Uncertain Power System Research Articles

Performance and Accuracy Investigation of the Two-Step Algorithm for Power System State and Line Temperature Estimation

Data concerning actual temperatures of line conductors constitutes essential information for the power system operator. The temperature of the power lines can be used to improve the accuracy of the power system model, thereby increasing the accuracy of the state estimation. This article presents a two-step algorithm for the power system state and line temperature estimation. In its second stage, the proposed method searches for a line temperatures vector, which corrects the uncertain power system base model and allows for further minimization of an objective function. As a result, a more accurate estimation is obtained along with a more precise model of the estimated system. The derived model can then be used for more accurate optimization. The presented method enhances standard procedures of power system state estimation, and its advantage is that it does not require direct measurements performed by phasor measurement units or measurements of line conductor temperatures and weather conditions realized by dynamic line rating systems. The results of simulations made on various test models have been examined, confirming the convergence of the procedure to the point at which the average temperature of the line wires together with the voltage values and phase angles are achieved. The algorithm’s performance and improvement method have also been presented. An advantage of the investigated approach is the possibility to calculate the temperature of line wires with the use of primary measurements in the power system. The presented and examined method, however, is sensitive to the measuring device errors. Additionally, an analysis of the method’s errors and ways of reducing them has been performed.

Design of Multi-Machine Power System Stabilizers with Forecast Uncertainties in Load/Generation

ABSTRACTOscillatory instability in modern power system has increased due to increasing complexity and integration of dynamic loads. Stability analysis of such interconnected power system is very prominent in the presence of uncertain load/generation. In this paper, a power system stabilizer (PSS) design approach, which aims at enhancing the oscillatory stability of the multi-machine power system over the specified uncertainty range in forecasted load/generation, is presented. With non-statistical uncertainty, problem of selecting design parameters of the PSS is formulated as an optimization problem with minimization of eigenvalues and damping ratios based multi-objective function. In order to account the non-statistical uncertainties, a boundary active power loss (BAPL) based objective function is proposed. This non-linear BAPL objective function is minimized for determining the optimal setting of the generators voltage and taps of the online tap changing transformers (OLTC) under various power system constraints. In this paper, both the objective functions are solved by a new metaheuristic technique known as gray wolf optimization (GWO). Boundary value-based approach is used to minimize the repeated load flows under uncertain load/generation scenarios. Improved small-signal stability (SSS) is achieved with optimal active power loss of uncertain power system. Eigenvalue and time domain analysis for New England system are carried out under wide range of disturbances to demonstrate the potential of the proposed approach.

Probabilistic Framework for Transient Stability Assessment of Power Systems With High Penetration of Renewable Generation

This paper introduces a probabilistic framework for transient stability assessment (TSA) of power systems with high penetration of renewable generation. The critical generators and areas of the system are identified using a method based on hierarchical clustering. Furthermore, statistical analysis of several transient stability indices is performed to assess their suitability for TSA of reduced inertia systems. The proposed framework facilitates robust assessment of transient stability of uncertain power systems with reduced inertia.

Risk-Based Probabilistic Voltage Stability Assessment in Uncertain Power System

The risk-based assessment is a new approach to the voltage stability assessment in power systems. Under several uncertainties, the security risk of static voltage stability with the consideration of wind power can be evaluated. In this paper, we first build a probabilistic forecast model for wind power generation based on real historical data. Furthermore, we propose a new probability voltage stability approach based on Conditional Value-at-Risk (CVaR) and Quasi-Monte Carlo (QMC) simulation. The QMC simulation is used to speed up Monte Carlo (MC) simulation by improving the sampling technique. Our CVaR-based model reveals critical characteristics of static voltage stability. The distribution of the local voltage stability margin, which considers the security risk at a forecast operating time interval, is estimated to evaluate the probability voltage stability. Tested on the modified IEEE New England 39-bus system and the IEEE 118-bus system, results from the proposal are compared against the result of the conventional proposal. The effectiveness and advantages of the proposed method are demonstrated by the test results.

