Prediction of critical generator buses in transient stability using synchrophasor data

Renewable energy generation has different static and transient characteristics than traditional synchronous power plants. The connection of renewable energy to the grid will have varying degrees of impact on the voltage stability of the local power grid. In a power grid with large renewable energy penetration, in addition to the voltage stability problem, renewable energy integration changes the original power flow distribution, line transmission power and inertia of the entire system, the power system transient stability has undergone tremendous changes. Renewable energy power generation technology and grid-connected scale are developing rapidly. The technical requirements for renewable energy and the research on grid-connected technology need to be continuously deepened and improved. However, some large-scale renewable energy off-grid accidents in recent years have brought serious threats to the security and stability of power systems, and have also raised higher research requirements for the stability of large-scale renewable energy grid-connected. This paper provides an introduction about the control and stability of renewable energy grid integration on both technologies and standardization aspects, and tries to explore potential the trend in active power and frequency control, reactive power and voltage control, security and stability control respectively caused by the integration of RE generation into power systems.

This paper proposes an energy storage controller synthesis method for voltage restoration in microgrids with respect to temporal logic specifications (TLSs). TLSs is introduced in this paper as a formalism to control the voltage variation of a critical bus against an operational bounds over time. The power system with synchronous generator (SG) connected to a critical load bus is modeled as a set of differential-algebraic equations and a simplified analytical model is derived to describe the voltage variation of this critical bus. The control objective is to schedule an optimal control input signal from a supportive energy storage system (ESS) connected to the critical bus, such that the voltage variation of the latter satisfies the TLSs, such as a finite-time restoration. The proposed control is verified on a lumped distribution system model. With this control diagram, supportive controllers can be designed to make voltage behaviors comply with grid codes and avoid unnecessary relay actions.

Today’s power systems are operated closer to their stability limits due to the continuously growing load demands, interface to open markets, and integration of more renewable energies. In order to provide operators with clear insight on the current system situation, near real-time power systems dynamic security assessment tools are required. One of the core elements of near real-time dynamic security assessment tools is contingency screening and ranking. Most of the commercially available tools screen and rank contingencies by using the traditional numerical integration or Transient Energy Functions (TEFs) or hybrid methods. The traditional numerical integration method is accurate but computationally intensive and has a slow assessment speed which makes it difficult to identify any insecure contingency before it happens. Despite the TEF method of transient stability analysis being relatively fast, it develops less accurate results due to models simplification and assumptions. This paper introduces transient stability based on fast and robust contingency screening and ranking using an Adaptive step-size Differential Transformation (AsDTM) method. Based on the most current snapshot from Supervisory Control and Data Accusation (SCADA) data, the proposed method triggers AsDTM-based transient stability simulation for each credible contingency and evaluates Transient Stability Indices (TSI) as the normalized weighted sum of squares of errors derived from state variables and complex bus voltages at every simulation time step. Finally, contingencies are ranked based on these TSI and the worst contingency is identified for the next detail assessment. The method is tested on IEEE 9 bus and 39 bus test systems. Test results reveal that the proposed method is faster, robust, and can be used in near real-time dynamic security assessment sessions.

Guest Editorial: Situational awareness of integrated energy systems

It is important to search voltage stability margin (VSM) of an interconnected power system in order to determine secure operation constraints. Traditionally, centralised continuation power flow (CPF) is used, which may fail to model the varied load growth directions of different regional power grids. In this study, a distributed VSM searching method is proposed grounding on a coordinated CPF (CCPF) performed by neighbouring dispatch centres. First, a distributed power flow model for VSM is established, which considers the automatic allocation of network loss. Then, a critical bus of the power system is used to indicate the system‐level voltage stability. It is chosen according to the sensitivity of the minimum singular value of Jacobi matrix to nodal voltage amplitudes, and the sensitivity of boundary power injection to nodal voltage amplitudes. Moreover, the gradient of critical bus voltage amplitude to regional loading parameters is computed, which is set as the load growth direction for the current step. The severest VSM is obtained by solving the CCPF iteratively along the worst load growth direction. Tests on IEEE 118 bus system and a real power grid of China validate the proposed method in the enhancement of the security for interconnected power systems.

Impact of renewable energy penetration rate on power system transient voltage stability

In the category of small signal stability problem, one of the major causes of unpredictability of power transfer in the inter-connected power system is due to low frequency oscillations (LFO). These oscillations in the inter-connected power system, affects the power transfer capability and thereby, needed to be suppressed. To damp the oscillation and protect the power system, power system stabilizers are used. In this study, a Kho-Kho optimization (KKO) based proportional integral derivative (PID) power system stabilizer is put forward which can suppress the LFO in the inter-connected power system. Optimization methods are widely being used to solve number of optimization problem. Therefore, in this work the specification of the stabilizer are calibrated using KKO technique by optimizing a objective function constructed using the Integral time square error (ITSE) of the speed deviation. To test the effectiveness of the designed optimal controller, a one machine infinite bus (OMIB) with IEEE type DC-1 exciter unit is also taken into consideration. The superiority of the proposed technique is examined by comparing the obtained results with some other existing techniques.

