Power System Dynamics Research Articles

Resilience-oriented protection scheme for TCSC-compensated line

This paper presents a resilience-oriented protection scheme for TCSC-compensated Line. A cross-differential protection scheme is proposed to enhance the resilience of a parallel transmission line (PTL) in the presence of a thyristor controlled series capacitor (TCSC). The faulty phase(s) is (are) identified by estimating the spectral energy of the three-phase currents and computed by applying an efficient powerful signal processing tool known as fast discrete orthonormal S-transform (FDOST). The proposed scheme is widely evaluated against various faults and dynamic power system conditions. The obtained results indicate the proposed resilience-oriented protection scheme is adaptable to different power system scenarios. The scheme precisely classifies the fault with effective discrimination between internal and external faults on a transmission line and a response time of a maximum one cycle from the fault inception.

Temporal Evolution Assessment of Dynamic Tidal Power Including Turbine Effects

Dai, P.; Zhang, J., and Xiao, L., 2020. Temporal evolution assessment of dynamic tidal power including turbine effects. Journal of Coastal Research, 36(5), 1050–1058. Coconut Creek (Florida), ISSN 0749-0208.The dynamic tidal power system adopts a coast perpendicular dike in capturing tidal potential energy and is basin free as opposed to the conventional tidal barrage system. Since it is important for the developers to have detailed information of the power output characteristics prior to implementation, the temporal evolution of the power output has been studied to improve the understanding of the dynamic tidal power resource using a two-dimensional hydrodynamic model. The model accurately simulates the tidal motion characteristic of Chinese marginal seas. As an essential input for the temporal power estimation, the turbine operation is taken into account for this study, while the watertight dike has often been considered in previous feasibility studies. The results show that the monthly average power output increases, reaches a maximum, and then decreases with an increase in the number of turbines. The temporal evolution of power is featured by strong semidiurnal intermittency due to the semidiurnal tide. The peak power is recorded as 2.81 GW during spring tide, when 8% of the dike is opened for turbines. The magnitude reduces in both the middle and neap tide stages. Four peaks in the monthly average hourly power variation histogram were picked up, with much more homogeneity as compared with the power series during any specific tidal stage. Structurally, the T-branch added to the seaward tip of the I-shaped system is called the T end and forms the T-shaped system. It is proposed that this T-shaped system leads to an increase in production. The T end harvests substantially greater M2 energy than K1 energy near the seaward end of the system. The concentration of M2 energy contributes to the improvement in power production.

Power flow management controller within a grid connected photovoltaic based active generator as a finite state machine using hierarchical approach with droop characteristics

Grid integration of photovoltaic (PV) system with a hybrid energy storage can help not only in increasing more penetration of PV system into the network but also in improving the power system dynamics and control in addition to helping the demand side management. In this work, a PV system with a hybrid energy storage including a battery array and a super capacitor bank is going to work as an active generator with innovative load management and power flow control strategies for managing the active power demand locally considering the grid constraints. This work proposes an architecture for a PV based active generator, which can provide active power in controlled manner while maintaining the frequency stability within the power grid. With the proposed architecture and innovative control strategies, the load demand to the grid can be effectively reduced as the PV generated power can be maximally utilized locally and the power fluctuations can be compensated using the embedded energy storage. The power flow is managed using the hierarchical approach with the state-flow and droop characteristics as a finite state machine.

Reactive power optimization of dynamic power system based on QPSO algorithm

During the operation of the power system, there is a certain loss when electrical energy transmitting through the line, The losses in the line are usually dominated by active network losses. The current research mainly uses reactive power optimization to reduce the reactive power loss in the system. Traditional reactive power optimization is optimized for a certain static time, and the state of the equipment in the line does not change, which is meaningless for actual engineering.A full-text optimization model is established for the purpose of reducing active network loss. The QPSO algorithm is used to dynamically optimize the load of a certain place for different periods of time. Based on the optimization results, we control the the operating status to reduce the active network loss in the line.

