Article ID: | iaor19881053 |
Country: | United Kingdom |
Volume: | 16 |
Start Page Number: | 247 |
End Page Number: | 256 |
Publication Date: | Mar 1989 |
Journal: | Computers and Operations Research |
Authors: | Muralidhar Krishnamurty, Tretter Marietta |
Keywords: | statistics: sampling, artificial intelligence: expert systems |
Load research conducted by electric utility companies is an activity embracing the measurement and study of electrical load to understand the trends and behavior of electric utility consumption. The results of load research are major determinants in rate design and capacity planning for the electric utility company. Accurate load research is imperative for a well managed electric utility. The information base used in load research consists of customer billing data and sample data collected under strict guidelines set by the Public Utilities Regulatory Policies Act. Selection of appropriate sampling procedures is a central function of load research. This paper describes the evolution of an integrated expert decision support system (XDSS) for load research sample design. It is an exploratory system that has a potentially large impact on the profitability of electric utility companies. It was the result of a consulting project begun 4 years ago with a medium sized utility company. Much of the underlying statistical sampling methodology in the XDSS had to be newly derived to meet the specific needs of sampling in load research.