Guest Editorial

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.

Conventional control techniques such as proportional integral (PI) control and proportional integral derivative (PID) control are widely used as the load frequency controller in power system control applications; however, the increase in complexity of the power system is degrading the performance of classical control. Therefore, in this paper a new control approach using fractional calculus has been proposed for the load frequency control problem of two-area hydro-thermal power system. The paper presents an interconnected hydro-thermal power system working under different operating conditions introduced in the form of various nonlinearities. Four case studies have been presented in this paper considering transient analysis with (i) different loading conditions, (ii) parameter variations, (iii) different nonlinearities (governor dead band nonlinearity, time delay and generation rate constraints), and (iv) superconducting magnetic energy storage (SMES) device. A tilt integral derivative (TID) control has been presented as a secondary controller to stabilize the frequency deviations occurring in the two-area power system with the above-mentioned different operating conditions. The parameters of TID controller have been optimized using a differential evolution algorithm which solves an optimization problem formulated using the integral of time-weighted absolute error (ITAE) performance index. In addition, a comparison of dynamic system response obtained using TID control and PID control has been presented, which focusses on the better performance of TID control over PID control in an interconnected power system.

Maintaining synchronous and stable operation in interconnected power system at minimum cost is complex problem. To ensure the continuous supply of electricity all synchronous generators must remain in synchronism during abnormal conditions also. In this work, Distributed Static Series Compensator (DSSC) is used to maintain required transient stability in power system during severe three-phase to ground fault and, it is found that DSSC is capable of maintaining synchronous operation in a considered two machine power system along with power system stabilizer as a supplementary controller.

This research explores the resurgence of DC applications in power systems, focusing on the integration of DC microgrids and the effectiveness of control strategies in managing such systems. The research aims to investigate how artificial intelligence (AI) can enhance the efficiency of DC microgrids, especially in the context of renewable energy sources (RES) integration. The methodology involves a comprehensive review of existing literature on the evolution of DC and AC power systems, with a particular emphasis on voltage regulation. The research examines various DC microgrid control methods, including centralized, decentralized, distributed, and hierarchical strategies. Special attention is given to the role of AI, machine learning, and the Internet of Things (IoT) in the tertiary level of hierarchical control, which aims to optimize system performance. The findings highlight the advantages of DC microgrids, particularly their compatibility with RES like Solar Photovoltaics (PV) and energy storage systems, as well as modern electrical appliances. Hierarchical control, with its primary, secondary, and tertiary levels, effectively manages voltage, power sharing, and operational efficiency. The tertiary level of control, when combined with AI technologies, significantly enhances the microgrid's performance through real-time data analysis and predictive decision-making, improving responsiveness and the integration of renewable energy. The research concludes that hierarchical control methods, augmented by AI, enable reliable, stable, and efficient operation of DC microgrids. These strategies improve the coordination of distributed generation, reduce operational costs, and enable participation in energy markets, promoting the sustainability of power systems. Future research should focus on advanced AI algorithms for optimization, exploring scalable control methods for larger microgrids and hybrid AC-DC systems to enhance energy transfer and storage capabilities.

Large‐scale renewable energy (RE) integration in the power systems is displacing conventional sources of generation, thus reducing the system's inherent inertia and primary frequency response (PFR) capabilities. This reduced response may decline the system's ability to stabilise frequency after inevitable events such as loss of generation or load and thus requires additional PFR. To meet the PFR requirements, fast‐acting resources like energy storage systems (ESS) and demand response (DR) (transferrable and interruptible loads) need to be integrated within the system. In this regard, a novel stochastic security‐constrained unit commitment framework is proposed to assess the potential of ESS and DR to ensure additional PFR requirements and handle post contingency frequency dynamics. Moreover, the proposed methodology analyses the impact of uncertain RE integration on system frequency dynamics using Bayesian inference statistics. Case studies are carried out on 39 bus New England and 118 bus IEEE test systems, incorporating post fault frequency security parameters. Simulation results analyse the PFR contribution of ESS and DR and indicate a substantial reduction in system operating cost and RE curtailment with their integration. The proposed analysis would help system operators to maintain required PFR under high RE penetration, and handle unavoidable contingencies.

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