Paul M. Anderson

Stability Simulation Of Wind Turbine Systems

A simulation and digital computer modeling effort is described in which a wind turbine- generator system is adapted for stability evaluation using a large scale transient stability computer program. Component models of the MOD-2 wind generator system are described and their digital model equations are provided. A versatile wind velocity model is described, which provides the capability of simulating a wide variety of wind variations, in addition to the usual network disturbances. Computed results obtained from runs of the enhanced stability program are provided that illustrate the wind turbine-generator system dynamic performance for changes in wind velocity.

A Probabilistic Approach to Power System Stability Analysis

Power system stability analysis is usually performed in a deterministic framework in which the time domain response of the power system is studied for certain specific disturbances to determine the adequacy of the system. However, the occurrence of disturbances and their attendant protective switching sequences are random processes and it would be more meaningful to determine the probability of stability for a power system. An approach for such a determination is presented in this paper. The probability of steady state stability is relatively easier to determine because of the linearization of the system equations. The probability of transient stability, on the other hand, is much more difficult to obtain analytically because of the nonlinear transformations required. However, a Monte Carlo simulation method to determine transient stability probability is shown to be feasible.

The Effect of Photovoltaic Power Generation on Utility Operation

This paper presents an evaluation of the effect on utility operation of photovoltaic (PV) generation that is interconnected to an electric utility grid. Various PV concentrations and performance characteristics are examined and the effect on utility generation control performance is evaluated.

Monte Carlo Simulation of Power System Stability

This paper presents a Monte Carlo simulation of the transient stability of a power system. The simulation time is in the order of years in which the occurrence of disturbances and the subsequent protective action are considered to be stochastic processes. The objective is to obtain a probabilistic measure of transient stability for a power system instead of just its particular response to an individual disturbance. The latter is the usual output of deterministic transient stability programs that are used for present day worst case analysis. A probabilistic analysis is needed if such worst case design criteria is to be replaced by (probabilistic) reliability criteria. This paper describes a computer program that has been developed for such a Monte Carlo simulation and presents some results of its application to representative systems.

Reliability Modeling of Protective Systems

Electric power systems are comprised of a very large number of interconnected components that are designed for the sole purpose of generating and delivering electrical energy to consumers. Usually, the consumers are free to accept or-reject the available electrical energy at will, suggesting a probabilistic rather than deterministic demand pattern. The system is operated by humans and by automatic control apparatus, both having some probability of failure to perform their function. Moreover, the system physical components are subject to failure in some random way, with each failure often requiring corrective action. Since the system is geographically extensive, it is subject to a large number of natural and man-made hazards. Examples are lightning induced faults and physically damaged components that result from natural or man-made causes. For the purpose of this discussion we classify all of the above as disturbances. Some of these disturbances, such as short circuits, cause severe upsets in system operation and must be somehow removed or isolated. This is the role of the protective systems, which are installed throughout the power system, to detect and remove hazardous disturbances, which we usually call faults.

Impact of New Energy Technologies on Generation Scheduling

Certain practices for the scheduling and dispatching of electric generation have become commonplace in the utility industry. These methods all take advantage of the fact that the generation for a power system is normally supplied from a small number of large units connected to the high voltage transmission system. Most of the new generation technologies, however, are much smaller in unit size and may be well dispersed. In this paper a critical examination is made of the impact of these new technologies on the generation scheduling methods. No particular technology is examined in detail but the general characteristics of all the new technologies are taken into consideration. The scheduling practices considered range from the real time load frequepcy control and economic dispatch to the weekly (short term) and yearly (long term) scheduling of generating units. It is shown that the impact will be significant and the exact effects will depend on the level of penetration, the extent of dispersion, ownership, and the weather dependency of the technologies selected.

Conventions for Block Diagram Representations

Although the use of block diagrams to represent various systems is very widespread, there are no standard conventions for the drawing of block diagrams. This is particularly true when such diagrams are used to represent complex nonlinear systems, and most practical systems of interest are of this type. The purpose of this paper is to suggest an approach to the drawing of clearly understandable block diagrams. In the process certain conventions are suggested.

AN APPROACH TO DIRECT STOCHASTIC ANALYSIS OF POWER SYSTEM STABILITY

Power system stability analysis is usually performed in a deterministic framework in which the time domain response of the power system is studied for certain specific disturbances to determine the adequacy of the system. However, the occurrence of disturbances and their attendant protective switching sequences are random processes and it would be more meaningful to determine the probability of stability for a power system. An approach for such a determination is presented in this paper. The probability of steady state stability is relatively easier to determine because of the linearization of the system equations. The probability of transient stability, on the other hand, is much more difficult to obtain analytically because of the nonlinear transformations required.