given-will-be-excel-tables-that-provide-georgiaa

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Given will be Excel tables that provide Georgiaâ??s actual hourly weather and average electrical load for the years 1992 and 1993 (9293w_ld) and Georgiaâ??s actual hourly weather data for the year 1994 (94wtr) to estimate the average electrical load from using a regression model.

How the data is represented in the columns and cells in these tables can (and probably should) be revised (i.e., added, deleted, modified, rearranged, etc.) to make it easier to produce a viable model that outputs estimates for the year 1994 that closely shadow or mirror the trend or graph of the combined 1992 and 1993 actual average hourly electrical loads

Dear OTA –

I need a solution or method to estimate the
hourly electrical load for the State of Georgia during 1994, using Regression
Modeling Techniques.

Given will be Excel tables that provide
Georgia’s actual hourly weather and average electrical load for the years 1992
and 1993 (9293w_ld) and Georgia’s actual hourly weather data for the year 1994 (94wtr)
to estimate the average electrical load from using a regression model.

How the data is represented in the columns
and cells in these tables can (and probably should) be revised (i.e., added,
deleted, modified, rearranged, etc.) to make it easier to produce a viable
model that outputs estimates for the year 1994 that closely shadow or mirror
the trend or graph of the combined 1992
and 1993 actual average hourly electrical loads.

After
choosing and providing this viable Regression Model to estimate the 1994
electrical loads, please also provide:

1. The rationale or reasoning behind the
revisions made to how the original data was represented in the tables, and

2. A summary of the steps
taken and formulas used to calculate this particular regression model.

Attached are Excel files having two tables:

9293w_ld
Georgia’s hourly weather and load data for 1992-93

94wtr
Georgia’s hourly weather data for 1994

The
columns of data in both files are:

column 1:
MONTH OF YEAR (JAN=1, FEB=2, …)

column 2:
DAY OF MONTH ( 1 – 31)

column 3:
YEAR (92, 93, or 94)

column 4:
HOUR OF DAY (1 – 24)

column 5:
DAY OF WEEK (Sunday = 1, Monday = 2, etc.)

column 6:
DRY BULB TEMPERATURE (DEGREES FAHRENHEIT)

column 7:
WET BULB TEMP (DEGREES FAHRENHEIT)

The
1992-93 data file has an eighth column:
the average electrical load over that hour in megawatts.

Using simple
statistical methods, it is possible to construct estimates having and RMS error
of about 440. (A commercially viable
model will achieve errors of less than 100)

Some helpful load statistics to get you started:

1992: 1993:

lowest load: 889 lowest load:
943
highest load: 3865
highest load: 4283
average load: 1760
average load: 1979

If you have any questions, please don’t
hesitate to ask. Thank you.

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