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If an extreme contingency strikes the Kinmen Island power system in Taiwan, it is very likely to cause blackouts. Although an underfrequency protection scheme has been applied, some drawbacks of the protection scheme hinder the Kinmen power system from avoiding blackouts. In the past decade, several blackouts have occurred in the Kinmen power system. To avoid further possible blackouts, a special protection system (SPS) is summoned. This paper describes the design guidelines and deployment procedures of an SPS for the Kinmen power system. The design depends on the Kinmen power system characteristics, and the deployment hinges upon the supervisory control and data acquisition system. Exquisite software was also developed to testify the Kinmen system SPS. Operational records have demonstrated that the proposed SPS can indeed prevent blackouts from occurring in the Kinmen power system. The design, implementation, and operation of the SPS dealt with in this paper might foster further deployments of other SPSs. [ABSTRACT FROM AUTHOR]

With smart fault indicators (SFIs) being widely deployed in distribution networks, availability of SFIs statuses and their current measurement provides an opportunity to locate distribution system faulted line sections in real time. However, the integrity of SFIs data together with complex fault scenarios poses a challenge for fault diagnosis, especially with the presence of distributed generators (DGs). To solve this issue, this paper proposes a new method based on mixed integer linear programming (MILP) for identification of the faulted line sections using incomplete and incorrect SFIs statuses. By minimizing the discrepancy between the expected SFI statuses and the available evidence at the distribution operating center, the proposed approach is able to handle complex fault scenarios with multiple faults and failures or malfunctions of SFIs. When DGs are present, the current measurement of SFIs and their statuses are jointly used. The result is a robust algorithm for detection of faulted line sections of distribution systems with DGs in real time. In addition, a new technique is proposed to convert nonlinear logical constraints into a linear combination of decision variables. The resulting linearity of the developed optimization model ensures its optimality. Simulation results based on a utility feeder demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Planned and unplanned outages on distribution networks may cause major economic loss to customers and can result in substantial reparation payments by utilities. This paper analyzes the use of a battery energy storage system (BESS) to partially or completely avoid these outages. The analysis is conducted with a multiday high-demand scenario where the load demand at peak times exceeds the current capacity of the line. This would result in an outage unless the current from the substation can be reduced. Three basic scenarios representative of different degrees of sophistication of feeder automation were studied, i.e., a conventional feeder controlled by one or more reclosing breakers; a modern distribution feeder equipped with a limited number of remote-controlled breakers that will disconnect nonvital loads belonging to residential, commercial, and industrial customers; and a modern distribution feeder equipped with numerous remote-controlled breakers that will selectively disconnect commercial, industrial, and residential loads based on their degree of criticality. This paper concluded that the total or partial avoidance of outages by way of BESS usage is feasible; however, the use of “smart grid” control technology can provide more benefit than BESSs in the scenarios studied. [ABSTRACT FROM AUTHOR]

Risk of blackouts is more than expected and must be considered in the power system studies. The interest of this paper is to minimize the blackouts risk during minimizing the costs in probabilistic transmission expansion planning (TEP). In this paper, a long-term reliability analysis, which was developed by self-organized criticality theory, is used in a multi-objective optimization to include risk of blackouts in TEP. The objective functions are costs and expected energy not supplied. Also, a new formulation for calculating transmission operating cost as a part of cost function is proposed. The problem is solved by a multi-objective particle swarm optimization to find an optimal Pareto set from which the decision-maker can choose the most desirable one, regarding existing budget. The proposed method is applied to the IEEE 118-bus test system to investigate its applicability and scalability. The results are compared with security-constrained TEP, which uses famous deterministic criterion known as N-1. The proposed approach produces more efficient plans for suppressing cascading blackouts with less network investment. Moreover, the results provide motivation for considering the risk of cascading blackouts in TEP, which afford substantial saving to society. [ABSTRACT FROM AUTHOR]

Environmental factors, such as weather, trees, and animals, are major causes of power outages in electric utility distribution systems. Of these factors, wind and lightning have the most significant impacts. The objective of this paper is to investigate models to estimate wind and lighting related outages. Such estimation models hold the potential for lowering operational costs and reducing customer downtime. This paper proposes an ensemble learning approach based on a boosting algorithm, AdaBoost^+, for estimation of weather-caused power outages. Effectiveness of the model is evaluated using actual data, which comprised of weather data and recorded outages for four cities of different sizes in Kansas. The proposed ensemble model is compared with previously presented regression, neural network, and mixture of experts models. The results clearly show that AdaBoost^+ estimates outages with greater accuracy than the other models for all four data sets. [ABSTRACT FROM PUBLISHER]