Sensitivity Analysis of the Impact of the Sub- Hourly Stochastic Unit Commitment on Power System Dynamics

Subhourly modeling of power systems and the use of the stochastic optimization are two relevant solutions proposed in the literature to address the integration of stochastic renewable energy sources. With this aim, this paper deals with the effect of different formulations of the subhourly stochastic unit commitment (SUC) problem on power system dynamics. Different SUC models are presented and embedded into time domain simulations (TDS) through a cosimulation platform. The objective of the paper is to study the combined impact of different frequency control/machine parameters and different SUC formulations on the long-term dynamic behaviour of power systems. The analysis is based on extensive Monte Carlo TDS (MC-TDS) and a variety of scenarios based on the New England 39-bus system.

Topology Identification for Power Systems via Compressive Sensing Based on Transient Dynamics

In this brief, we study topology identification with data from the transient dynamics of power systems. An improved sparsity adaptive matching pursuit algorithm based on compressive sensing is proposed to deal with the sparse topology recovery problem. The effect of algorithm parameters on the recovery performance is analyzed. The merits of our proposed algorithm are demonstrated in numerical simulations.

PowNet: A Network-Constrained Unit Commitment/Economic Dispatch Model for Large-Scale Power Systems Analysis

PowNet is a free modelling tool for simulating the Unit Commitment/Economic Dispatch of large-scale power systems. PowNet is specifically conceived for systems characterized by the presence of variable renewable resources (e.g., hydropower, solar, and wind), whose penetration on the grid is strongly influenced by climatic variability and constrained by the availability of transmission capacity. To help users effectively capture the nuances of power system dynamics, PowNet is equipped with features that enable accuracy, transferability, and computational efficiency over large spatial and temporal domains. Specifically, the model (i) accounts for the techno-economic constraints of both generating units and transmission networks, (ii) can be easily coupled with models that estimate the status of generating units as a function of the climatic conditions, and (iii) explicitly includes import/export nodes, which are useful in representing cross-border systems. PowNet is implemented in Python and is compatible with any standard optimization solver (e.g., Gurobi, CPLEX). Its functionality is demonstrated on the Cambodian power system. <strong>Funding statement:</strong> This research is supported by Singapore’s Ministry of Education (MoE) through the Tier 2 project ‘Linking water availability to hydropower supply—an engineering systems approach’ (Award No. MOE2017-T2-1-143).

Risk-Based Active Power Redispatch Optimization

Risk-based redispatch optimization is proposed as a methodology to support the Transmission System Operator (TSO) with preventive remedial actions obtained by extending the security-constrained unit commitment/economic dispatch with constraints resulting from the risk assessed for the power system. Although being heuristic, the methodology is based on comprehensive dynamic security assessment as time-domain simulations are used, allowing to express the degree of all types of instabilities, e.g., caused by contingencies, in monetary terms. Therefore, the risk is assessed as the expected value of the cost incurred by the TSO. Such an approach forms a new pathway to including risk in planning procedures already used by TSOs. Results obtained for the IEEE39 dynamic power system, with costs assigned to load shedding and generator tripping due to single transmission lines short-circuits, are shown as a reference case.

Analysis of the impact of sub-hourly unit commitment on power system dynamics

This paper discusses the impact of the sub-hourly unit commitment problem on power system dynamics. Such an impact is evaluated by means of a co-simulation platform that embeds a sub-hourly stochastic mixed-integer linear programming security constrained unit commitment (sSCUC) into a time domain simulator, as well as includes a rolling planning horizon that accounts for forecast updates. The paper considers different sub-hourly sSCUC resolutions (i.e., 5 and 15 min) and different wind penetration levels (i.e., 25 and 50%). The focus is on the transient response of the system and on frequency variations following different sSCUC strategies, and different sSCUC wind power uncertainty and volatility. The case study consists of a comprehensive set of Monte Carlo simulations based on the 39-bus system.

