Search

Transient stability of a power system can be significantly affected by wind power generators due to their stochastic power output and complex dynamic characteristics. This paper proposes a robust optimization approach for coordinating generation dispatch and emergency load shedding against transient instability under uncertain wind power output. The problem is modelled as a two-stage robust optimization (TSRO) model considering transient stability constraints, where the first-stage is to optimize the generation dispatch (preventive control) before a contingency and the second-stage decision is the emergency load shedding (emergency control) after the contingency occurrence under the worst case of wind power variation. To solve this TSRO problem, this paper also proposes a solution algorithm which integrates transient stability assessment and transient stability constraint construction in a column and constraint generation framework. The proposed method is validated on the New-England 39-bus system and the Nordic32 system, which shows high computational efficiency and stability robustness against uncertain wind power. [ABSTRACT FROM AUTHOR]

Globally,wind power plants (WPPs) installations are dramatically increasing, leading to a large-scale integration into the power grids. Huge endeavors are devoted to achieving an efficient operation of WPPs. This paper offers a novel chaotic-billiards optimizer (C-BO) algorithm to properly design the fuzzy logic control (FLC) strategy for stability enhancement of grid-integrated WPPs. The C-BO algorithm has distinct features such as simple construction, low numbers of parameters required to design, high convergence speed, and low computational burden. The permanent-magnet synchronous generator (PMSG)-based WPP is interlinked into the electric power grid through power converters. A cascaded FLC approach, which is optimally fine-tuned by the C-BO, is offered as the control methodology for these converters. The C-BO algorithm fine-tunes the gain factors of multiple FLCs at a rapid convergence speed. A simulation-based optimization approach is applied, in which the integrated square error criterion is chosen as an objective function. For the sake of preciseness, the PMSG-based WPP is connected to the IEEE 39-bus New England test system. The effectiveness of the optimal FLC using the C-BO algorithm is compared with that achieved using the water cycle algorithm-based optimal FLC, the genetic algorithm-based optimal FLC, and the marine predator algorithm-based optimal proportional-integral controller, taking into account severe grid disturbances. Moreover, real wind speed measured data captured from Zaafarana Station in Egypt are extensively performed in the system studies. The validity of the offered control approach is widely verified by the simulation analyses using the MATLAB/Simulink environment. [ABSTRACT FROM AUTHOR]

Distance relays are quite vulnerable to maloperation during dynamic stressed situations. The apparent impedance seen by the relay encroaches the zone-3 resulting in distance relay maloperation that can initiate cascading failures. This paper presents an enhanced scheme for wide area backup protection which implements improved protection algorithms to decide final relaying status. A machine learning tool namely Deep Neural Network is utilized to build those protective relaying decision logics: RDL-1 and RDL-2. Wide area information retrieved from phasor measurement units (PMU) is used to take real time decisions. RDL-1 is designed to detect if the system is operating in normal or stressed condition. During normal state, traditional zone-3 relay undertakes the relaying decision. However, under stressed situations, RDL-1 switches the decision-taking to RDL-2. RDL-1 also predicts whether the system is progressing towards an out-of-step situation so that appropriate remedial action can be undertaken. Proposed scheme was studied on IEEE-39 bus New England system using MATLAB/SIMULINK and validated on Real Time Digital Simulator platform and third zone mal-tripping are avoided. Performance of the proposed algorithm was compared with the conventional blinder and other data-mining techniques which show considerably high classification accuracy. [ABSTRACT FROM AUTHOR]

To analyze the grid integration effect of a virtual synchronous generator (VSG), this paper proposes a simple power system modeling method. It is shown that for a specific disturbance, by simplifying the original network to a radical n generators single-load model, its state-space small-signal model can be obtained using a unified formula, as long as the single generator infinite bus model of each generator is given. Case studies based on the IEEE 9-bus test system as well as the New York New England test system show high efficiency of the proposed modeling to represent slow power and frequency deviations. Modal analyses give insight into how system poles are synthesized by individual generator poles, and how different designs of VSGs affect the system oscillation modes. Potential errors due to the topology simplification and the measures to avoid them are discussed. The time-domain results and modal analyses highlight some important features of VSG, which are overlooked in previous studies. [ABSTRACT FROM AUTHOR]

