Power System Security Assessment Research Articles

Model free graphical index for transient stability limit based on on‐line single machine equivalent system identification

In this study, a novel technique for fast transient stability limit assessment is proposed. In the proposed method, first the whole power system is approximated with a single machine equivalent model independent of the type and location of the fault, and its parameters are identified using on-line measured data. Next, a graphical index based on transient energy approach is presented for the transient stability limit. The proposed method is tested on a real 247-machine power network to all devices in service, and the load flow matched with real recorded data. Simulation studies show very promising results. Furthermore, they show that the defined stability index can be evaluated immediately after the fault clearing and can be accurately estimated even if does not exist any prior knowledge about the operating condition. This new method can be used for preventive security assessment in smart power systems. The results show that the proposed graphical stability limit can be used accurately as a measure for ‘distance to critical clearing time’ of relays.

Security-Based Active Demand Response Strategy Considering Uncertainties in Power Systems

In modern power systems, the stochastic and interactive characteristics of mixed generations have gained increasing interest, especially when more renewable energy sources are connected to the grid. The uncertainty of renewable energy has notable effects on power system security. In this paper, a set of composite security indices, which are derived from the Hyper-box and Hyper-ellipse Space theory, are extended by a Latin hypercube sampling method to model multiple probabilistic scenarios under uncertainty. Thus, the proposed approach is suitable for power system security assessment with wind power integrated. According to the indices, a security-based active demand response (DR) strategy is proposed. This strategy is able to provide expected active DR capacity based on the forecast wind power fluctuations. Therefore, it can be applied to day-ahead power system dispatches.

Probabilistic Risk-Based Security Assessment of Power Systems Considering Incumbent Threats and Uncertainties

In-depth security analyses of power systems (PSs) require to consider the vulnerabilities to natural and human-related threats, which may cause multiple dependent contingencies. On the other hand, such events often lead to high impact on the system, so that decision-making aimed to enhance security may become difficult. Introducing the uncertainty, the risk associated to each contingency can be evaluated, thus allowing to perform effective contingency ranking. This paper describes an in-depth security assessment methodology, based on an “extended” definition of risk (including threats, vulnerability, contingency, and impact) aimed to perform the risk assessment of the integrated power and Information and Communication Technology (ICT) systems. The results of the application to test cases and realistic PSs show the added value of the proposed approach with respect to conventional security analyses in dealing with uncertainty of threats, vulnerabilities, and system response.

A least square support vector machine-based approach for contingency classification and ranking in a large power system

AbstractThis paper proposes an effective supervised learning approach for static security assessment of a large power system. Supervised learning approach employs least square support vector machine (LS-SVM) to rank the contingencies and predict the system severity level. The severity of the contingency is measured by two scalar performance indices (PIs): line MVA performance index (PIMVA) and Voltage-reactive power performance index (PIVQ). SVM works in two steps. Step I is the estimation of both standard indices (PIMVA and PIVQ) that is carried out under different operating scenarios and Step II contingency ranking is carried out based on the values of PIs. The effectiveness of the proposed methodology is demonstrated on IEEE 39-bus (New England system). The approach can be beneficial tool which is less time consuming and accurate security assessment and contingency analysis at energy management center.

Machine Learning Techniques for Power System Security Assessment

Abstract: Modern electricity grids continue to be vulnerable to large-scale blackouts. As all states leading to large-scale blackouts are unique, there is no algorithm to identify pre-emergency states. Moreover, numerical conventional methods are computationally expensive, which makes it difficult to use for the on-line security assessment. Machine learning techniques with their pattern recognition, learning capabilities and high speed of identifying the potential security boundaries can offer an alternative approach. The purpose of this paper is not to suggest that one particular kind of machine learning technique for security assessment would be more appropriate than others. We start from the premise that almost every method may be useful within some restricted context. Based on this idea, we developed an automated multi-model approach for on-line security assessment. The proposed method allows us to automatically test the different state-of-art techniques in order to find both the best algorithm and its top performance tuning for particular analyzed power system. A case study using the IEEE RTC-96 system demonstrates the effectiveness of the proposed approach.

A Systematic Approach to -1-1 Analysis for Power System Security Assessment

Cascading outages can have a catastrophic impact on power systems. One such recent incident was the September 8, 2011 blackout that affected San Diego and large parts of the southwestern United States. To prepare for such events, the NERC transmission planning standards require utilities to plan for ${n}$ -1-1 outages. However, such analyses can be computationally burdensome for any realistic power system owing to the staggering number of possible ${n}$ -1-1 contingencies. This paper proposes a systematic approach to analyze ${n}$ -1-1 contingencies in a computationally tractable manner for power system security assessment. The proposed approach addresses both static and dynamic security assessment. The proposed methods have been tested on the Western Electricity Coordinating Council (WECC) system. The test results show that a substantial reduction in computational effort is achieved by implementing these methods for an ${n}$ -1-1 contingency analysis. In addition, the reliability of the proposed methods is evaluated by an exhaustive contingency analysis.