This paper proposes an improved analytical model for the study of steady-state performance of droop-controlled VSC-MTDC systems. When power disturbances occur, such as those imposed by normal changes in power settings and converter outages, the powers of the converters with droop control may hit their limits and hence such converters no longer contribute to power sharing, which should be paid special attention when analyzing the impacts of power disturbances on the performance of multi-terminal HVDC (MTDC) systems. Based on the bisection algorithm and superposition principle, the proposed analytical model provides an easy way to estimate the results of power distributions, dc voltage deviations, and power loss variations of the MTDC system taking converter outage and converter overload into account. Simulations of a modified New England 39-bus system incorporating a four-terminal MTDC system are carried out for validating the proposed analytical model. [ABSTRACT FROM AUTHOR]

This paper extends previous research on using a Bayesian network model to investigate impacts of time (month) and weather (number of fair weather days in a week) on animal-related outages in distribution systems. Outage history (outages in the previous week) is included as an additional input to the model, and inputs and outputs are classified systematically to reduce errors in estimates of outputs. Conditional probability table obtained from the historical data are used to estimate weekly animal-related outages which is followed by a Monte Carlo simulation to find estimates of mean and confidence limits for monthly animal-related outages. Comparison of results obtained for four cities of different sizes in Kansas with those obtained using a hybrid wavelet/neural network model shows consistency between the two models. The methodology presented in this paper is simple to implement and useful for the utilities for year-end analysis of the outage data to identify specific reliability-related concerns. [ABSTRACT FROM PUBLISHER]

Power distribution systems play an important role in modern society. When distribution system outages occur, fast and proper restorations are crucial to improve the quality of services and customer satisfaction. Proper usages of outage root cause identification tools are often essential for effective outage restorations. This paper reports on the investigation and results of two popular classification methods: logistic regression (LR) and artificial neural network (ANN) applied on power distribution fault cause identification. LR is seldom used in power distribution fault diagnosis, while ANN has been extensively used in power system reliability researches. This paper discusses the practical application problems, including data insufficiency, imbalanced data constitution, and threshold setting that are often faced in power distribution fault cause identification problems. Two major distribution fault types, tree and animal contact, are used to illustrate the characteristics and effectiveness of the investigated techniques. [ABSTRACT FROM AUTHOR]

The paper provides a review of the electrocution and collision hazards of overhead distribution lines of large birds, particularly raptors, which can be reduced through modifications to existing design standards. The modifications to overhead distribution lines discussed in the paper include pole-line reconfiguration, the use of cover-up materials, perch deterrents, and line markers. The paper also discusses the effectiveness of these measures and research that is under way to develop tools to better understand where the problems are occurring and to determine if existing mitigating measures are working. [ABSTRACT FROM AUTHOR]

Cascading outages in power systems can lead to major power disruptions and blackouts and involve a large number of different mechanisms. The typical development of a cascading outage can be split in two phases with different dominant cascading mechanisms. As a power system is usually operated in N-1 security, an initiating contingency cannot entail a fast collapse of the grid. However, it can trigger a thermal transient, increasing significantly the likelihood of additional contingencies, in a “slow cascade.” The loss of additional elements can then trigger an electrical instability. This is the origin of the subsequent “fast cascade,” where a rapid succession of events can lead to a major power disruption. Several models of probabilistic simulations exist, but they tend to focus either on the slow cascade or on the fast cascade, according to mechanisms considered, and rarely on both. We propose in this paper a decomposition of the analysis in two levels, able to combine probabilistic simulations for the slow and the fast cascades. These two levels correspond to these two typical phases of a cascading outage. Models are developed for each of these phases. A simplification of the overall methodology is applied to two test systems to illustrate the concept. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to enable frequent computational cycles in online dynamic security assessment by using the terms of the transient energy function (TEF) as input features to a machine learning algorithm. The aim is to train a single classifier that is capable of classifying stable and unstable operating points independent of the contingency. The network is trained based on the current system topology and the loading conditions. The potential of the proposed approach is demonstrated with the New England 39-bus test power system model using the support vector machine as the machine learning technique. It is shown that the classifier can be trained using a small set of data when the terms of the TEF are used as input features. The prediction accuracy of the proposed scheme was tested under the balanced and unbalanced faults with the presence of voltage sensitive and dynamic loads for different operating points. [ABSTRACT FROM PUBLISHER]