Recent Progress and Future Research Direction of Nonlinear Dynamics and Bifurcation Analysis of Grid-Connected Power Converter Circuits and Systems

Since the discovery of nonlinear dynamics and chaotic behaviors of basic power converter circuits, stability analysis has been extended to more complex converter structures, paralleled and interconnected converters, microgrids, and power systems. While the analysis has long been identifying the parameters that cause various nonlinear phenomena, some work has shown direct relevance toward practical design of power converters, and control circuits. In this article, a review is conducted to highlight the key contributions of bifurcation analysis for power converter circuits and systems, and to discuss the ongoing work in this area.

Ultrafast Active Response Strategy against Malfunction Attack on Fault Current Limiter

Fault current limiter (FCL) is a crucial device to guarantee the corresponding breaker can clear the fault with over-limit short-circuit current (SCC). If a FCL is disabled by malicious cyber-attackers, the breaker will fail to clear the fault. Under this circumstance, the breaker failure protection system will be activated to trip all the connected transmission lines, resulting in a severe N-k contingency. In order to deal with the breaking failure caused by FCL malfunction attack, we propose an ultrafast active response strategy (UFARS) based on deep neural network framework. Firstly, an Long Short-Term Memory (LSTM) network is designed to extract features from the time sequence of SCC. Then, a deep reinforcement learning (RL) based approach is proposed to determine the optimal strategy to clear the fault. More specifically, with the features from the LSTM network, the deep RL will select and trip a combination of transmission lines connected to the faulty line, such that the SCC will become smaller than the breaking capacity. Thus, the fault can be cleared with the corresponding breaker. After the fault is cleared, the tripped connected transmission lines will be reclosed to recover the integrity of power system. An environment is established to simulate the power system dynamics and obtain the essential data to train the proposed deep neural network. Numerical results show that the proposed strategy can clear the fault with the minimum impact on power system stability.

A High-Accuracy Phasor Estimation Algorithm for PMU Calibration and Its Hardware Implementation

Phasor measurement units (PMUs) are one of the most effective devices for measuring power system dynamics, and it is critically important that they have good performance. This paper proposes a high-accuracy synchrophasor estimation algorithm and builds a PMU calibrator to offer reference values for PMU test and calibration in the laboratory. Based on a general signal-fitting model, a nonlinear-fitting-based phasor and frequency estimation algorithm using an iterative solution are proposed. A rate-of-change-of-frequency (ROCOF) estimation method using the filter spectrum characteristic of a least-squares method is proposed to improve ROCOF measurement accuracy under dynamic conditions. For PMU laboratory tests, an interference suppression method and a post-processing method for step tests are presented. Then, the selected hardware for the PMU calibrator is tested, and its influence on phasor measurement is analyzed. Simulations and experiments verify that the accuracy of the calibrator is at least 30 times better than the requirements in PMU compliance standards of both IEEE and China, indicating that it can be used for PMU testing and calibration. In addition, the calibrator is also verified that it can offer references with high accuracy under combined tests, since the proposed algorithm is based on one general signal-fitting model.

An Analysis of a Wind Turbine-Generator System in the Presence of Stochasticity and Fokker-Planck Equations

In power systems dynamics and control literature, theoretical and practical aspects of the wind turbine-generator system have received considerable attentions. The evolution equation of the induction machine encompasses a system of three first-order differential equations coupled with two algebraic equations. After accounting for stochasticity in the wind speed, the wind turbine-generator system becomes a stochastic system. That is described by the standard and formal Itô stochastic differential equation. Note that the Itô process is a strong Markov process. The Itô stochasticity of the wind speed is attributed to the Markov modeling of atmospheric turbulence. The article utilizes the Fokker-Planck method, a mathematical stochastic method, to analyse the noise-influenced wind turbine-generator system by doing the following: (i) the authors develop the Fokker-Planck model for the stochastic power system problem considered here; (ii) the Fokker-Planck operator coupled with the Kolmogorov backward operator are exploited to accomplish the noise analysis from the estimation-theoretic viewpoint.

