilities under different transient disturbances including short circuit, voltage dip, and power rise are analyzed. Because the equivalent damping of the VSC is state-dependent, the theoretical results based on the EAC are examined. Furthermore, based on the analytical results from the generalized swing equation, the principle for all major transient stability enhancement methods is uncovered. All these findings are well verified by extensive electromagnetic transient simulations. Therefore, the generalized swing equation provides a deeper physical insight and plays a crucial role in transient stability problems in power-electronic-dominated power systems, similar to the swing equation in traditional power systems.

Chapter 18 - Power System Stability

It is becoming increasingly difficult to conduct standard stability studies on modern power systems due to the growing use of power electronic devices. Power electronic converters, regardless of their power or voltage, must contend with a rising challenge known as electromagnetic transient stability. For power system stability analysis and control, transient stability assessment (TSA) is essential. On the basis of numerical integration of the dynamics equations for an EPS under consideration at a particular disturbance, a method for assessing transient stability reserves is described. In order to improve the transient stability of hybrid AC/DC power systems, a multi-HVDC emergency coordinated modulating method has been suggested in this study. Multi-DC lines are used to build and test the AC/DC hybrid power system. Machine learning models that forecast power system transient stability are more reliable, versatile, and robust if they incorporate knowledge of power system dynamics into their data gathering process. Fault location and how disturbance effects spread over the network are critical for determining unstable regions of operation, thus this determination is made using domain knowledge. That’s why traditional machine learning models may now be used in an instance transfer learning framework thanks to a whole new data gathering technique. Therefore, the suggested solution does not rely primarily on the collected data, but also incorporates system insights.

Comparison between inductive and resistive SFCL in terms of current limitation and power system transient stability

Transient stability refers to a power system's ability to maintain synchronism (i.e., operate in coordination without losing step) after a severe disturbance such as a fault, sudden generation loss, or a large load change.Since modern power systems are more stressed, ensuring transient stability has become a critical operational concern.These disturbances cause significant changes in generator rotor angles, power flows, and voltages.Because the system's behaviour is governed by nonlinear differential equations with no general analytical solution, numerical methods (especially point-by-point or step-by-step simulations) are used for analysis.This is particularly useful in calculating critical clearing times and analysing multi-machine systems

Remedial Action Schemes (RAS) provide automatic control action with high impact on system performance. In order to improve the resilience of the RAS against any single node failure and to guarantee the secured and reliable operation of the power systems, distributed implementations of the RAS is researched upon. The input data to such a distributed RAS must be of high quality. In addition, RAS operation must be fast. Traditional centralized state estimation, which feeds data to RAS is slow and cannot meet the requirements of RAS. New approach needs to be developed to provide the fast and accurate data to RAS. In order to solve this problem, distributed state estimation is developed as an alternative strategy to feed data to the RAS. This paper discusses the implementation of Distributed Linear State Estimation (DLSE) in a decentralized platform called Resilient Information Architecture Platform for Smart Grid (RIAPS). The DLSE algorithm is fully implemented in RIAPS platform and validated on a real-time testbed consisting of Real Time Digital Simulator, Phasor Measurement Units and BeagleBones. The effectiveness of the proposed approach is validated through online simulations on IEEE 14-bus test system under various cyber failures.