Risk Assessment of Power System Security based on a Hybrid Optimization GP Method

Risk Assessment of Power System Security based on a Hybrid Optimization GP Method

A parallel computing approach for integrated security assessment of power system

Abstract Fast and accurate assessment of integrated security of present day complex and highly interconnected power system within time frame is a challenging task. The traditional methods used for integrated security assessment are fast but approximate. On the other hand, full simulation methods provide more accurate security assessment, but require large computation time. This paper proposes the use of parallel computing for fast and accurate assessment of integrated security of power system by running full Newton Raphson (NR) load flow program with sparsity technique to compute real power flow or MW performance index ( MWPI ), and voltage performance index ( VPI ), and continuation power flow program with sparsity technique to compute voltage stability index ( VSI ) for all possible single line outage contingencies. The proposed work has been carried out using the Matlab Parallel Computing Toolbox Software (PCTS). To implement parallel computing, the job scheduler, a part of PCTS, divides a computationally intensive job into various tasks and distributes these tasks to its assigned workers for evaluation. Effectiveness of the proposed approach has been demonstrated on IEEE 30-bus system and a practical NREB 246-bus Indian power system. As the proposed method utilizes NR load flow and continuation load flow programs, the accurate post contingency operating status of a power system is also available, which can be used for appropriate corrective actions planning to bring the power system back into secure state. The proposed approach is quite accurate and fast and hence can be implemented for integrated security assessment of practical power systems in smart grid environment also.

An importance sampling technique for probabilistic security assessment in power systems with large amounts of wind power

Larger amounts of variable renewable energy sources bring about larger amounts of uncertainty in the form of forecast errors. When taking operational and planning decisions under uncertainty, a trade-off between risk and costs must be made. Today's deterministic operational tools, such as N-1-based methods, cannot directly account for the underlying risk due to uncertainties. Instead, several definitions of operating risks, which are probabilistic indicators, have been proposed in the literature. Estimating these risks require estimating very low probabilities of violations of operating constraints. Crude Monte-Carlo simulations are very computationally demanding for estimating very low probabilities. In this paper, an importance sampling technique from mathematical finance is adapted to estimate very low operating risks in power systems given probabilistic forecasts for the wind power and the load. Case studies in the IEEE 39 and 118 bus systems show a decrease in computational demand of two to three orders of magnitude.

An enhanced cuckoo search algorithm based contingency constrained economic load dispatch for security enhancement

Abstract This paper propose a meta-heuristic algorithm known as the enhanced cuckoo search (ECS) algorithm for contingency constrained economic load dispatch (CCELD) in order to relieve transmission line overloading. The power system security assessment deals with finding out the secure and the insecure operating states, whereas the security enhancement deals with the necessary control action against overloads under contingency scenario. By generation rescheduling the overloaded lines can be relieved from the severity. In the proposed ECS algorithm, in order to improve the solution vectors, dynamically variable parameters namely the step size and the probability are incorporated instead of the fixed values of the parameters. The CCELD problem includes scheduling of generators to minimize the severity index with minimum fuel cost. A standard IEEE-30 bus system is considered to study the effectiveness of the proposed ECS algorithm for CCELD problem. Numerical results reveals that, for 100 iterations the proposed ECS algorithm out performs the other state-of-the-art algorithms, namely cuckoo search (CS), Bat algorithm (BA) and particle swarm optimization (PSO) algorithm in obtaining the minimum fuel cost and the minimum severity index in minimum time. Thus, the proposed ECS algorithm is found to be efficient to obtain the solution of contingency constrained economic load dispatch problem.

Application of Support Vector Machine to Static Security Assessment in Power systems

Application of Support Vector Machine to Static Security Assessment in Power systems

Mega Watt Security Assessment of Power Systems

This paper deals with the security aspects of power system by evaluating the severity of transmission line outage. MW security assessment is made by determining the power flow in the line using load flow for each contingency. The severity of contingency is measured using a scalar index called performance index (PI). DC load flow and Fast Decoupled load flow are used as approximate and exact load flow methods for MW security assessment respectively. Contingency analysis is carried out and ranked lists in the decreasing order of severity based on PI values are prepared for standard test systems. The severity of line is evaluated and compared using these load flow methods. A new method is proposed to avoid Masking problems in MW security assessment. Security analysis is made on standard test systems such as 5, 6, IEEE 14 and IEEE 30 bus systems under present study.

Mega Watt Security Assessment of Power Systems

This paper deals with the security aspects of power system by evaluating the severity of transmission line outage. MW security assessment is made by determining the power flow in the line using load flow for each contingency. The severity of contingency is measured using a scalar index called performance index (PI). DC load flow and Fast Decoupled load flow are used as approximate and exact load flow methods for MW security assessment respectively. Contingency analysis is carried out and ranked lists in the decreasing order of severity based on PI values are prepared for standard test systems. The severity of line is evaluated and compared using these load flow methods. A new method is proposed to avoid Masking problems in MW security assessment. Security analysis is made on standard test systems such as 5, 6, IEEE 14 and IEEE 30 bus systems under present study.