Due to global climate change, the effect of extreme weather on power systems has attracted extensive attention. In the prior-art grid resilience studies, the hurricanes or wildfires are mainly defended in terms of expected line damages, while they are prone to trigger short-circuit fault (SCF) evolved with dynamic influence in reality. In this paper, a fragile model is developed to evaluate the nodal SCF probability considering the insulation aging of equipment and extreme weather condition. Then, a response framework for extreme weather events is developed for a transmission system to defend the cascading impacts of expected SCFs. Specifically, switches are shifted to restrain the out-of-range short-circuit currents (SCCs) so that to ensure the SCFs can be removed by circuit breakers, generation rescheduling and load shedding are arranged to maintain the post-fault system transient stability. The above measures are optimized simultaneously by an integrated Mixed-Integer Nonlinear Programming (MINLP). Considering the error or uncertainty of weather event forecasts, a multi-state model is established to provide the most cost-effective grid resilience enhancement scheme, in which the expected urgent adaptions of the initial scheme subject to weather state transition is included in the overall cost. The proposed model and techniques are validated using the IEEE 39-bus New-England test system and realistic meteorological data. [ABSTRACT FROM AUTHOR]

This paper proposes a fractional-order sliding mode controller (FOSMC) for fixed-time stability of multimachine power systems. Fractional calculus has been applied in sliding mode control (SMC) to design FOSMC which can better suppress the chattering phenomenon than the traditional integer-order SMC. Hence, a FOSMC is proposed to regulate the excitation of synchronous generators to improve the transient stability of the power system. In addition, the FOSMC can maintain the multimachine power systems stabilization in an upper bound and measurable convergence time independent of the initial operating conditions of the power system. The Lyapunov function is implemented to demonstrate the stability of multimachine power systems under the FOSMC, and the upper bound convergence time of the power system is generally estimated. The New England 10-machine 39-bus power system is taken into simulation to test the effectiveness and superior performances of the FOSMC than the existing control methods under different operating conditions. Meanwhile, the FOSMC with different orders are presented to verify that the FOSMC can better restrain the chattering phenomenon than traditional integer-order SMC. Simulation results show that the FOSMC can effectively reduce the chattering phenomenon and ensure the power system stabilization in an upper bound time, thus enhancing the dynamic performances of the power system. [ABSTRACT FROM AUTHOR]

Frequency dynamics during primary frequency control is closely related to pre-disturbance operating conditions, the disturbance, and equipment characteristics. How to rigorously express such a relation in a frequency stability constrained optimal dispatch problem is still an open question. This paper presents an optimal power flow (OPF) model for generation re-dispatch that considers dynamic frequency response constraints to ensure frequency stability during primary frequency regulation. The distinct feature of the model is that the dynamic frequency response is formulated as a set of differential algebraic equations (DAEs), which allows considering the transient behavior of frequency and mechanical/electromagnetic power for each generator during primary frequency control period. Based on the solution of the optimization problem, a definition of the primary reserve for each unit is proposed according to the maximum of incremental mechanical power. This definition helps meet the adequacy requirement of primary frequency response and achieve partial frequency restoration. Simulation results on WSCC 3-machine 9-bus system, New England 10-machine 39-bus system and the modified IEEE 54-machine 118-bus system validate the effectiveness of the proposed model and reveal the strong coupling between frequency dynamics and the pre-disturbance generation. [ABSTRACT FROM AUTHOR]

Growing integration of wind power and increasing use of induction motor loads dramatically affect a power system's dynamic performance. To address the challenges, this paper proposes a robust dynamic VAR planning method to enhance the voltage stability of wind energy power systems under uncertainty. Firstly, two indices are developed to evaluate the steady-state and the short-term voltage stability of the system. Then, a robustness index is proposed to quantitatively evaluate the robust optimality of the solutions, considering the uncertainties from wind power output and STATCOMs initial state before a contingency. Four objectives are optimized simultaneously: 1) total planning cost, 2) short-term voltage stability index, 3) steady-state voltage stability index, and 4) robustness of the solutions. Finally, an Adaptive Non-dominated Sorting Genetic Algorithm-III based on Latin Hypercube Sampling (A-NSGA-III-LHS)is designed to solve this many-objective optimization problem with 3 improvements over the standard NSGA-III: 1) adaptive mutation rate, 2) Differential Evolution operator, 3) Latin Hypercube Sampling based initial population generation. The proposed method is tested on the New England 39-bus system with an industry-standard complex load model, showing high robust optimality and computational efficiency over conventional methods. [ABSTRACT FROM AUTHOR]

Energy storage systems (ESSs) have been applied in power systems for a long time. It participates in the grid frequency control at two levels, the primary frequency control and the secondary frequency control. In this paper, a control strategy that integrates one synchronous generator (SG) and ESS as one single generation unit named flexible generator (FG) is proposed, allowing ESS to participate in primary frequency control. The main trick is that the proposed control strategy not only adopts SG's frequency as the ESS control input but also feeds back FG's total output power to control the ESS. FGs have more substantial damping and stability than SGs. The proposed control strategy has a superior performance compared to traditional PID control and fuzzy control strategies of ESSs. The flexible control parameters are determined by the linear quadratic regulator (LQR) with disturbance suppression. The ESS's capacity is discussed and determined. Simulation results of the New England 39-bus system verify the advantages of FGs both in load changes and faults. The HIL experiment results also illustrate the applicability and effectiveness of the flexible control. [ABSTRACT FROM AUTHOR]