Real-time implementation of affine nonlinear optimal control for SMIB system

This paper presents the simulation and the experimental validation of the designed robust power system controller to stabilise a linearised uncertain power system using affine nonlinear optimal control (ANOC) loop shaping design procedure. Guidance for setting the feedback configuration for loop shaping, weighing functions selection and synthesis are also presented. The stability and effectiveness of the designed controller is simulated using MATLAB/Simulink and tested by implementing on real-time environment using iNetCon-PC104 work stations and the control circuit designed. Meanwhile, the hardware in the loop (HITL) simulation results of single-machine infinite-bus (SMIB) transient stability are compared with the off-line digital simulation results based on MATLAB/Simulink, thus validating the simulation results with the experimental results. Also, justification of robustness is presented by considering with or without controller based on affine nonlinear algorithm when large disturbances (faults) happen, which shows the effectiveness of the ANOC presented in the power system.

Real-time implementation of affine nonlinear optimal control for SMIB system

This paper presents the simulation and the experimental validation of the designed robust power system controller to stabilise a linearised uncertain power system using affine nonlinear optimal control (ANOC) loop shaping design procedure. Guidance for setting the feedback configuration for loop shaping, weighing functions selection and synthesis are also presented. The stability and effectiveness of the designed controller is simulated using MATLAB/Simulink and tested by implementing on real-time environment using iNetCon-PC104 work stations and the control circuit designed. Meanwhile, the hardware in the loop (HITL) simulation results of single-machine infinite-bus (SMIB) transient stability are compared with the off-line digital simulation results based on MATLAB/Simulink, thus validating the simulation results with the experimental results. Also, justification of robustness is presented by considering with or without controller based on affine nonlinear algorithm when large disturbances (faults) happen, which shows the effectiveness of the ANOC presented in the power system.

Nonlinear power system excitation control using adaptive wavelet networks

A wavelet network-based nonlinear excitation control is designed to enhance the transient stability of a power system. The power system model used to improve the transient stability via excitation control can be written in the canonical form. The resulting excitation control signal that achieves a prescribed tracking performance is shown to include unknown nonlinear terms. A wavelet network is constructed to generate an approximation of these nonlinear terms and hence facilitate the design of the nonlinear excitation controller. Based on the wavelet network approximation, suitable adaptive control and appropriate parameter update algorithm are developed to force the nonlinear uncertain power system to track a prescribed trajectory with desired dynamic performance. It is shown that the proposed controller achieves ultimately bounded tracking error and boundedness of the closed loop signals. A single machine infinite bus system with uncertain fault location is presented to illustrate the proposed design procedure and exhibit its performance. The performance of the proposed excitation controller is compared with the classical IEEE-type ST1A static exciter equipped with a power system stabilizer.

Robust distributed MPC for load frequency control of uncertain power systems

Reliable Load frequency control (LFC) is crucial to the operation and design of modern electric power systems. However, the power systems are always subject to uncertainties and external disturbances. Considering the LFC problem of a multi-area interconnected power system, this paper presents a robust distributed model predictive control (RDMPC) based on linear matrix inequalities. The proposed algorithm solves a series of local convex optimization problems to minimize an attractive range for a robust performance objective by using a time-varying state-feedback controller for each control area. The scheme incorporates the two critical nonlinear constraints, e.g., the generation rate constraint (GRC) and the valve limit, into convex optimization problems. Furthermore, the algorithm explores the use of an expanded group of adjustable parameters in LMI to transform an upper bound into an attractive range for reducing conservativeness. Good performance and robustness are obtained in the presence of power system dynamic uncertainties.

Intelligent robust PI adaptive control strategy for speed control of EV(s)

The intensive non-linear system and plants of modern industry highly motivating researcher to extend and evolve non-linear control systems. In this study, in order to control a class of non-linear uncertain power systems in the presence of large and fast disturbances, a new simple indirect adaptive proportional-integral is proposed. For handling dynamic uncertainties, the proposed controller utilises the advantages of least squares support vectors regression (LS-SVR) to approximate unknown non-linear actions and noisy data. The LS-SVR is used to approximate the non-linear uncertainties which must be bounded, whereas no requirement needs for bounds to be known. The globally asymptotic stability of the closed-loop system is mathematically proved by using Lyapunov synthesis. To show the merits of the proposed approach, a non-linear electric vehicle (EV) system is considered as a case study. The goal is to force the speed of EV to track a desired reference in the present of structured and unstructured uncertainties. The experimental data, new European driving cycle, is used in order to examine the performance of proposed controller. The simulation studies on a second-order EV with the presence of fast against slow and large against small disturbances demonstrate the effectiveness of the proposed control scheme.

