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This paper demonstrates how a probabilistic criterion could be explicitly integrated in the unit commitment (UC) formulation. Both spinning reserve and interruptible load are taken into account as the operating reserve facilities. Incorporating the interruption notice time of interruptible load involves some complexities in the evaluation procedure and problem formulation which is considered in this paper. The expected energy not supplied (EENS) is considered as a probabilistic criterion and a new method is proposed to calculate this index in the presence of interruptible load. The reliability-constrained unit commitment (RCUC) problem is formulated based on the mixed-integer programming (MIP) method that can be solved using large-scale commercial solvers. The effectiveness of the proposed formulation is examined using the IEEE-RTS. Numerical results are presented and the implementation issues are discussed. A number of analyses are examined to evaluate the impact of some important factors on the problem solution. [ABSTRACT FROM AUTHOR]

Traditional online security assessment determines whether the system is secure or not, but how secure or insecure is not explicitly indicated. This paper develops probabilistic indices, risk, to assess real-time power system security level. Risk captures not only event likelihood, but also consequence. System security level associated with low voltage and overload can be optimally controlled, using the NSGA multiobjective optimization method. A security diagram is used to visualize operating conditions in a way that enables both risk-based and traditional deterministic views. An index for cascading overloads is used to evaluate the Pareto optimal solutions. This paper shows that the multiobjective approach results in less risky and less costly operating conditions, and it provides a practical algorithm for implementation. The IEEE 24-bus RTS-1996 system is analyzed to show that risk-based system security control results in lower risk, lower cost, and less exposure to cascading outages. [ABSTRACT FROM AUTHOR]

This paper discusses the use of state diagrams in maintenance modeling. These diagrams frequently illustrate deterioration, inspections and maintenance. Mathematically, the state diagram can be represented by a Markov process. The paper discusses the properties of such a Markov process. They are compared with the maintenance situation in the real world. It is shown that some properties make the model inconsistent with reality especially in cases where a maintenance policy with non-periodic inspections is modeled. A numerical example is provided that shows that these model properties result in modeling errors. The presented results make it clear that the common practice of using Markov processes based on state diagrams must be judged critically when they are used for modeling certain maintenance strategies. [ABSTRACT FROM AUTHOR]

This paper proposes a boundary analysis method for reliability and economic assessment in distribution systems. The main purpose is to deal with uncertainties of input data, especially when statistical information is unavailable or insufficient. The presented method uses interval numbers to enclose variability and incertitude in reliability and economic parameters, and provides the estimates on upper and lower bounds of reliability and economic indices. The proposed method has been applied to real-life distribution reinforcement projects. Case studies demonstrated effectiveness and efficiency of the method. [ABSTRACT FROM AUTHOR]

This paper presents a new approach for finding the sequence of events that may lead to catastrophic failure in a power system. The probable sequences (of events) leading to catastrophic failures are identified using risk indices which incorporate the severity as well as the probability of the contingencies. Probable collapse sequences are identified offline for different possible loading conditions using a modified fast decoupled load flow method which considers the voltage and frequency dependence of loads and generator regulation characteristics and stored in a knowledge base. Pattern recognition method and fuzzy estimation are used for online identification of collapse sequences for any operating condition from the stored database (knowledge base). [ABSTRACT FROM AUTHOR]

This paper proposes a probabilistic small signal stability assessment (PSSSA) methodology based on the application of Monte Carlo approach for iterative evaluation, via modal analysis of small signal stability (SSS). Operation states represented by random values of generation and demand are analyzed. A probabilistic instability risk index based on cumulative probability distribution function of damping ratios of oscillatory modes is calculated, as well as a power system stabilizer (PSS) devices location index based on eigenvectors and participation factors, which are considered random variables. Moreover, the impact of long-distance power flows on oscillatory modes (OM) and how the damping of OM depends on the orientation and magnitude of power flows is investigated. Further, an additional index concerns qualitatively the determination of transfer capability as affected by small signal stability. PSSSA is tested on a reduced order model of New England-New York's interconnected system considering uncertainties around three different system conditions separately: highly loaded, fairly loaded, and lowly loaded. The results highlight the main advantages of PSSSA over deterministic SSS studies such as instability risk assessment, small signal stability enhancement through adequate PSS location, and the proposal of possible restrictions for transfer capability in order to avoid poorly damped oscillations in the face of the diversity in power system operation. [ABSTRACT FROM AUTHOR]

Recent research has shown that portfolio optimization theory can be extended to generation self-scheduling in a competitive energy market. This letter considers the self-scheduling problem in the case where the mean vector and covariance matrix of the probability distribution of prices are only known within given bounds, and the probability distribution is otherwise arbitrary. Under the above assumptions, it is shown that a method for optimization over symmetric cones can be used to 1) compute the worst-case robust profit with probability level β and 2) optimize the self-schedule for a given probability level β of the corresponding worst-case robust profit. [ABSTRACT FROM AUTHOR]