Page 156 - Sustainable On-Site CHP Systems Design, Construction, and Operations

Fundamental Concepts 129

Manuals and Nomograms for Coarse Screening
(or Preliminary Feasibility Evaluation)
Turner (2006) identifies a number of specific manuals and references, which allow sim-
plified sizing of CHP systems. Two studies of special mention are those by Hay (1988)
and Oven (1991) which use thermal and electric load duration curves for system sizing.
This approach has also been adopted and illustrated by Orlando (1996) for two detailed
case study examples. Caton and Turner (1997) have developed a methodology for
sizing CHP plants for small industrial applications. Somasundram et al. (1988) pro-
posed a simple screening method to determine the economic feasibility of small-scale
cogeneration systems. Available billing data for electricity and gas use and cost are
needed for the “go or no-go” evaluation, which is determined from interlinked set of
figures or nomograms. Three nomograms have been developed (one for engine sizes >
400 kW, for engine sizes 100 to 400 kW, and for engine sizes 20 to 100 kW) and five illus-
trative case studies have been provided.
Fischer and Glazer (2002) and Fischer (2004) suggest a simple method involving the
development of a closed-form equation to determine the savings factor from a CHP
system. This approach is meant for any energy manager wishing to evaluate the feasi-
bility of a CHP system for his facility. It uses information such as (a) facility utility bills,
(b) utility rate structure, (c) building and system parameters and performance measures
such as recoverable waste heat, chiller COP, ratio of thermal-electric loads, and (d) equip-
ment costs. Numerical values associated with these factors are used to solve an analyti-
cal expression using a handheld calculator, and thereby deduce the simple payback.
Another closed-form method for early feasibility analysis has also been proposed by
Beyene (2002).
Knowledge-based system design approaches have also been proposed in conjunc-
tion with the technical design. Hughes et al. (1996) propose a methodology wherein the
inherent risk and uncertainty in the proper design of CHP systems are better handled
in terms of decision analysis techniques rather than traditional economic models, and
illustrate the approach with a case study. Williams et al. (1998) propose a computerized
decision support tool to aid engineers in selecting the optimal CHP system. The pro-
gram can accommodate different types of inputs depending on the type of information
available: option 1 being an initial assessment where only the type, size, and location of
the building are known, going up to option 4, where actual measured heat and power
profiles are used to size the CHP system. A commercial interval analysis tool called
EconExpert-IAT (Competitive Energy Insight 2006), driven by Excel-based spreadsheets,
has also been developed which performs an automated simulation of the economics
(discounted cash flows) associated with energy purchases, and on-site power genera-
tion using DG/CHP or energy management projects. This tool requiring interval data
(at 15 minutes, 30 minutes, or hourly time scales) uses an existing building load profile
database called EnergyShape (which was originally developed by EPRI).

Software Screening Tools
Programs in this category require only monthly thermal and electric load data and are
meant to allow evaluation as to whether a CHP system is feasible. Only after such an
analysis proves positive, would an engineer undertake a detailed system design.
Three software tools, namely Building Energy Analyzer (BEA) (2004), Ready Reckoner
(2006), and CogenPro (2004), have been evaluated in terms of their input requirements