Grid-Forming Power Converters Tuned Through Artificial Intelligence to Damp Subsynchronous Interactions in Electrical Grids

The integration of non-synchronous generation units and energy storage through power electronics is introducing new challenges in power system dynamics. Specifically, the rotor angle stability has been identified as one of the major obstacle with regards to power electronics dominated power systems. To date, conventional power system stabilizer (PSS) devices are used for damping electromechanical oscillations, which are only tuned sporadically leading to significant deterioration in performance against the ever-changing operating conditions. In this paper, an intelligent power oscillation damper (iPOD) is proposed for grid-forming converters to attenuate electromechanical inter-area power oscillation. In particular, the iPOD is applied to a synchronous power controller (SPC) based grid-forming power converter to increases gain of the active power control loop at the oscillatory frequency. Predictions regarding the mode frequency, corresponding to the current operating points, are given by an artificial intelligence ensemble model called Random Forests. The performance of the proposed controller is verified using the two area system considering symmetrical fault for random operating points. In addition, a comparison with PSS installed in each generator reveals the individual contribution with respect to the inter-area mode damping.

Load frequency controller for multisource interconnected nonlinear power system incorporating FACTs devices

The load frequency control for two area multisource interconnected power system model incorporating flexible AC transmission system (FACTs) devices is presented in this paper. The slow response of governor, the power swings and frequency oscillations tend to take longer time to settle to normal condition post disturbances. To overcome this condition, application of FACTs devices for frequency stabilisation under a small perturbation is studied and investigations are carried out on two area multisource interconnected power system model. The controller gains are tuned using genetic algorithm and the effect of FACTs devices for damping of power swings and frequency oscillations in an interconnected power system is studied and compared by the detailed analysis of power system dynamics. The power system model consists of thermal, hydro and doubly fed induction generator (DFIG)-based wind plant in each area. Governor deadband (GDB) and generation rate constraint (GRC) is also considered to study the effect of nonlinearity on the power system dynamics. It has been observed that FACTs enabled power system is very effective in damping out the power swings and local frequency oscillations caused due to disturbance in load. An improvement in the transient response and tie-line power oscillations is also quite appreciable.

Investigation of Impacts of Wind Source Dynamics and Stability Options in DC Power Systems With Wind Energy Conversion Systems

Wind energy conversion systems (WECSs), based on permanent magnet synchronous generators (PMSGs), are becoming common sources in dc grids. However, in previous dc grids integration studies, turbine-generator mechanical dynamics are represented by a single-mass model. A practical direct-drive connection in a PMSG-WECS yields lightly-damped torsional speed oscillations because of the double-mass mechanical nature of the generator and the wind turbine. Active damping strategies are usually employed to suppress the mechanical oscillations in a full back-to-back converter interfacing PMSG-WECSs into ac grids; nevertheless, the active damper performance in dc grids is unknown, particularly under dc grid uncertainties and, more importantly, the presence of dynamic and constant power loads commonly used in dc grids. To fill out this gap, this paper presents a detailed modeling and comprehensive stability assessment of a dc grid with a high penetration level of wind power generation. Moreover, stability enhancement strategies are proposed to increase the damping of the entire system, considering different operating and installation scenarios that might face a system integrator/designer. Time-domain simulation studies, based on nonlinear models, are conducted to validate the analytical results. Furthermore, hardware-in-loop real-time simulation studies demonstrate the feasibility of hardware implementation.

Swing equation in power systems: Approximate analytical solution and bifurcation curve estimate.

