Bulk Electric System Reliability Research Articles

NERC Reliability Standards and Compliance Adjust With Experience

The North American Electric Reliability Corporation (NERC) reliability standards for bulk electric system reliability became mandatory and enforceable in June of 2007. Since then, the standards and the compliance monitoring and enforcement programs have been ever‐changing to improve and expand the NERC reliability standards and to modify and focus the NERC Compliance Monitoring and Enforcement Program.

Impact of the Real-Time Thermal Loading on the Bulk Electric System Reliability

This paper presents a transmission line failure model that is enhanced with the dynamic thermal rating (DTR) system. The failure model consists of two parts. The first part is the Arrhenius model and it considers the loading effect of the DTR system as a result of operating at a higher temperature than the static thermal rating system. The second part is the Weibull model and it considers the end-of-life (natural ageing) failure effect of the transmission line. The proposed model is compared with the normal distribution model that considers only the end-of-life failure effect of the transmission line. This paper also investigates the uncertainty effects of the line failure model parameters, effects of the DTR system reliability, and the effects of the weather data correlation on the reliability performance of the power system. The proposed methodology and case studies were performed on the IEEE-reliability test network.

BULK ELECTRIC SYSTEM RELIABILITY EVALUATION WITH WIND TURBINE AND ENERGY STORAGE

This paper describes a new methodology for grid expansion planning considering the probabilistic reliability of a Bulk Electric Systems (BES) including Wind Turbine Generators (WTG) and Energy Storage System (ESS).The proposed model includes the main parameters used to create an operational history for each individual unit and transmission line unavailability. Bulk electric system reliability analysis associated with wind energy provides an opportunity to investigate the reliability benefits when large-scale wind power is injected in a BES. High wind power penetration can lead to high risk levels in the overall system reliability. The impacts of different wind turbine penetration levels on the reliability benefits from ESS are analyzed when the WTG capacity is utilized to replace the conventional generators with same total rated power capacity. The WTG and ESS capacity are installed to meet the annual growth of load demand and maintain the BES adequacy levels. The proposed method is applied to the IEEE Reliability Test System (IEEE– RTS ).

Effects of Load Forecast Uncertainty on Bulk Electric System Reliability Evaluation

Load forecast uncertainty is an important factor in long-range system planning and has been shown to have a significant impact on the calculated reliability indices in generating capacity studies. In general, a higher capacity reserve is required to satisfy a future uncertainty load than to serve a known load, at a specified level of reliability. Load forecast considerations are also important in composite generation and transmission system reliability studies, and their associated probability distributions. This paper examines the effects of load forecast uncertainty in bulk system reliability assessment incorporating changes in system composition, topology, load curtailment policies and bus load correlation levels.

Reliability assessment of bulk electric systems containing large wind farms

Wind power is an intermittent energy source that behaves quite differently than conventional energy sources. Bulk electric system reliability analysis associated with wind energy conversion systems (WECS) provides an opportunity to investigate the reliability benefits when large-scale wind power is injected at specified locations in a bulk electric system. Connecting the WECS to different locations in a bulk system can have different impacts on the overall system reliability depending on the system topology and conditions. Connecting a large-scale WECS to an area which has weak transmission could create system operating constraints and provide less system benefit than connecting it to an area with stronger transmission. This paper investigates bulk electric system transmission constraints associated with large-scale wind farms. The analyses presented in this paper can be used to determine the maximum WECS installed capacity that can be injected at specified locations in a bulk electric system, and assist system planners to create potential transmission reinforcement schemes to facilitate large-scale WECS additions to the bulk system. A sequential Monte Carlo simulation approach is used as this methodology can facilitate a time series modeling of wind speeds, and also provides accurate frequency and duration assessments. An auto-regressive moving average (ARMA) time series model is used to simulate hourly wind speeds.

Reliability-Based Transmission Reinforcement Planning Associated With Large-Scale Wind Farms

The reliability impacts of a highly variable energy source such as wind power is an important aspect that needs to be assessed as wind power penetration becomes increasingly significant. Bulk electric system (BES) reliability analysis associated with wind energy conversion systems (WECS) provides an opportunity to investigate the reliability benefits at potential BES connection points in close proximity to the wind power development area. A bulk electric system can encounter transmission capacity limitation problems when a large-scale WECS is connected to a weak transmission area. In this case, transmission reinforcement may be required in order to increase the system capability to absorb more wind power at specified locations. BES reliability analysis associated with large-scale wind farms as demonstrated in this paper can assist system planners to create potential transmission reinforcement schemes to facilitate large-scale WECS additions to a bulk system. Reliability cost/worth analysis is also incorporated in the examination of reinforcement alternatives. A sequential Monte Carlo simulation approach is used as this methodology can facilitate a time series modeling of wind speeds and also provides accurate frequency and duration assessments. An auto-regressive moving average (ARMA) time series model is used to simulate hourly wind speeds

A Combined Bulk Electric System Reliability Framework Using Adequacy and Static Security Indices

Deterministic techniques have been applied in power system planning for many years and there is a growing interest in combining these techniques with probabilistic considerations to assess the increased system stress due to the restructured electricity environment. The overall reliability framework proposed in this paper incorporates the deterministic N-1 criterion in a probabilistic framework, and results in the joint inclusion of both adequacy and security considerations in system planning. The combined framework is achieved using system well-being analysis and traditional adequacy assessment. System well-being analysis is used to quantify the degree of N-1 security and N-1 insecurity in terms of probabilities and frequencies. Traditional adequacy assessment is Incorporated to quantify the magnitude of the severity and consequences associated with system failure. The concepts are illustrated by application to two test systems. The results based on the overall reliability analysis framework indicate that adequacy indices are adversely affected by a generation deficient environment and security indices are adversely affected by a transmission deficient environment. The combined adequacy and security framework presented in this paper can assist system planners to realize the overall benefits associated with system modifications based on the degree of adequacy and security, and therefore facilitate the decision making process.