This paper deals with wind power offering strategies in day-ahead markets. A new plan is proposed in which a wind power producer participates in the day-ahead market while employing demand response (DR) to smooth its power variations. In this context, a new DR scheme is presented through which the wind power producer is able to achieve DR by establishing various DR agreements with DR aggregators. The proposed offering plan involves two stages: the first stage clears on the day-ahead market. The wind power producer decides on day-ahead offers as well as DR agreements with the aggregator. The second stage takes place on the balancing market. In a successive approach, the wind power producer determines its energy trading for each period until the whole day is covered. Additionally, proper DR agreements for each period are confirmed here. The proposed plan is formulated in a stochastic programming approach, where its validity is assessed on a case of the Nordic market. [ABSTRACT FROM PUBLISHER]

In this paper, the interactions between component failures are quantified and the interaction matrix and interaction network are obtained. The quantified interactions can capture the general propagation patterns of the cascades from utilities or simulation, thus helping to better understand how cascading failures propagate and to identify key links and key components that are crucial for cascading failure propagation. By utilizing these interactions a high-level probabilistic model called interaction model is proposed to study the influence of interactions on cascading failure risk and to support online decision-making. It is much more time-efficient to first quantify the interactions between component failures with fewer original cascades from a more detailed cascading failure model and then perform the interaction model simulation than it is to directly simulate a large number of cascades with a more detailed model. Interaction-based mitigation measures are suggested to mitigate cascading failure risk by weakening key links, which can be achieved in real systems by wide-area protection such as blocking of some specific protective relays. The proposed interaction quantifying method and interaction model are validated with line outage data generated by the AC OPA cascading simulations on the IEEE 118-bus system. [ABSTRACT FROM PUBLISHER]

The paper investigates the effect of a transformer unplanned outage on the failure probability of the remaining transformers in the network. The probability of consequential dependent failures of transformers might ultimately lead to a multiple or cascading failure. New probabilistic indicators based on the transformer's unavailability under outage conditions have been formulated for individual power transformers and transformer sites to help with this assessment. The effect of thermal stress of transformer on its unavailability due to the new loading condition is taken into account as well as the age and the original loading of the transformer. The Arrhenius–Weibull life-stress model was adopted for assessment of the transformer unavailability. The study identifies both transformers whose outage could initiate cascading failure and those that are the most vulnerable to consequential failure. The effectiveness of the proposed probabilistic indicators in identifying the most critical transformers for multiple failure events is demonstrated on a realistic transmission test system with 154 power transformers. [ABSTRACT FROM PUBLISHER]

Voltage flicker is one of many serious power quality disturbances, which would deteriorate the stability and operation efficiency of a power system. Effective evaluation of flicker severity plays an important role in the monitoring and control of developing advanced metering infrastructure. Since the evaluation process for voltage flicker is complicated, some inaccurate intermediate results may give rise to the propagation of estimation errors. Therefore, an accurate solution procedure for the calculation of voltage flicker components is proposed in this paper. With the extraction technique for envelope signal and high-frequency resolution mechanism for flicker spectral analysis, the superior performance to achieve the instantaneous flicker severity evaluation can be obtained. [ABSTRACT FROM PUBLISHER]

This paper presents a new method to allocate the costs of the transmission system among generators and loads. The allocation is calculated for each branch of the transmission system to identify and quantify the individual responsibility of generators and loads. A two-step method based on the perfect coupling of the circuit theory with the Aumann-Shapley method is proposed here. First: to determine the participation of the generators in the costs of the transmission network, the generators are modeled as current injections and the loads as impedances. Second: to determine the participation of the loads in the cost of the transmission network, the loads are modeled as current sources and the generators as impedances. The Aumann-Shapley method and the circuit theory are used to calculate the participation of each real and imaginary current component in the “Allocation of the costs of the transmission system” game by considering them as independent agents. The properties of the Aumann-Shapley method ensure equitable allocation and recovery of the total costs. Numerical results are presented and discussed to demonstrate the applicability of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper proposes a stochastic framework to enhance the reliability and operability of wind integration using energy storage systems. A genetic algorithm (GA)-based optimization approach is used together with a probabilistic optimal power flow (POPF) to optimally place and adequately size the energy storage. The optimization scheme minimizes the sum of operation and interrupted-load costs over a planning period. Historical wind speed, load and equipment failure data are used to stochastically model the wind generation, load and equipment availability. Using Fuzzy C-Means (FCM) clustering, wind and load samples are grouped into 40 clusters of days with similar sample points to account for seasonal variations. The IEEE 24-bus system (RTS) is used to evaluate the performance of the proposed method and realize the maximum achievable reliability level. A cost-benefit analysis compares storage technologies and conventional gas-fired alternatives to reliably and efficiently integrate different wind penetration levels and determine the most economical design. Storage distribution and its effect on performance enhancement of wind integration are examined for higher wind penetrations. [ABSTRACT FROM PUBLISHER]

