Selma K. E. Awadallah

The Influence of Modeling Transformer Age Related Failures on System Reliability

The paper investigates the effect of age related failure of power transformers on the identification of most critical transformer sites for system reliability. The end-of-life failure model of power transformers is modified first to integrate loading conditions effect. The adopted Arrhenius-Weibull probability distribution, which represents the effect of thermal stress on the transformers end-of-life failure, was compared with the commonly used Gaussian probability distribution model. The sensitivity of results to the uncertainty in model parameters is thoroughly assessed, and acceptable level of uncertainty is determined. The results demonstrated the importance of integration of loading conditions into the failure model. The sensitivity analysis revealed that the identification of critical transformer sites is not significantly affected by the uncertainty in the failure model parameters and that approximate ranges of parameters can be used instead of accurate values without significant, if any, loss in accuracy. The case studies were performed on a realistic transmission test system with 154 power transformers.

Probabilistic Indicators for Assessing Age- and Loading-Based Criticality of Transformers to Cascading Failure Events

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 transformers 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.

Reliability Based Framework for Cost-Effective Replacement of Power Transmission Equipment

This paper presents a probabilistic framework for making decisions about the replacement of ageing power equipment. The framework involves three steps: first, to identify the most important and critical components of the system for overall system reliability; secondly, to perform Pareto analysis to relate the replacement of the components to the effect on system reliability indices; finally, to determine the optimum scenario for replacement based on a comparison between the cost of unreliability due to deferring the replacement and the saving on reinvestment cost. The proposed approach is illustrated on a meshed test system modeled using U.K. transmission system parameters, a representative transformer age profile and regulatory energy not supplied values. The results demonstrate the feasibility of the framework for application in the area of power system reliability, and show its feasibility for informing replacement decisions.

Quantification of aleatory and epistemic uncertainty in bulk power system reliability evaluation

Uncertainty can be generally classified as aleatory uncertainty, related to random behaviour, and epistemic uncertainty, related to a lack of information. This paper studies the uncertainty in bulk power system reliability assessment. It analyses the source of uncertainty in components outage model and refers it to the congruous uncertianty forms. This leads to the characterization of outage model uncertainty by a mixed aleatory-epistemic model. In consequence, the paper suggests two methods for representing and quantifying the effect of mixed aleatory-epistemic uncertainty on system reliability indices. These methods are second order probability and evidence theory. The paper validates the feasibility of the two methods by conducting case studies on the IEEE-RTS system using the non-sequential Monte Carlo simulation approach. The mixed aleatory-epistemic model is shown to provide more detailed estimate of uncertainty than the typical aleatory model.

Modelling of Ageing Distribution Cable for Replacement Planning

The paper proposes a new reliability model of ageing distribution cable and simulation methodology for prioritization of cable replacement. The proposed reliability model combines IEC cable thermal model, Arrhenius aging model and Weibull probability distribution. Here, Weibull scale parameter is defined through the Arrhenius aging model, in which conductor temperature is governed by the cable thermal model. A novel estimation method for the calculation of Arrhenius model parameters is proposed. The cable reliability model is then incorporated into the developed sequential Monte Carlo simulation procedure and reliability indicators and loss-of-lives are calculated. An industry based cable ranking scheme is further proposed to prioritize individual cable due for replacement. The whole methodology is tested on several medium voltage distribution networks.

Mathematical model of steam power plant for voltage and reactive power control

The paper presents development of mathematical model of steam power plant for studies of reactive power - voltage (Q-V) control. The model of realistic six generator power plant is developed in Matlab-Simulink environment. All relevant components of the system studied are modeled in sufficient detail including synchronous generators, turbines and governors, exciters and AVRs, transformers, and the network. Several case studies are used to investigate potential problems that could occur if manual control was performed by the plant operator to restore the voltage at a point of common coupling or to produce the required reactive power set by the system operator. Results of simulations are compared with recorded responses at the power plant and confirmed the accuracy of developed mathematical model.

Quantification of Uncertainty in End-of-Life Failure Models of Power Transformers for Transmission Systems Reliability Studies

Power system components have a relatively long life span and hence there is not enough data to derive an accurate end-of-life failure model. This contributes to the uncertainty in system reliability assessment. This paper discusses the quantification of the effect of uncertainty in end-of-life failure models on system reliability indices. This paper characterizes the uncertainty by a mixed aleatory-epistemic uncertainty model, where the aleatory uncertainty originated from the variability of failure events and the epistemic uncertainty originated from a lack of data. The mixed aleatory-epistemic uncertainty was propagated using two methods: Second Order Probability and Dempster-Shafer Evidence Theory (DSET). Power transformers were chosen as the case study equipment and the methods were applied on a realistic transmission network.

Assessment of suitability of different reliability importance measures for prioritising replacement of transmission system components

The paper presents a comparison of four widely used reliability importance measures in order to identify their appropriateness for the identification of the most critical system components for replacement planning; specifically when using Non-sequential Monte Carlo method. These importance measures are Improvement Potential, Structural Importance, Criticality Importance, and Fussell-Vesely Importance. The four reliability importance measures were calculated for each system component (power transformer in this particular study) and then components were ranked separately based on each measure. Then, the components were replaced, one by one starting from the most critical, to establish the relationship between the replacement according to each ranking and the overall system reliability. The study was performed on a realistic transmission network containing 154 transformers. The results of the paper proved that Improvement Potential is the most appropriate importance measure for replacement planning.

The influence of modelling transformer age related failures on system reliability

The paper investigates the effect of age related failure of power transformers on the identification of most critical transformer sites for system reliability. The end-of-life failure model of power transformers is modified first to integrate loading conditions effect. The adopted Arrhenius-Weibull probability distribution, which represents the effect of thermal stress on the transformers end-of-life failure, was compared with the commonly used Gaussian probability distribution model. The sensitivity of results to the uncertainty in model parameters is thoroughly assessed, and acceptable level of uncertainty is determined. The results demonstrated the importance of integration of loading conditions into the failure model. The sensitivity analysis revealed that the identification of critical transformer sites is not significantly affected by the uncertainty in the failure model parameters and that approximate ranges of parameters can be used instead of accurate values without significant, if any, loss in accuracy. The case studies were performed on a realistic transmission test system with 154 power transformers.

Intra-plant reactive power-voltage control: Practices, drawbacks and challenges

The paper discusses reactive power-voltage (Q-V) control in a multi-machine steam power plant (SPP). After briefly introducing some of the basic characteristics of synchronous generators voltage control through automatic voltage regulators, the practices of widely applied manual voltage references setting for Q-V control in SPP is illustrated through several examples of SPP response recorded at site. Further the case studies were developed with the emphasis on the drawbacks of manual intra-plant Q-V control by building a mathematical model of realistic SPP in Matlab-Simulink. Relying on noticed drawbacks the paper highlights the requirements for enhancing SPP reactive power response and voltage support to the power system by coordinated Q-V control at power plant level. Finally, the paper illustrates the achieved performances of coordinated Q-V controller in real SPP.