Single-area System Research Articles

Teaching Load Frequency Control using Matlab and Simulink

In this paper, an attractive approach for teaching automatic load frequency control of a single-area system is presented. This approach is based primarily on using SIMULINK in building the system model and simulating its behaviour. A detailed design example for such an application is also presented.

Uncertainty considerations in frequency and duration analysis for large hydrothermal generating systems

The paper presents a general and practical method for evaluating the mean and variance of the frequency and duration indices for a single-area system. The method is based on discrete convolution, which is especially efficient when applied to large hydrothermal generating systems. It recognises the uncertain nature of generating unit transition rates and forecast peak loads by treating these parameters as random variables with specified statistics. Clustering techniques are used to model the uncertainties in the output capacities of hydraulic units. Numerical examples are presented to illustrate the impact of parameter uncertainties on the resulting indices of typical systems, including the IEEE Reliability Test System and the Brazilian South/Southeastern generating system.

Uncertainty Aspects in Lole Calculations for Two Interconnected Systems

This paper extends the basic techniques used for considering the uncertainty associated with the system parameters of a single area system to two interconnected systems and presents an approximate method for evaluating the effects of these uncertainties on the LOLE of two interconnected systems. The effect of uncertainty in tie line parameters on the LOLE index is examined. Equations are derived for calculating the mean and variance of the LOLE in each system under the different uncertainties. The methods are compared by application to a hypothetical system and to the IEEE Reliability Test System.

An Approximate and Practical Approach Including Uncertainty Concepts in Generating Capacity Reliablity Evaluation

This paper presents an approximate but practical method based on Fourier transform techniques for evaluating the significance of uncertainty associated with the basic system parameters on the LOLE index of single area systems. The method utilizes a continuous representation of a generating capacity model. The IEE Reliability Test System is used not only to illustrate the method but also to compare it with other existing methods used for considering system uncertainty.

Practical methods in the computation of LOLP variances and confidence limits

An earlier paper described a method for recognizing the uncertainty in loss-of-load probability (LOLP) as computed for a single-area system due to uncertainty in generator forced outage rates. This was done by treating generator forced outage rates as random variables with known means and variances and computing, exactly, the resulting mean and variance of LOLP. The mean and variance of LOLP were then used to compute, approximately, the limits between which LOLP can be expected to vary with specified probability. The present paper presents approximate methods for computing the variances and covariances of generating capacity outage state probabilities and of LOLP variance in systems with or without maintenance outages. These approximate methods offer significant savings in computer time and storage as compared to exact methods while maintaining excellent accuracy.

Variance and approximate confidence limits on LOLP for a single-area system

The paper presents a method for recognizing the uncertain nature of generator forced outage rates as used in computing the popular reliability index of LOLP (expected number of days per period on which capacity is insufficient) for a single-area system by treating forced outage rates as random variables with specified mean and variance. An efficient method is presented for computing the variance of LOLP in addition to the mean. Monte Carlo simulation studies indicate that LOLP is approximately gamma distributed regardless of the distribution of generator forced outage rates. Hence, approximate confidence limits for LOLP can be obtained using the gamma distribution with parameters corresponding to the computed mean and variance of LOLP.