Marayati Marsadek | Universiti Tenaga Nasional (original) (raw)
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Papers by Marayati Marsadek
This paper describes the implementation of a fast and easy-to-use, intelligence-based algorithm t... more This paper describes the implementation of a fast and easy-to-use, intelligence-based algorithm to assess the risk of voltage collapse when risk is defined as the product of the event likelihood and a severity function. In the event likelihood, the effect of weather is taken into account; the failure rate of each transmission line under different weather conditions is calculated using real historical outage data. A new severity function model that utilises the voltage collapse prediction index is proposed in this paper. Two intelligent techniques, i.e., support vector machines and a generalised regression neural network are studied, and their performances are evaluated using mean absolute and mean square error. The proposed methodology has been applied in a real power system network. Simulation results show that a generalized regression neural network provides the lowest mean absolute and mean square error.
Power system security assessment based on the concept of risk is required in the current power en... more Power system security assessment based on the concept of risk is required in the current power environment. In risk based security assessment, the likelihood and severity of security violation are the two main factors that determine the security level of a power system. To evaluate likelihood of security violation, the probability technique based on Poisson probability distribution function is adopted. Severity function signifies the extent of security violation. Two types of severity functions, namely the continuous and percentage of violation severity functions are considered in this study. This paper presents the assessment of risk of line overload at various loading condition using a risk index. A risk classification technique is also proposed so as to provide a qualitative interpretation of the risk index value by classifying the risk as low, medium and high degree of risk. This paper presents the implementation of line overload security assessment on the IEEE 24 bus test system and practical interconnection power system so as to investigate the effect of severity functions on risk classification in risk assessment. Results are presented in terms of risk index curves.
This paper describes the implementation of a fast and easy-to-use, intelligence-based algorithm t... more This paper describes the implementation of a fast and easy-to-use, intelligence-based algorithm to assess the risk of voltage collapse when risk is defined as the product of the event likelihood and a severity function. In the event likelihood, the effect of weather is taken into account; the failure rate of each transmission line under different weather conditions is calculated using real historical outage data. A new severity function model that utilises the voltage collapse prediction index is proposed in this paper. Two intelligent techniques, i.e., support vector machines and a generalised regression neural network are studied, and their performances are evaluated using mean absolute and mean square error. The proposed methodology has been applied in a real power system network. Simulation results show that a generalized regression neural network provides the lowest mean absolute and mean square error.
Power system security assessment based on the concept of risk is required in the current power en... more Power system security assessment based on the concept of risk is required in the current power environment. In risk based security assessment, the likelihood and severity of security violation are the two main factors that determine the security level of a power system. To evaluate likelihood of security violation, the probability technique based on Poisson probability distribution function is adopted. Severity function signifies the extent of security violation. Two types of severity functions, namely the continuous and percentage of violation severity functions are considered in this study. This paper presents the assessment of risk of line overload at various loading condition using a risk index. A risk classification technique is also proposed so as to provide a qualitative interpretation of the risk index value by classifying the risk as low, medium and high degree of risk. This paper presents the implementation of line overload security assessment on the IEEE 24 bus test system and practical interconnection power system so as to investigate the effect of severity functions on risk classification in risk assessment. Results are presented in terms of risk index curves.