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Operating electrical networks by Dynamic Transformer Rating (DTR) unlocks the capacity of grids and allows to increase the exploitation of distributed generation and renewables. However, there is risk associated with the operation of transformers by DTR. Energy dispatch and/or load curtailment must be scheduled before the actual energy delivery, thus DTR and load should be predicted prior the actual transformer loading. Since both are random variables, this problem is prone to be addressed by stress-strength analysis. In this paper, the novel comprehensive probabilistic tool “SmarTrafo” is presented. It allows predicting the probability of the DTR to be greater than the load (i.e., the probability of success) through an exact analytic stress-strength model, and formulating an alarm-setting strategy in order to establish a warning if the expected probability is greater than a threshold. Specifically, the threshold is optimized in a multi-objective formulation, exploiting three different indices which differently evaluate the predictive skill of alarm-setting strategy. Numerical experiments based on actual data confirm the suitability of the proposal in predicting the probability of success and in establishing high-performance alarms based on such predictions. [ABSTRACT FROM AUTHOR]

Due to the demand for high reliability, modular multilevel converters (MMCs) are designed with redundant submodules. Redundant submodules can be integrated into the converter by employing different redundancy schemes: the conventional active scheme, the load-sharing active scheme, and the passive scheme. Different schemes have different impacts on the improvement of converter reliability. The contributions of this paper include that an analytical method is proposed to evaluate the reliability of MMCs under different redundancy schemes and the factors’ influence on the converter reliability is analyzed to determine the proper redundancy scheme. Reliability models of MMCs under different redundancy schemes are built using Markov chains and the iteration method. Based on the proposed models, the effects of redundant schemes are evaluated in terms of the converter reliability. A case study is conducted to validate the feasibility and robustness of proposed models and to specify the conditions in the favor of each redundancy scheme. The benefits of sharing redundancy among arms are also explored from the reliability point of view. If insulated-gate bipolar transistors (IGBTs) and capacitors are dominant components in a submodule in terms of failure rates, the load-sharing active scheme performs better; otherwise, setting the redundant submodules in an idle state is more effective. It is also found that the number of required redundant submodules is greatly reduced by sharing redundancy among arms. [ABSTRACT FROM AUTHOR]

The half-bridge-based modular multilevel converter (MMC) has emerged as the favored converter topology for voltage-source HVDC applications. The submodules within the converter can be constructed with either individual insulated-gate bipolar transistor (IGBT) modules or with series-connected IGBTs, which allows for different redundancy strategies to be employed. The main contribution of this paper is that an analytical method was proposed to analyze the reliability of MMCs with the consideration of submodule arrangements and redundancy strategies. Based on the analytical method, the relative merits of two approaches to adding redundancy, and variants created by varying the submodule voltage, are assessed in terms of overall converter reliability. Case studies were conducted to compare the reliability characteristics of converters constructed using the two submodule topologies. It is found that reliability of the MMC with series-connected IGBTs is higher for the first few years but then decreases rapidly. By assigning a reduced nominal voltage to the series valve submodule upon IGBT module failure, the need to install redundant submodules is greatly reduced. [ABSTRACT FROM PUBLISHER]

This paper presents an economic study to find the switches that should participate in a switch upgrade plan, based on the results of reconfiguration. The traditional reconfiguration problem trend considers only one loading condition (mostly maximum demand), in order to find the optimum reconfiguration. However, as the distribution loading condition has hourly and daily variations, the optimum configuration continuously changes. Consequently, considering only one loading condition might lead to inefficiency of the results. In this paper, daily load curves of different types of distribution consumers, during various types of days (weekdays and holidays) and seasons (summer and winter), are used to obtain the best reconfiguration hours during a day. Then, genetic algorithm (GA) is used to obtain the optimum configuration during each time interval. The objective function applied to GA consists of loss and energy not supplied. The switches that contribute to reconfiguration should be remotely controlled in order to have the capability of immediate mode alteration. In order to evaluate the feasibility of automated switch installation, the benefit-to-cost ratio is calculated. The entire procedure is applied to a test distribution system, and the results are discussed in this paper. [ABSTRACT FROM AUTHOR]

Reliability assessment methods that need large failure sample sets would face a bottleneck while the “high reliability” of the protection system is taken into account and would, therefore, directly affect the credibility of the assessment results. To overcome this inadequacy, a protection system reliability assessment method based on small failure samples was proposed. First, after analyzing the operating characteristics of protection devices and its small failure sample data, the Weibull distribution was selected as the failure distribution through the goodness-of-fit test. Second, the parameters of the Weibull distribution were estimated by regression analysis, and Monte-Carlo simulation was used to determine the prior distribution of the Bayes estimation. The posterior probability and reliability indices were then obtained by using the Bayes theory. The case study demonstrates the effectiveness of the method. [ABSTRACT FROM AUTHOR]

The effectiveness of various functions in a smart distribution grid relies on a reliable communication system. These functions are normally developed based on specific automation schemes. The majority of automated fault-management schemes (AFMSs) requires a dependable communication system to accomplish their intended functions. In a smart distribution grid, the AFMSs are responsible for automatic fault detection, location, isolation, and service restoration activities. Failure to communicate among various communicating devices involved in the AFMS may have a considerable impact on the reliability of electricity service delivered to the customers. This paper aims to quantitatively evaluate the reliability impact of failure to communicate in the AFMS. A highly loaded urban distribution network equipped with AFMS is utilized for directing the quantitative reliability case studies. The study results show that the service reliability can be significantly affected if the communication system fails to operate successfully. [ABSTRACT FROM AUTHOR]

Constant failure rate model used in the conventional reliability assessment of power systems cannot reflect the impacts of the various operating conditions such as transformer loading, ambient temperature, weather on component reliability. A hybrid conditions-dependent outage model (CDOM) of a transformer is proposed in this paper to include those impacts. The CDOM is the combination of three failure models: the aging failures due to the loss of mechanical strength of conductor insulation; the random failures considering weather conditions, and the outages caused by the direct trips of the overload protections. The component reliability using the proposed model has been tested under different operating conditions. The model is also applied in power system operational reliability assessment. The reliability indices using CDOM are compared with that using the condition-independent outage model. The reliability indices using the CDOMs of transformers can provide useful information for operators to understand possible system and component failure risk in real-time operation and to make important alleviation decisions. [ABSTRACT FROM AUTHOR]

Lightning is a significant cause of faults and outages in many electric power systems and is one of the major causes of poor system reliability. Predictive assessment of distribution reliability indices can be used to identify areas that have poor reliability so that appropriate changes in system design can be implemented. The assessment of distribution system performance under lightning conditions requires modeling of storm characteristics and system response. In this paper, a Monte Carlo simulation for evaluating distribution system reliability under lightning storm conditions is presented. The results from a practical distribution system show the importance of detailed modeling of storm characteristics and simulation of the system response in assessing distribution system reliability during lightning storms. [ABSTRACT FROM AUTHOR]

In order to ensure that the changing utility environment does not adversely affect the reliability of electric power supplied to customers, several state regulatory agencies have started to prescribe reliability standards-minimum reliability levels-to be maintained by electric power distribution companies. The standards are based on reliability indexes computed from historical outage data. The reliability indexes vary from year to year because of the statistical variation in the number of customer interruptions and the duration of such interruptions. To be effective, the reliability standards adopted must identify feeders that consistently perform poorly, while being insensitive to those that occasionally have poor reliability. This paper employs a duration based Monte Carlo simulation to explore the predicted impact of various reliability standards on a large practical distribution system. The sensitivity of different standards to differences in system size and component failure rate is also explored. [ABSTRACT FROM AUTHOR]