1. NAME AND TITLE

PICES: Probabilistic Investigation of Capacity and Energy Shortages.

2. CONTRIBUTOR

Oak Ridge National Laboratory through the Energy Science and Technology Software Center.

3. CODING LANGUAGE AND COMPUTER

Fortran; IBM 3033(P00568I303300).

4. NATURE OF PROBLEM SOLVED

PICES (Probabilistic Investigation of Capacity and Energy Shortages) was developed for estimating an electric utility’s expected frequency and duration of capacity deficiencies on a daily on and off-peak basis. In addition to the system loss-of-load probability (LOLP) and loss-of-load expectation (LOLE) indices, PICES calculates the expected frequency and duration of system capacity deficiencies and the probability, expectation, and expected frequency and duration of a range of system reserve margin states. Results are aggregated and printed on a weekly, monthly, or annual basis. The program employs hourly load data and either the two-state (on/off) or a more sophisticated three-state (on/partially on/fully off) generating unit representation. Unit maintenance schedules are determined on a weekly, levelized reserve margin basis. In addition to the 8760-hour annual load record, the user provides the following information for each unit: plant capacity, annual maintenance requirement, two or three-state unit failure and repair rates, and for three-state models, the partial state capacity deficiency. PICES can also supply default failure and repair rate values, based on the Edison Electric Institute's 1979 Report on Equipment Availability for the Ten-Year Period 1968 through 1977, for many common plant types. Multi-year analysis can be performed by specifying as input data the annual peak load growth rates and plant addition and retirement schedules for each year in the study.

5. METHOD OF SOLUTION

Based on the unit specific data supplied by the user, PICES utilizes recursive techniques to calculate exact-state probability and departure rates for the range of possible system capacity deficiency states. The system load information is represented both as periodic cumulative load probability functions and load frequency functions. Unit maintenance is represented by deconvolving any units which are unavailable from the previously derived capacity deficiency probability and departure rate distributions. These probability and departure rate functions are combined with the load probability and frequency models to yield the probability and expected frequency and duration of the range of possible system reserve margin states.

6. RESTRICTIONS OR LIMITATIONS

Maxima of 1000 system reserve margin states, 301 generating units, 20 years of simulated operation, and 5 generating units added or retired per year. Plant maintenance requirements must be specified as integer weeks, and generating units are represented by either two or three-state models. Changes in load cycle shape are not accommodated within the code; the new year’s load record is derived from multiplying the annual hourly load value by the annual growth factor.

7. TYPICAL RUNNING TIME

A typical 20 year study, for a 10,000 MW system comprised of 100 units employing a 25 MW table step-size, requires 23 minutes of CPU time. NESC executed the sample problem in 50 CPU seconds on an IBM370/195.

8. COMPUTER HARDWARE REQUIREMENTS

480K bytes of memory are required for execution.

9. COMPUTER SOFTWARE REQUIREMENTS

A Fortran compiler is required.

10. REFERENCES

Greene, S. R., “PICES – A Computer Code for Evaluation of Electric Utility Static Generation Reliability, Oak Ridge National Laboratory, ORNL-5739 (August 1981).

11. CONTENTS OF CODE PACKAGE

The package is transmitted on a CD that includes the referenced document above, source code and sample problem.

12. DATE OF ABSTRACT

April 2012.

KEYWORDS: ENERGY SHORTAGES