This paper proposes a new coordinated method for preventive generation rescheduling and corrective load shedding to maintain power system transient stability under uncertain wind power variation. A two-step bi-level optimization model is proposed where generation rescheduling and load shedding are coordinated by a risk coordination parameter, which adjusts the total coordination cost in the upper level. Then, based on Extended Equal Area Criterion (EEAC) and trajectory sensitivities, the non-linear risk and stability constraints are converted into the linear form for generation rescheduling cost and load shedding cost optimization in the lower level, respectively. Uncertain wind power output is modeled as a small number of robust test scenarios. Finally, the golden section search is applied to solve the bi-level problem. The proposed method is validated on the New-England 39-bus system by using commercial grade software. The computational efficiency, economic optimality, and stability robustness under random wind power of the method are demonstrated. [ABSTRACT FROM AUTHOR]

Based on the knowledge accumulated off-line and feature extractions, a novel data-based learning and control method is proposed for the long-term voltage stability problem in this paper. All the spatial-temporal data is considered and the features of different emergency events are extracted by principle component analysis which can reduce the dimension and reveal the significant internal structure of the data. An artificial neural network is used to build a classifier to reinforce the relationship directly between the system dynamics and optimal control actions. With the prepared control knowledge, it is faster to find an optimal control action online with a good system performance. Simulation results on the 6-bus system, New England 39-bus system and Iceland 189-bus system are given to show the potential of this method for on-line control. [ABSTRACT FROM AUTHOR]

System inertia plays a vital role in controlling the angular stability of the system during a disturbance. Due to increased penetration of power electronic interfaced sources, such as Solar Photovoltaic (SPV) source, the overall system inertia reduces and varies depending on their operating conditions. In this paper, an approach for online inertia estimation in the power system network with SPV sources is proposed, using the synchronized measurements from Phasor Measurement Units (PMUs). An equivalent swing equation is used to emulate the network dynamics. A relationship between the inertia constant and the roots of this equation is determined. In order to numerically obtain the roots, the Estimation of Signal Parameter via Rotational Invariance Techniques (ESPRIT) method is first used to find the modes present in the frequency signal. A new formulation is proposed to extract an equivalent mode from all the obtained modes. Also, to avoid phase step error, Rate Of Change Of Frequency (ROCOF) is estimated from the equivalent mode of the frequency signal. Results obtained for the 39 bus New England system for various test cases, using Real-Time Digital Simulator (RTDS), prove the efficacy and superiority of the proposed approach over the existing approaches in the literature. [ABSTRACT FROM AUTHOR]

This paper presents a power swing detection algorithm in multi-machine power systems, which uses wide-area synchrophasor measurements and is based on Zubov’s stability boundaries. Zubov’s boundary method, an approximation of the famous Lyapunov function, is very common for numerical analyses of power system stability. This work extends the concept of Zubov’s approximation boundaries to online protection applications. First, the proposed protection algorithm constructs a series of Zubov’s stability boundaries on power angle–frequency ($\delta$ – $\omega$) plane for generators based on real-time measurements from phasor measurement units/merging units. Then, it tracks the trajectory of each generator in the $\delta$ – $\omega$ plane after the disturbance to differentiate out-of-step (OOS) conditions from stable swings. The proposed approach is suitable for online applications, which is a significant improvement over the existing methods for swing detection since it does not require offline studies and network reduction. Effectiveness of the proposed method is shown using a single-machine infinite bus and New-England 10-machine 39-bus systems. The proposed method is also implemented in a hardware-in-the-loop setup with a customized IEC 61850-based OOS relay, and performance is compared with a commercially available relay. [ABSTRACT FROM AUTHOR]

Poorly damped inter-area modes of oscillations represent a major concern to power system operation since they detain the power transfer capability of transmission networks. This situation becomes more stringent as the tie-lines are heavily stressed and/or large amounts of renewable energy resources are installed. To overcome this issue, a detailed mathematical model is proposed in this paper to reduce the linearized model of a large power system using the cross-Gramian technique. The presented approach divides the system into a study area which contains one generation unit with installed power system stabilizer (PSS) and an external one which comprises the rest of generation units in the system. Model order reduction is only applied to the external area with the objective of maintaining the characteristics of the original model. Meanwhile, the dynamics of the study area are preserved to provide the required damping through the designed PSS. In addition, an online tuning methodology is also presented to provide robust damping performance in response to changes in the system operating conditions. The deployed cross-Gramian model order reduction alleviates the computational burden and time associated with the online PSS tuning when original power system models are used. The effectiveness of the proposed approach is tested using the New-England 39-bus system in addition to another practical system which resembles the Northern Regional Power Grid India test system. [ABSTRACT FROM AUTHOR]

