Determination of Most Representative Residential Subdivision

• Published in: Journal of energy engineering 1993-04, Vol.119 (1), p.43-54
• Main Author: Stanford, Robert E
• Format: Article
• Language: English
• Subjects: 320100 > Energy Conservation, Consumption, & Utilization-- Buildings; Applied sciences; ELECTRIC UTILITIES; Electrical engineering. Electrical power engineering; Electrical power engineering; ENERGY CONSERVATION; ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; ENERGY CONSUMPTION; Exact sciences and technology; LOAD ANALYSIS; LOAD MANAGEMENT; MANAGEMENT; Power networks and lines; PUBLIC UTILITIES 320603 > Energy Conservation, Consumption, & Utilization-- Municipalities & Community Systems-- Public Utilities-- (1980-); RESIDENTIAL SECTOR; TECHNICAL PAPERS; Users connections and in door installation
• ISSN: 0733-9402; 0733-9372; 1943-7897; 1943-7870
• DOI: 10.1061/(ASCE)0733-9402(1993)119:1(43)

A procedure is established for determination of the most representative residential subdivision in a group of randomly selected subdivisions described by N physical characteristic measures. The procedure allows an electric utility company to use a single subdivision for their annual estimated cost differential between underground and overhead power distribution to new subdivisions. In the context of this procedure, the term most representative refers to the tendency of the selected subdivision to exhibit central values for the characteristic measures used to describe the subdivisions, as well as to the degree to which the underground versus overhead cost differential for the selected subdivision corresponds to the mean cost differential for the group of subdivisions considered. The methodology developed involves regression and correlation analyses of the relationships between the physical characteristics and the cost differentials for all the subdivisions under study as well as definition of quadratic measures of atypicality for each subdivision. The reliability of the process is established using the chi-square distribution of the atypicality measure. Data provided by a particular electric power company are analyzed, and experiences with the procedure are reported.