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Archives for Power System Stability

Approaches to Complying with NERC Standard PRC-019-2 on the “Coordination of Generating Unit or Plant Capabilities, Voltage Regulating Controls, and Protection”

By Francis Luces, Ric Austria, Cherry Bautista, Ted Garcia

The undesired outages of generating units during the July 1996 Outages in the Western Interconnection and the August 2003 blackout in the Eastern Interconnection have resulted in updates to reliability standards which secure, improve, and optimize generator response during power system disturbances. The North American Electric Reliability Corporation (NERC) has recently issued Standard PRC-019-2 which specifies reporting and review standards for generator protection coordination.  Because the skill requirements to conduct the review are not normally included in plant operations, outside experts are brought in that have a knowledge of what may be available in terms of information and data at the plant, the technical knowledge to conduct the coordination assessment and the experience to identify needs and deficiencies that are critical to presenting a credible review report.

In recent work, Pterra, acting as an external resource, developed approaches to conducting the review for compliance with PRC-019-2 for several legacy power plants.  Such power plants have been in operation for many years, but may have changed ownership at least once, and where test results and data may not be readily available.  This article discusses the general review approach, and applies this to a sample a 230-MVA Steam Turbine Generator Unit in a combined-cycle power station.

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Modeling Wind Farms for Power System Stability Studies

Wind energy conversion systems comprise of wind energy, and the mechanical and electrical equipment to convert this into electrical energy. The controls are an important part of being able to deliver the power to the network. Modeling wind systems for power system stability simulation studies requires careful analysis of the equipment and controls to determine the key factors that affect stability in the timeframe and bandwidth of such studies.

There are a number of public and proprietary models of wind turbine units and wind farms available for use with commercial power flow and stability simulation packages. Manufacturers of wind turbines also provide specialized models. Consultants, such as Pterra, labs and research organizations may also develop special user models. Hence, there is a variety of models to choose from. However, there are four basic types of wind farms. In selecting generic models, it may be sufficient to apply the best fit with one of the four basic types. This is particularly appropriate in planning studies.

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Deriving Machine Parameters for Simulation

For use in power system stability simulations, utilities and system operators may desire to derive accurate model parameters of generators, excitation systems, governor controls and other control equipment. The utility may have found that actual events have not been accurately simulated by computer models or that individual equipment characteristics do not seem to match the manufacturer data. Further, adjustments may have been made by field or operating personnel that have altered the response of the equipment. In these situations, there is a need to obtain more accurate models for simulation. This Techblog provides an overview of the methodology for obtaining more accurate model response from measurements of the actual equipment and appropriate derivation of parameters for the model.

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Towards Better Dynamic Simulation

Today’s popular commercial power system dynamics simulation (PSDS) software use explicit integration to handle the time-increment response of power system controls. The basis of this goes back to as early as 1960, when an integration technique known as the Fortran Analog Computer Equivalent, or FACE, was proposed. Explicit integration allows for simpler programming by assuming the response to stimulus can be represented in the next time step, thus avoiding iteration.  However, explicit integration leads to a slight numerical error that is cumulative.  This error leads to phenomena such as the “lie” and “drift” (illustrated in a case study below) encountered during dynamic simulation.

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Developing My Dynamic Model

(Dr. Gutierrez has developed numerous dynamic models over 30 years of working in the industry.  He was previously a developer for one of the major simulation software packages and has written models for several other packages, including General Electric’s PSLF program.)

From time to time it is necessary to develop user models for equipment which do not have representation in commercial software packages for stability assessments.  Emerging technologies and new equipment are typical bases for user models.  Sometimes an approximate model is applied comprised of a simple “blackbox” with current/voltage input and output.  In a pinch, a forced fit to an existing model may be attempted.  But in most cases, developing a new user model is a necessity if the objective is to accurately assess the interaction of equipment on the power network for stability.

The dynamic model may be developed by the software supplier, or, if there are inherent confidentiality issues with the supplier, by an independent consultant such as Pterra.

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