Using their fast power reduction capabilities, the induction motor variable speed drives can successfully participate in the power system primary frequency control. A new control strategy for fast frequency support from the diode front-end induction motor variable speed drive is presented in this paper. By this, practical restrictions are considered. In this context, an existing conventional scheme presented in literature is firstly modified by deploying an estimated motor's power losses for a more exactly control design. Next, a novel control scheme is proposed. It attains the fastest frequency support from the drive and simultaneously restricts its minimum power consumption to a given positive value to prevent regeneration mode during the frequency support process. The frequency of applied voltage to the motor is adjusted through a proportional-integrator compensator with deviation of the drive's consumption power from its reference power as input. The reference power is synthesized by permanent and temporary components, which are determined based on deviation and time derivative of the power system's frequency, respectively. The effectiveness of the proposed smart drive for the primary frequency control is investigated using the New England 39 bus and a more realistic Great Britain 36 zone test networks. It improves system frequency response in terms of the rate of change of frequency and the frequency nadir. Furthermore, the new control scheme can contribute to quickly damping inter-area oscillations in multi-machine power systems. [ABSTRACT FROM AUTHOR]

Series compensation is used to improve power system transmission capacity. Subsynchronous resonance (SSR) associated with such a system is a challenging issue. Today, with increasing integration of wind farm (WF) to power network, the stability of the system gets deteriorated due to variation in wind speed at the WFs. The reaction between the SSR modes and the doubly fed induction generator converters is known as subsynchronous control interaction (SSCI), due to which, it becomes more challenging to achieve power system stability. To overcome these issues, in this paper, a synchrophasor data-based control (SDC) technique is proposed. The proposed controller diminishes induction generator effect, torsional interaction, and the SSCI effect on the series compensated network, integrating multiple WFs. The SDC provides an auxiliary SSR damping control (SSRDC) with thyristor controlled series compensation (TCSC). This SSRDC uses synchrophasor data from WF connected point of common couplings (PCCs) inside the grid to improve the SSR oscillation damping. The proposed method maintains reference voltage angle of the PCCs by controlling equivalent impedance of the grid. The impedance provides significant damping for SSR along with the TCSC control. The proposed SDC is tested for modified 39-bus New England system with WFs and is found to be effective. Comparison of this method with conventional local control demonstrates its superior performance. [ABSTRACT FROM AUTHOR]

The increasing power/load demand is becoming a new concern for the grid operators as it can potentially overload transmission lines. Among advantages of a multi-terminal dc (MTDC) grid, its high controlability makes it a promising asset for ac line overload alleviation. This paper proposes a model predictive control based strategy, which regularly updates the power setpoints of the MTDC converter stations and ac generators to alleviate ac line overloads. To compute and update the power setpoints, necessary measurements are received by the controller within regular time intervals. The proposed controller ensures that subsequent to any ac line overload, changing the power setpoints of the MTDC converter station does not cause any operation violation in the MTDC grid. Furthermore, it ensures that the ac voltage limits and voltage stability criteria are met to avoid voltage instability. Performance and effectiveness of the proposed controller are evaluated by simulation studies on two systems, i.e., the 39-bus New England system integrated with a 5-bus MTDC system and the IEEE 118-bus system connected to a 6-bus MTDC system. Simulation results confirm that the MTDC grid can play a major role in controlling active powers of most of the ac transmission lines. [ABSTRACT FROM AUTHOR]

With increase of practical power system complexity, power system online stability assessment and control is more and more important. Application of the traditional model-driven methods is always limited by contradiction between accuracy and efficiency, while data-driven methods demonstrate strong abilities for the online decision-making support with advancement of various data mining techniques. Instead of direct application of data-driven methods in the power system, this paper first discusses feasible integration approaches for the model-driven and data-driven methods based on the existing achievements, and then, proposes to integrate both methods for the power system online frequency stability assessment and control. The integrated method consists of frequency dynamics prediction and load shedding procedure. In frequency dynamics prediction procedure, integration of system frequency response (SFR) model and the extreme learning machine (ELM)-based learning model is applied, where basic physical causality is kept in the SFR model and ELM is used to fit and correct error of the SFR. The ELM also plays a part in load shedding prediction model construction by digging out mapping relationship from samples. Finally, the proposed prediction and control scheme for the frequency stability is verified by simulations on WSCC 9-bus, New England 39-bus, and NPCC 140-bus system. Results show that the reliability, time efficiency, and accuracy are enhanced with the proposed method. [ABSTRACT FROM AUTHOR]