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     

Bulk electric system well-being analysis using sequential Monte Carlo simulation

There is growing interest in combining deterministic considerations with probabilistic assessment in order to evaluate the "system well-being" of a composite generation and transmission system and to evaluate the likelihood not only of entering a complete failure state but also the likelihood of being very close to trouble. This paper presents bulk electric system well-being analysis using sequential Monte Carlo simulation. This approach provides accurate frequency and duration assessments and the index probability distributions associated with the mean values. The basic N-1 security criterion is used as the deterministic requirement for incorporating a deterministic consideration in a probabilistic assessment to monitor system well-being. The results shown in this paper indicate that the system well-being concept can provide comprehensive knowledge on what the degree of system vulnerability might be under a particular system condition. The basic concepts and their application in composite power system well-being analysis are illustrated by application to a small practical test system.     

Empirical Circuit Breaker Failure Rate Assessment and Modeling in a Preventive Maintenance Application

This article presents an analysis of the failure rates of SF6 puffer circuit breakers in the 230-kV voltage class. Historical failure recorded data for existing power circuit breakers in high-voltage substations in Thailand from 1992 to 2011 were retrieved. Subsequently, the data were analyzed and classified based on the causes of failure related to circuit breaker sub-components. The failure rates of the individual circuit breaker sub-components were determined. These failure rates were then categorized into three main circuit breaker component categories based on their functionality, which includes the live part and insulation, operating mechanism, and control part. The failure rates of the individual circuit breaker sub-components were calculated, and their associated probability distributions were estimated using Weibull distribution functions. The resulting Weibull distribution parameters were subsequently utilized in a circuit breaker preventive maintenance application to aid in the decision-making process for setting the maintenance schedule of the circuit breaker components. Finally, circuit breaker reliability is also monitored. This proposed method can also be applied to other high-voltage equipment in power systems.     

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.     

Utilization of time varying event-based customer interruption cost load shedding schemes

Load curtailments occurring under emergency conditions can have significant monetary impacts on the system customers. Customer satisfaction is becoming increasingly important in the new deregulated electric utility environment, and the customers in some jurisdictions are beginning to receive monetary compensation for power supply failures. Minimizing the customer interruption costs associated with a load curtailment event is an important factor in maintaining customer satisfaction. Customer interruption costs depend on many factors such as the customer types interrupted, the actual load demand at the time of the outage, the duration of the outage, the time of day and the day in which the outage occurs. This paper focuses on incorporating these interruption cost factors in a load shedding strategy. The load shedding algorithm was developed using an approximate event-based customer interruption cost evaluation technique to identify and determine the priority of the distribution feeders on a given bus during an emergency. The developed algorithm incorporates a time dependent feeder cost priority index (FCP). The optimum load shedding set determined using the FCP is a feeder or group of feeders that meet a capacity deficiency, and result in the lowest customer interruption cost for the specified emergency situation. This paper illustrates the algorithm development for a load shedding scheme and demonstrates the utilization of the technique on a sample load bus.     

Considering load-carrying capability and wind speed correlation of WECS in generation adequacy assessment

Wind power is an intermittent energy source that behaves quite differently from conventional energy sources. The reliability impact of this highly variable energy source is an important aspect that needs to be assessed as wind power penetration becomes increasingly significant. Generation adequacy assessment including wind energy conversion systems (WECS) at multiple locations is described in this paper. Effective load-carrying capabilities (ELCC) obtained using the loss of load expectation (LOLE) and the loss of load frequency (LOLF) for a power system containing WECS are illustrated and compared. The results show that ELCC obtained using the LOLF and obtained using the LOLE for WECS can be considerably different, while they are similar for a conventional generating unit. The impact on the system reliability indices of wind speed correlation between two wind farms is also examined. The studies show that the degree of wind speed correlation between two wind farms has a considerable impact on the resulting reliability indices. The 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 autoregressive moving average time series model is used in this study to simulate hourly wind speeds.