multiplying factor for month j average consumption (kWh) by the user for the month j selected from the monthly electricity usage versus degree day plot typical working-day electric usage (kWh), i.e. the area under the typical working day electric demand profile for the month j typical non-working day usage (kWh), i.e. the area under the typical non-working day electric demand profile for the month j.

Lee suggests that each hourly load in the load profiles be multiplied by the K factor to obtain the "cor rect working and non-working day load profiles for the month." The procedure is repeated for all months of the year for both electric and steam demands. Lee states that "the resulting load profiles represent the load demand for average weather conditions."

Once a number of candidate CHP systems has been selected, equipment performance data and the load profiles are fed into CELCAP to produce the required output. The output can be obtained in a brief or detailed form. In brief form, the output consists of a summary of input data and a life cycle cost analysis including fuel, operation and maintenance and purchased power costs. The detailed printout includes all the information of the brief printout, plus hourly performance data for 2 days in each month of the year. It also includes the maximum hourly CHP output and fuel consumption. The hourly electric demand and supply are plotted, along with the hourly steam demand and supply for each month of the year.

Despite the simplifying assumptions introduced by Lee to generate average monthly and typical daily load profiles, it is evident that still a large amount of data handling and preparation is required before CELCAP is run. By recognizing the fact that CHP loads vary over time, he implicitly justifies the amount of effort in representing the input data through hourly profiles for typical working and non-working days of the month.

If a change occurs in the products, process or equipment that constitute the energy consumers within the industrial plant, a new set of load profiles must be generated. Thus, exploring different conditions requires sensitivity analyses or parametric studies for off-design conditions.

A problem that becomes evident at this point is that, to accurately represent varying loads, a large number of load data points must be estimated for subsequent use in the computer program. Conversely, the preliminary feasibility evaluation methods discussed previously, require very few and only "average" load data. However, criticism of preliminary methods has arisen for not being able to truly reflect seasonal variations in load analysis (and economic analysis) and for lacking the flexibility to represent varying CHP system performance at varying loads.

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