Efficient Estimation of the Probability of Small-Disturbance Instability of Large Uncertain Power Systems

This paper proposes a methodology to efficiently estimate the probability of small-disturbance rotor angle instability of uncertain power systems. Traditional Monte Carlo (MC) approaches are computationally intensive and inefficient, particularly when used to study low probability conditions which result in small disturbance instabilities and develop into serious outage events high impact. The proposed methodology uses importance sampling to focus on conditions which contain the high information content required to make relevant decisions about low probability events. Latin hypercube sampling (LHS) is used to efficiently bound the search space and identify operating conditions leading to a marginally stable or unstable system response. The proposed approach is demonstrated on a model of a multi-area transmission network with a significant capacity of intermittent generation connected through a multi-terminal voltage source converter-based high voltage direct current (VSC-HVDC) grid. It is demonstrated that the methodology yields accurate results with just a small fraction of the sample points required using a conventional numerical MC approach.

An LMI approach to the design of robust delay-dependent overlapping load frequency control of uncertain power systems

This paper considers the design of a fixed structure robust H∞ Load Frequency Controller (LFC) for an uncertain state-delayed power system. The time-delay, which is due to information transfer over communication links, is assumed to be unknown but upper bounded by a known constant. The uncertainties are parametric and assumed to be norm bounded. The design approach is based on the principle of overlapping decomposition where the tie-line power is modelled as the overlapping variable between the interconnected areas comprising the power system. The design is formulated as a Linear Matrix Inequality (LMI) problem, the solution of which returns a fixed structure delay-dependent robust LFC. The validity of the proposed design approach is demonstrated through simulation studies carried out on an uncertain, state-delayed 2-area interconnected power system. The simulation results clearly illustrate better performance of the proposed robust H∞ LFC, compared with existing designs.

Saturated robust power system stabilizers

Abstract In this paper, a new saturated control design for uncertain power systems is proposed. The developed saturated control scheme is based on linear matrix inequality (LMI) optimization to achieve prescribed dynamic performance measures, e.g., settling time and damping ratio. In this design, the closed-loop poles are forced to lie within a desired region. The proposed design provides robustness against system uncertainties. The simulation results of both a single machine infinite bus and a multi-machine power systems are given to validate the effectiveness of the proposed controller.

Guaranteed cost load frequency control for a class of uncertain power systems with large delay periods

This paper investigates the problem of guaranteed cost load frequency control (LFC) for a class of uncertain power systems with large delay periods (LDPs). The model of LFC for power systems with LDPs has been firstly modeled as a switched delay system, which includes a potentially unstable subsystem caused by LDPs and a stable subsystem caused by small delay periods (SDPs). Based on the switching technique and under the constraint conditions of the length ratio and the frequency of LPD, the guaranteed cost load frequency controller can be obtained such that the closed-loop system is exponentially stable and a weighted guaranteed cost upper bound is achieved. Finally, an example is provided to demonstrate the applicability of the proposed method.

Risk-Based Small-Disturbance Security Assessment of Power Systems

This paper presents a risk-based probabilistic small-disturbance security analysis (PSSA) methodology for use with power systems with uncertainties. This novel addition to existing dynamic security assessment (DSA) techniques can be used to quantify the small-disturbance stability risks associated with forecasted operating conditions. This approach first establishes the probability density functions (PDFs) for the damping of the critical oscillatory electromechanical modes by modeling the stochastic variation of system uncertainties, such as loading levels, intermittent generation sources, and power flows through voltage-source converter-high-voltage direct current (VSC-HVDC) lines. The produced PDFs are then combined with severity measures (either simple risk matrices or continuous functions) in order to quantify the risk of stability issues for the system associated with the forecasted operating scenario. In addition, the PSSA is used to establish risk-based operational limits and the concept of a probabilistic security margin is introduced to more accurately represent the probabilistic operation of uncertain power systems. The proposed techniques are demonstrated using a multiarea meshed power system incorporating two VSC-HVDC systems, one of which is connected to a large wind farm.