Fast and accurate unveiling of power-line outages is of paramount importance not only for preventing faults that may lead to blackouts, but also for routine monitoring and control tasks of the smart grid, including state estimation and optimal power flow. Existing approaches are either challenged by the combinatorial complexity issues involved and are thus limited to identifying single and double line-outages or they invoke less pragmatic assumptions such as conditionally independent phasor angle measurements available across the grid. Using only a subset of voltage phasor angle data, the present paper develops a near real-time algorithm for identifying multiple line outages at the affordable complexity of solving a sparse signal reconstruction problem via either greedy steps or coordinate descent iterations. Recognizing that the number of line outages is a small fraction of the total number of lines, the novel approach relies on reformulating the DC linear power flow model as a sparse overcomplete expansion and leveraging contemporary advances in compressive sampling and variable selection. This sparse representation can also be extended to incorporate available information on the internal system and more general line-parameter faults. Analysis and simulated tests on 118-, 300-, and 2383-bus systems confirm the effectiveness of identifying sparse power line outages. [ABSTRACT FROM PUBLISHER]

In this paper, the application method of superconducting fault current limiter (SFCL) for the protection coordination of the protective devices in a power distribution system was analyzed. The SFCL has been announced as better solution among many methods to limit a fault current effectively, which has continuously increased due to more complex network of a power system. However, the application of the SFCL in a power system affects the operation of the protection devices and the protection coordination, which requires the study on the protection coordination of the protective devices considering the application of the SFCL in a power distribution system. [ABSTRACT FROM PUBLISHER]

In this paper, an integrated simulation—optimization approach is proposed for annual planning of power restoration workforce related to an electricity distribution company in a province of Canada. Internal and external workforces are employed to perform maintenance actions and restore power after interruptions throughout the province. According to the electricity distribution network, the province is divided into a number of work locations (WL), each having local crews to perform maintenance actions and fix power interruptions. However, determining the size of the crew in each WL over the year is challenging because of high fluctuation in interruption frequency and consequently in projected demand during the year. The frequency of interruptions is affected by various factors such as geographical location, time calendar, and particularly weather conditions. The objective is to determine the optimal combination of internal and external workforce over the year to cover the interruptions across the province with minimum cost and minimum customer interruption duration. [ABSTRACT FROM PUBLISHER]

Fault location in distribution systems is an important function for outage management and service restoration directly impacting feeder reliability. In this paper, a fault location method based on matching calculated voltage sag data and data gathered at some nodes in the network is proposed. A method for characterization of voltage sags is utilized to reduce amount of transferred data. The proposed method can pinpoint fault location precisely, and is applicable to any complex distribution systems with load taps, laterals, and sub-laterals, single-phase loads, as well as networks with heterogeneous lines. The performance of the proposed method is demonstrated on the IEEE 123-node distribution test system via computer simulations in Alternate Transients Program software. [ABSTRACT FROM AUTHOR]

In this paper, the ergodic sum rate and the outage probability of a downlink single-antenna channel with K users are analyzed in the presence of Rayleigh flat fading, where limited channel state information (CSI) feedback is assumed. Specifically, only 1-bit feedback per fading block per user is available at the base station. We first study the ergodic sum rate of the 1-bit feedback scheme and consider the impact of feedback delay on the system. A closed-form expression for the achievable ergodic sum rate is presented as a function of the fading temporal correlation coefficient. It is proved that the sum rate scales as log logK, which is the same scaling law achieved by the optimal nondelayed full CSI feedback scheme. The sum-rate degradation due to outdated CSI is also evaluated in the asymptotic regimes of either large K or low SNR. The outage performance of the 1-bit feedback scheme for both instantaneous and outdated feedback is then investigated. Expressions for the outage probabilities are derived, along with the corresponding diversity-multiplexing tradeoffs (DMTs). It is shown that, with instantaneous feedback, a power allocation based on the feedback bits enables doubling of the DMT compared with the case with short-term power constraint in which a dynamic power allocation is not allowed. However, with outdated feedback, the advantage of power allocation is lost, and the DMT reverts to that achievable with no CSI feedback. Nevertheless, for finite SNR, improvement in terms of outage probability can still be obtained. [ABSTRACT FROM AUTHOR]