The swing equation plays a central role in the model and analysis of power system dynamics, including small-signal stability and transient stability. As it has the same form as that in a variety of different disciplines, such as the forced pendulum in mechanics, the classical mechanistic description of superconducting Josephson junctions in physics, and the classical second-order phase-locking loop in electronics, it has aroused general interest in science and engineering. In this paper, its approximate solution of the limit cycle is obtained by means of the incremental harmonic balance (IHB) method. It is found that the trouble of a more distorted limit cycle when the parameters are closer to the homoclinic bifurcation curve can be easily solved by incorporating higher order harmonics in the IHB method. In this way, we can predict the homoclinic bifurcation curve perfectly. In addition, the method is extended to study a generalized swing equation including excitation voltage dynamics.

Robust Adaptive Control of Maximum Power Point Tracking for Wind Power System

A novel data-driven robust approximate optimal Maximum Power Point Tracking (MPPT) control method is proposed for the wind power generation system by using the adaptive dynamic programming (ADP) algorithm. First, a data-driven model is established by a recurrent neural network (NN) to reconstruct the wind power system dynamics using available input-output data. Then, in the design of the controller, based on the obtained data-driven model, the ADP algorithm is utilized to design the approximate optimal tracking controller, which consists of the steady-state controller and the optimal feedback controller. Ulteriorly, developing a robustifying term to compensate for the NN approximation errors introduced by implementing the ADP method. Based on the Lyapunov approach, it proves the stability of the designed model and controller to show that the proposed controller guarantees the system power asymptotically tracking the maximum power. Finally, the simulation results demonstrate that the control method stabilizes the tip speed ratio near the optimal value when the wind speed is lower than the rated wind speed. Moreover, the tracking response speed of the proposed method is fast, which enhances the stability and robustness of the system.

Problems and challenges of power-electronic-based power system stability: A case study of transient stability comparison

With the development of power electronic technology and requirement for clean energy, the traditional power systems which are dominated by synchronous generators are gradually changing into the power-electronic-based power systems with diversified power electronic equipment. The power systems are facing a great revolution in their primary equipment, and this has not happened in the past one hundred years. In recent years, with great increasing penetration of power electronic devices into power grids, the large-scale blackouts caused by power electronic devices have been reported, which seriously threatens the safe and stable operation of power systems. Under the above background, in this paper we first introduce several methods of analyzing the traditional power system transient stability from the equal area criterion for the single machine infinite bus system to several Lyapunov function based direct methods for multi-machine systems. Then we introduce some of our recent work on the nonlinear modeling and analysis of a key component of power-electronic-based power systems, voltage source converter (VSC), and propose a multiple machine system model including power electronic equipment and traditional synchronous machines. Finally, we illustrate the transient characteristics of the power electronic devices, and summarize the basic problems and challenges for the transient stability of power-electronic-based power systems. We hope that these basic problems in power-electronic-based power system dynamics including nonlinearity, multi-time-scale, and complexity could arouse the general interest of researchers in the fields of complex systems and statistical mechanics.

PMU and DVR based Power System Monitoring, Controlling and Voltage sag Compensation

The power system network is becoming dense and much more complex. Dynamic and continuous monitoring of the power system network is required to avoid power outages. Phasor Measurement Unit (PMU) is one such device that provides state estimation parameters of dynamic power system networks that are used for designing relays and controlling the system network. Power Quality problems such as voltage sags and swells can damage the sensitive load and cause abnormal voltage, current, and frequency conditions in a power system network. Fast and major developments in power electronics technology have made it possible to mitigate the power quality problems. Dynamic Voltage Restorer (DVR) is a voltage sag compensation device that compensates the difference in voltage avoiding interruptions and restores the voltage to the pre-fault value. This paper discusses a technique used for monitoring, protecting, and controlling the system under fault condition using PMU and compensate voltage sag for a sensitive load using DVR based on the data collected by placing PMU in an optimal location. The outcome of the above analysis is recorded which shows that effective monitoring, controlling, and voltage sag compensation can be done with less number of PMU’s placed optimally in conjunction with DVR.