Probabilistic Small-Disturbance Stability Assessment of Uncertain Power Systems Using Efficient Estimation Methods

This paper presents comparative analysis of the performance of three efficient estimation methods when applied to the probabilistic assessment of small-disturbance stability of uncertain power systems. The presence of uncertainty in system operating conditions and parameters results in variations in the damping of critical modes and makes probabilistic assessment of system stability necessary. The conventional Monte Carlo (MC) approach, typically applied in such cases, becomes very computationally demanding for very large power systems with numerous uncertain parameters. Three different efficient estimation techniques are therefore compared in this paper-point estimation methods, an analytical cumulant-based approach, and the probabilistic collocation method-to assess their feasibility for use with probabilistic small disturbance stability analysis of large uncertain power systems. All techniques are compared with each other and with a traditional numerical MC approach, and their performance illustrated on a multi-area meshed power system.

Real time implementation of H∞ loop shaping robust PSS for multimachine power system using dSPACE

This paper presents the simulation and the experimental validation of the designed robust power system stabilizer (RPSS) to stabilize a linearized uncertain power system using Glover–McFarlane’s H ∞ loop shaping design procedure. Guidance for setting the feedback configuration for loop shaping, weighing functions selection and synthesis are also presented. The efficiency of the designed controller is simulated using Matlab/Simulink and tested by implementing on real time environment using dSPACE work stations DS1005 and DS1104. The real time experimental results of RPSS are compared with that of the conventional power system stabilizer (CPSS) for a three phase fault. Also, the real time simulation results of RPSS are compared with the off-line simulation results of RPSS, thus validating the simulation results with the experimental results. Justification of robustness is also presented by considering three different operating points. The proposed method presented in this paper shows the effectiveness of the RPSS in damping the power system oscillations.

Robust SVC controller design and analysis for uncertain power systems

A Static Var Compensator (SVC) installed in a power transmission network can be effectively used to enhance the damping of electromechanical oscillations [Schweickardt, H. E., Romegialli, G., & Reichert, K. (1978). Closed loop control of static VAR sources (SVS) on EHV transmission lines. IEEE Pes winter power meeting, (paper no A78, pp. 135–136), New York, Jan. 29–Feb. 3]. An adequately designed robust controller, which takes into account variations in the operating conditions, can help to achieve the desired damping control. The proposed approach described in this paper is aimed to achieve damping of electromechanical oscillations by considering a systematic approach, based on interval systems theory and Kharitonov's Theorem. The method presented allows for the design of a fixed-parameter, low-order controller, given a supposed stability degree of the system. The synthesis of a robust SVC controller is divided into two tasks. The first is the determination of the region of stability in the controller parameter plane by plotting the stability boundary locus. The second task is the optimization of the selected controller parameters from the obtained solutions to the first task. Examples of eigenvalue analysis and time simulation demonstrate the effectiveness and robustness of the designed controller.

Stabilizing decentralized robust controllers of interconnected uncertain power systems based on the Hessenberg form: Simulated results

This paper addresses stability analysis and design issues in load-frequency control (LFC) for interconnected power systems with a structure uncertainty satisfying the matching conditions. A simple robust decentralized control law for each subsystem has been developed on the basis of the Hessenberg model and utilizing the basic concepts of both linear-quadratic regulator theory and Lyapunov stability theory. A detailed design procedure together with simulation results have been presented for the case of the LFC problem of interconnected power systems. The performance robustness and stability bounds are studied and subsequently condition numbers corresponding to the stabilizing solution of the algebraic Riccati equation are also presented.

A New Robust Controller Design for Load-Frequency Control via Incomplete State Feedback

A new robust load-frequency controller using incomplete state feedback is proposed. It is suited for an uncertain power system using reheat type turbines. Such a plant contains system parameter uncertainties and an immeasurable state. The new controller design, based on the Riccati equation approach, considers the bounds of system parameters and feedback gains. Appropriate feedback gains can be chosen from their predefined bounds. This includes the selection of zero-gains for immeasurable states. The new robust controller thus uses incomplete state feedback. No observer is needed. Good performance is reported for an example system.