A new look at component maintenance practices and their effect on customer, station and system reliability

This paper introduces a new concept in the analysis of the effect of changes in maintenance policies on component, delivery point and bulk electric system reliability and associated costs. In the new approach several different analysis methods are combined, allowing for a comprehensive look at the effect of maintenance and reliability issues. This approach has been made possible by a development of a computer platform, which seamlessly links several complex computer programs. The concepts of the new approach and the implementation of the computer platform are presented in this paper. A numerical example illustrating implementation of these concepts is also presented.

Predicting Bulk Electricity System Reliability Performance Indices Using Sequential Monte Carlo Simulation

System reliability performance is usually based on average customer interruption information. These average values are valuable information, but provide only a single customer risk dimension without underlying probability distributions. The average annual indices give no insight on how reliability may vary from year to year as a result of the random behavior of bulk electric systems (BES). A significant advantage when utilizing sequential Monte Carlo simulation in bulk electric system reliability analysis is the ability to provide reliability index probability distributions in addition to the expected values of their indices. Parameter distribution analysis and its potential utilization are relatively new concepts in composite power system reliability analysis and decision making. This paper presents a technique to predict future reliability performance indices of the BES using a sequential simulation approach. The results obtained using the sequential software show that the system performance index probability distributions have unique characteristics that are basically dependent on the system topology and the operating philosophy. Operating policies involving load shedding procedures have a considerable impact on the system performance indices and their associated distributions. Two test systems are used to illustrate the concepts associated with the determination of system performance indices and their associated probability distributions. The results obtained using two different load shedding policies are presented and compared.

Impact of Load Shedding Philosophies on Bulk Electric System Reliability Analysis Using Sequential Monte Carlo Simulation

Sequential Monte Carlo simulation can be used to estimate bulk electric system reliability indices by simulating the actual chronological process and random behavior of the system in fixed discrete time steps. The technique consequently provides accurate frequency and duration assessments compared with those obtained using other traditional methods. Delivery point reliability indices obtained using the sequential technique, therefore, can be realistically used to forecast future system reliability performance. Operating policies such as load shedding procedures can have a considerable impact on the predicted reliability indices in a bulk electricity system. This article examines the impact of utilizing different load shedding philosophies in bulk electric system reliability analyses. The results obtained using the developed sequential software show that the adopted load shedding policy has a significant impact on the delivery point indices, but has relatively little impact on the overall system predictive indices. The load shedding philosophy, however, has a considerable impact on the system performance indices. The results obtained using three different load shedding policies are presented and compared using two test systems.

Delivery Point Reliability Indices of a Bulk Electric System Using Sequential Monte Carlo Simulation

A significant advantage when utilizing sequential Monte Carlo simulation in bulk electric system reliability analysis is the ability to provide reliability index probability distributions in addition to the expected values of their indices. Reliability index probability distributions provide a pictorial representation of the annual variability of these parameters around their mean values. Parameter distribution analysis and its potential utilization are relatively new concepts in composite power system reliability analysis and decision making. Computer software has been developed to produce reliability index probability distributions for the individual delivery points (DPs) in a bulk electric system. The results obtained using the sequential software show that the DP reliability index probability distributions have unique characteristics that are basically dependent on the system topology and the system operating philosophy. Operating policies such as load shedding procedures have a significant impact on the DP reliability indices and their associated distributions. The IEEE Reliability Test System is used to illustrate the concepts associated with the determination of DP and system indices and their associated probability distributions. The results obtained using two different load shedding policies are also presented and compared.

Reliability-performance-index probability distribution analysis of bulk electricity systems

System reliability performance is usually based on average customer-interruption indices. The average values are valuable information, but provide only a single customer risk dimension without the underlying probability distributions. The average annual indices give no insight as to how reliability may vary from year to year as a result of the random behaviour of a bulk electric system. Reliability-index probability distributions, therefore, provide additional valuable information and a more complete understanding of composite power system behaviour. A significant advantage when utilizing sequential Monte Carlo simulation in bulk electric system reliability analysis is the ability to provide reliability-index probability distributions in addition to the expected values of their indices. This paper illustrates the development of probability distributions for bulk electric system reliability performance indices using sequential simulation. The results obtained using the developed software show that the system performance-index probability distributions have unique characteristics that are basically dependent on the system topology, operating philosophy and conditions. System conditions such as the peak load level and system reinforcement options have significant impacts on the performance-index probability distribution characteristics. The basic concepts and their application in composite power system reliability evaluation are illustrated by application to a small practical test system.

September 1990 Report - The Future of Bulk Electric System Reliability in North America (1990 to 1999)

September 1990 Report - The Future of Bulk Electric System Reliability in North America (1990 to 1999)