Real-time transient stability simulation is of paramount importance for system security assessment and to initiate preventive control actions before catastrophic events such as blackouts happen. Transient stability simulation of realistic power systems involves the solution of a large set of nonlinear differential-algebraic equations in the time-domain which requires signi icant computational resources. Exploitation of parallel processing techniques can provide an efficient and cost-effective solution to this problem. This paper proposes a fully parallel method known as instantaneous relaxation (IR) for real-time transient stability simulation. To validate the proposed method, two test systems have been implemented on an advanced PC-cluster-based real-time simulator. A comparison of the captured real-time results with those from the PSS/E software shows high accuracy. [ABSTRACT FROM AUTHOR]

The risk of blackouts is inherent in complex power systems, despite all efforts to prevent their occurrence. To mitigate the consequences of major blackouts, better restoration plans have been demanded. Commonly, these plans consist of a set of actions textually described. In order to enhance the operating staff comprehension about the restoration plan, this paper proposes a methodology, based on CPM/PERT graph theory, that allows power system restoration plans to be graphically visualized. This approach permits to clearly see the precedence relations among activities and to graphically follow the restoration process during its execution. The methodology can also take advantage of calculations involved with CPM/PERT methods to evaluate the restoration duration and the plan critical path. The application of the proposed approach is illustrated using the IEEE 30-bus network and the restoration plan developed for a portion of the Brazilian interconnected power system. [ABSTRACT FROM AUTHOR]

The proposed approach to the optimal coordination of midterm planning can be used by vertically integrated utilities as well as the ISOs in electricity markets. The approach coordinates the optimal maintenance scheduling of generating units and transmission lines, within the outage scheduling horizon of weeks to months, with the security-constrained unit commitment of available components. The proposed model provides hourly schedules for maintenance outages, generation unit commitment, and transmission flows based on hourly load curves. In addition, the approach calculates the optimal allocation of fuel and emission allowance for thermal units in a vertically integrated utility, and energy allocation in electricity markets. This paper discusses that a seamless coordination of midterm and short-term optimization schemes will effectively improve the security of electricity services and reduce the chance of blackouts in aging power systems. The proposed approach highlights a trade-off between calculation speed and accuracy for large-scale implementations. A six-bus system is used for detailed analyses, and further results presented for the IEEE-118 system exhibit the effectiveness of the proposed midterm planning approach. [ABSTRACT FROM AUTHOR]

Power distribution systems have been significantly affected by many fault causing events. Effective outage cause identification can help expedite the restoration procedure and improve the system reliability. However, the data imbalance issue in many real- world data often degrades the outage cause identification performance. In this paper, artificial immune recognition system (AIRS), an immune-inspired algorithm for supervised classification task is applied to the Duke Energy outage data for outage cause identification using three major causes (tree, animal, and lightning) as prototypes. The performance of AIRS on these real-world imbalanced data is compared with an artificial neural network (ANN). The results show that AIRS can greatly improve the performance by as much as 163% when the data are imbalanced and achieve comparable performance with ANN for relatively balanced data. [ABSTRACT FROM AUTHOR]

This paper demonstrates the use of a slow-coherency-based generator grouping algorithm and a graph theoretic approach to form controlled islands as a last resort to prevent cascading outages following large disturbances. The proposed technique is applied to a 30 000-bus, 5000-generator, 2004 summer peak load, Eastern Interconnection data and demonstrated on the August 14, 2003 blackout scenario. Adaptive rate of frequency decline-based load shedding schemes are used in the load rich islands to control frequency. The simulation results presented show the advantage of the proposed method in containing the impact of the disturbance within the islands formed and in preventing the impact of the disturbance from propagating to the rest of the system. This is demonstrated by the significant reduction in line flows in the rest of the system and by improved voltage and relative angle characteristics. Based on the suggestion in the joint U.S.-Canadian task force final report on the blackout, load shedding without any islanding is also performed, and results obtained are compared with the proposed controlled islanding method. The islanding method outperforms the load shedding-only method in reducing the transmission line flows, but both methods have similar effects on voltage and relative angle behavior. [ABSTRACT FROM AUTHOR]

