Search

In transient stability simulators such as PSS/E, the bus frequency is estimated using a window of (positive-sequence) phasor angle measurements. A digital filter is often used to account for the filtering effect in actual measurement devices and to eliminate sudden changes during frequency computations. Although transient stability simulators label the filtered angle derivative as the “frequency,” the frequency provided by such programs does not match actual measurements reported by phasor measurement units (PMUs), which makes it difficult to gauge the validity of studies (e.g., wide-area event detection and control applications) that are based on such simulations. In this paper, we implement a frequency computation method directly using positive phasor angles provided by simulators. The proposed method is tested on two systems extensively and validated against the measurements of an actual PMU. The improved frequency measurements closely match PMU responses. Cross-validation results also suggest the method may be used for other systems without conducting full time-domain simulations. [ABSTRACT FROM AUTHOR]

An identification algorithm is proposed for generator outages in external systems given tie-line flow measurements and pre-outage linear sensitivity factors. The problem is challenging due to limited information available to operators in interconnected systems. To overcome the underdetermined nature of the problem (the number of tie-line measurements is smaller than the number of generators), a clustering method based on pivoted QR decomposition is implemented so that the outage location can be identified to the area of origination. Two test systems, the 68-bus New England system and the 500-bus synthetic system, were used for validation. The results demonstrate that with limited knowledge of the external system, the algorithm is able to identify the correct generator cluster in all cases. Another advantage of the proposed algorithm is its high efficiency, which enables detection within sub-milliseconds. In addition, an estimation of the cluster injection change is also provided by the algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes and evaluates a systematic method of scheduling energy storage and conventional generation capacities in a day-ahead frequency regulation market, based on compliance to control performance standard 1 (CPS1), during each hour of the following day. The salient feature of this method is the development of two simple piecewise linear curves that represent the relationship between first, conventional generation and energy storage power capacities, and second, energy storage power and energy capacities, to satisfy CPS1 compliance in the presence of stochastic load variations. These curves are then modeled inside a mixed integer linear program to solve for resource allocations by minimizing total capacity cost. As such, the formulation avoids complex algorithms that are otherwise required to model frequency dynamics inside the optimization problem. To reduce computation time, a scenario reduction algorithm is used to obtain a small set of scenarios to represent the stochastic load. The proposed method is evaluated using comprehensive dynamic simulations of the two-area IEEE reliability test system implemented in PSS/E. The results prove that the proposed method is effective for scheduling capacities to meet CPS1 compliance with minimum cost. [ABSTRACT FROM AUTHOR]