Hybrid algorithm for rotor angle security assessment in power systems

Transient rotor angle stability assessment and oscillatory rotor angle stability assessment subsequent to a contingency are integral components of dynamic security assessment (DSA) in power systems. This study proposes a hybrid algorithm to determine whether the post-fault power system is secure due to both transient rotor angle stability and oscillatory rotor angle stability subsequent to a set of known contingencies. The hybrid algorithm first uses a new security measure developed based on the concept of Lyapunov exponents (LEs) to determine the transient security of the post-fault power system. Later, the transient secure power swing curves are analysed using an improved Prony algorithm which extracts the dominant oscillatory modes and estimates their damping ratios. The damping ratio is a security measure about the oscillatory security of the post-fault power system subsequent to the contingency. The suitability of the proposed hybrid algorithm for DSA in power systems is illustrated using different contingencies of a 16-generator 68-bus test system and a 50-generator 470-bus test system. The accuracy of the stability conclusions and the acceptable computational burden indicate that the proposed hybrid algorithm is suitable for real-time security assessment with respect to both transient rotor angle stability and oscillatory rotor angle stability under multiple contingencies of the power system.

A probabilistic security assessment approach to power systems with integrated wind resources

Renewable energy sources, such as wind and photovoltaic solar, have added additional uncertainty to power systems. These sources, further to the conventional sources of uncertainty due to stochastic nature of both the load and the availability of generation resources and transmission assets, make clear the limitations of the conventional deterministic power flow in power system analysis and security assessment applications. In order to manage uncertainties, probabilistic approaches can provide a valuable contribution.In this paper, we propose a new scheme for probabilistic security assessment. The model can deal with various types of probability distributions modeling power injections and can explicitly represent the effects on system security of correlation among nodal power injections (such as wind power) and of contingencies due to branch and generating unit outages. In addition, the steady-state behavior of the frequency regulation is explicitly included in the model. A new approach to deal with current limits is also proposed.Extensive testing on both the modified IEEE-14 bus test system and the Sicilian power system indicates good performance of the proposed approach in comparison with the result obtained by the computationally more demanding Monte Carlo approach.

On‐line parameter identification of power plant characteristics based on phasor measurement unit recorded data using differential evolution and bat inspired algorithm

Parameter estimation and dynamic modelling of power systems and their components are basis of design, planning and stability or security assessment in power systems. This study considers the estimation of power system model parameters by a global identification framework based on the maximum-likelihood principle. The proposed framework is formulated as a non-linear optimisation problem, which is solved by a hybrid method based on the bat-inspired algorithm and differential evolution method. The combination of these algorithms makes the hybrid method faster and it obtains closer to the global minimum than a pure global method. Since noise and model uncertainties are inherent parts of system identification, the effect of these factors on the performance of the proposed identification framework are studied. Results based on synthetic data in frequency domain show that the estimated parameters are close to the correct values even in the presence of significant measurement noise and considerable uncertainties.

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.

An Approach to Assess the Resiliency of Electric Power Grids

Modern electric power grids face a variety of new challenges and there is an urgent need to improve grid resilience more than ever before. The best approach would be to focus primarily on the grid intelligence rather than implementing redundant preventive measures. This paper presents the foundation for an intelligent operational strategy so as to enable the grid to assess its current dynamic state instantaneously. Traditional forms of real-time power system security assessment consist mainly of methods based on power flow analyses and hence, are static in nature. For dynamic security assessment, it is necessary to carry out time-domain simulations (TDS) that are computationally too involved to be performed in real-time. The paper employs machine learning (ML) techniques for real-time assessment of grid resiliency. ML techniques have the capability to organize large amounts of data gathered from such time-domain simulations and thereby extract useful information in order to better assess the system security instantaneously. Further, this paper develops an approach to show that a few operating points of the system called as landmark points contain enough information to capture the nonlinear dynamics present in the system. The proposed approach shows improvement in comparison to the case without landmark points.

On Study of Harmonic Load Modeling for Equipment Power System

It has been well recognized that the methods for electrical load modeling have significant impacts on the power systems operation, simulation, analysis and security assessment. Compared with the power grid of infinite capacity, the equipment power system with a large number of power electronic devices has larger internal resistance, and the application objects of the model face to the three-phase four-wire independent power supply system. Therefore, this paper deals with the problem of the three-phase four-wire harmonic load modeling in the equipment power system of infinite capacity, including the basic idea and principle of nonlinear load design, the main circuit structure of the chosen four-leg PWM converter, and the overall control strategy. Based on FFT analysis comparison between the real measured data and the simulation data, it is further shown that the load model can reproduce accurately the current waveform distortion, and simulate the harmonic characteristics of the steady state and transient state of equipment power system.

PMU based voltage security assessment of power systems exploiting principal component analysis and decision trees

The need for feature selection and dimension reduction is felt as a fundamental step in security assessment of large power systems in which the number of features representing the state of power grids dramatically increases. These large amounts of attributes are not proper to be used for computational intelligence (CI) techniques as inputs, because it may lead to a time consuming procedure with insufficient results and they are not suitable for on-line purposes and updates.