This paper proposes and evaluates a method that improves the adaptability and efficiency of genetic algorithms (GAs) when applied to the minimal loss reconfiguration problem. This research reduces the searching space (population) when a new codification strategy and novel genetic operators, called accentuated crossover and directed mutation, are used. This allows a drastic reduction of the computational time and minimizes the memory requirements, ensuring a efficiency search when compared to current GA reconfiguration techniques. The reduced population is created through the branches that form ‘system loops.’ This means that almost all individuals created for the GA are feasible (radial networks) generating topologies that can only be limited by the system's operational constraints. The results of the proposed reconfiguration method are compared with other techniques, yielding smaller or equal power loss values with less computational efforts. [ABSTRACT FROM AUTHOR]

In this paper, the maximum loading margin (MLM) approach is proposed in finding generation directions to maximize the static voltage stability margin, where the MLM is evaluated at various possible generation directions in the generation direction space. An approximate and simple model representing the relation- ship between the generation direction and the LM is used to obtain the MLM point. The proposed method is validated in the modified IEEE 14-bus test system and applied to the Thailand power system. LMs of the system with the generation directions are compared for different generator combinations using the proposed technique. [ABSTRACT FROM AUTHOR]

This paper proposes a probabilistic load flow method considering random branch outages as well as uncertainties of nodal power injections. Branch outages are simulated by fictitious power injections at the corresponding nodes. A unified procedure is given to deal with random branch outages, generating unit outages, and load uncertainties by their moments and cumulants. The variations of nodal voltages and line flows produced by normally and discretely distributed input variables are handled separately. The method proposed by Von Mises is employed to solve the discrete distribution part of each state and output variable. The final distribution of a desired variable is obtained by simply convoluting its continuous and discrete distribution part. Results of 24-bus IEEE Reliability Test System are analyzed and compared to those obtained by Monte Carlo simulation. A numerical test on a real power system shows the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a comparison of the accuracy of several approaches to modeling the annual number of supply interruptions and their duration in an MV municipal cable distribution network when estimating the costs of penalty payments to be paid by the given distribution company to individual consumers as a result of breaching the guaranteed standards of supply continuity. [ABSTRACT FROM AUTHOR]

Bird related outages are more common and wide-spread than generally believed. The objective of this paper is to review the existing bird related problems and to recommend practices and procedures that are successful in reducing bird related outages on transmission lines, in substations and on overhead distribution lines. Experience has shown that use of perch guards, metal or plastic spikes, insulating caps, alternate perch sites and washing have significantly reduced bird related streamer and contamination outages. [ABSTRACT FROM AUTHOR]

This paper proposes defining a major event day (MED) in distribution reliability in terms of average frequency of occurrence. This definition is easy to understand for nontechnical people like regulators, seems to be fair to apply to systems of any size, and can be translated into a reliability threshold that can be used to classify individual days. Two possible methods of applying the definition are discussed with an example using real utility data, a bootstrap method, and fitting a probability distribution. Practical issues such as the type of probability distribution to use, how to handle zero-outage days, and calculating normal annual reliability with MEDs removed are discussed and resolved. [ABSTRACT FROM AUTHOR]

Voltage sags, also known as dips, are important to industrial reliability. This paper presents a Monte Carlo-based approach to evaluate the maximum voltage sag magnitudes in series capacitor compensated radial distribution systems. In this context, investigations have been conducted on a sample distribution system model taking into consideration the uncertainty of several factors associated with the practical operation of a power system. The power system blockset of MATLAB is used in the simulation studies. [ABSTRACT FROM AUTHOR]

Monitoring of events in the power system provides a great deal of insight into the behavior of the system. Events with impact on the entire power system typically occur in or near the transmission network and are therefore best monitored at transmission system substations. This puts great demands on the equipment and in general restricts the use of the data since it becomes property of the transmission system operator. An alternative is to measure at lower voltage levels. This paper documents the close agreement between voltage and frequency at low and high voltage levels during a remote and a nearby fault in the transmission network. The very high quality of the data suggests that valuable information about the transmission system can be obtained at lower voltages. [ABSTRACT FROM AUTHOR]