NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Modeling and Optimization of 

Commercial Buildings and 

Stationary Fuel Cell Systems

2013 Fuel Cell Seminar and Energy Exposition

Keith Wipke (presenter, NREL) for Chris Ainscough 

(NREL) and Dustin McLarty, Ryan Sullivan, Jack Brouwer

(University of California Irvine)

October 23, 2013

Columbus, Ohio

NREL/PR-5400-60904

STA44-5
2

Acknowledgements

This project is supported by the U.S. Department of 

Energy’s Fuel Cell Technologies Office

Project Manager and Champion, Jason Marcinkoski
3

Introduction

Tool Name: Distributed Generation Building Energy 

Assessment Tool (DG-BEAT)

DG-BEAT is designed to allow the stakeholders (OEMs, end 

users, building energy managers) to assess the economics of 

installing stationary fuel cell systems in a variety of building 

types in the United States. 

It enables sizing and controls optimization between 

commercial buildings, fuel cells, energy storage, and 

renewables.

Compiled version is available (for free).
4

Questions the Model Answers

1. What size fuel cell or size of other DG technology 

is best for my building?

2. What are optimal system sizes that can serve the 

broadest market in the most economical 

fashion?

3. How should fuel cell systems be dispatched to 

achieve benefits (energy, emissions, economics)?

4. How much do thermal and electrical energy 

storage systems benefit stationary FC 

installations?
5

Software Layout

DG-BEAT

Components

Fuel Cell

Chiller

Thermal 

Storage

Batteries

Solar

Wind

Demand

16 Building 

Types

16 ASHRAE 

Climates

3 Vintages

CEC Building 

Data

Controls

Base Load

Diurnal 

Dispatch

Weekly 

Dispatch

Load 

Following

Economics

Component 

Costs

O&M 

Costs

Grid Costs

Nat. Gas 

Costs

Manufacturing 

Scale Up

Analysis

Single 

Scenario

MultiBuilding

Sensitivity

Validation

National 

Survey
6

16 Building Types Modeled

Modeled buildings represent ~67% of national inventory

Sizes range from 5 kW to 1,500 kW

0

2

4

6

8

10

12

14

16

National Market (GW)
7

Economics

Utility Costs

EIA forecasted NG costs

Time-of-use electricity rates

20+ pre-loaded rate structures

State average energy costs

Equipment Costs

Installation costs, scales with capacity (kW)

Operation/maintenance costs, scales with capacity and operation (kW and kWh)

Energy costs vs. demand charges

Zero-export constraint

20-year NPV analysis

Includes stack replacement

Analyze financing methods, interest rates, offset electricity charges

0

20

40

60

80

100

Baseline With DG

Demand Charges

Energy Charges
8

Energy Storage Shift

0

5

10

15

20

25

0 1 2 3 4 5 6 7 8

Demand/Generation (kW)

Day

Electric Demand

Shifted Demand

Motivation

Move demand to lower-cost times by using cold or hot water storage
9

Preliminary Results—Without Storage

• Building: L.A. Clinic/Small Hospital (avg. demand ~100 kW)

• Utility: SoCal Edison

• Control Strategy: Base Load

• Results:

o Base load = 34 kW ~23.7% 

of demand

o Grid cost is $0.126/kWh 

delivered

o 20 year savings (NPV) is 6%

3.24 

million$ 3.02

million$

6% difference
10

Preliminary Results—With Cold Water Storage

• Building: L.A. Clinic/Small Hospital (avg. demand ~100 kW)

• Utility: SoCal Edison

• Control Strategy: Base Load

• CW Storage: 3,600 kWh

• Results:

o Base load = 34 kW ~23.7% 

of demand

o Grid cost is $0.126/kWh 

delivered

o 20 year savings (NPV) is 13%

3.24 

million$ 2.83

million$

13% difference

Takeaway: Hybridizing fuel cell systems for buildings can result in

significant savings (double, in this one case)
11

Dispatch Controller Flowchart: How it Works

Are renewable 

generators present? 

Renewable 

Power Profile

Yes

Subtract 

from 

demand 

Profile

Dispatch 

Controller

System Demand

Are there chillers or cold 

thermal storage

No

Apply 

cold 

storage 

shift

Chillers 

only

Both

Subtract 

absorption 

chiller output 

from cooling demand

Meet cooling 

demand with 

electric 

chillers

Are there 

batteries? 

Apply 

electric 

storage 

shift

Dispatch 

Fuel 

Cells

Use efficiency 

curve to 

calculate fuel 

use

Calculate 

un-met 

electric 

demand

Grid 

Electricity

Fuel 

Used

Self 

Generation

Yes

No No

BBBBBBBB DDDD ≠ G G G G

Due to renewable power and energy storage

Energy 

Shifting
12

Base Load

800

900

1000

1100

1200

1300

0 6 12 18 24

Demand/Generation (kW)

Hour

0

50

100

150

200

250

300

350

0 6 12 18 24

Grid Supply (kW)

Hour

Simplest type of dispatch

Grid Load
13

Diurnal Peaking

800

900

1000

1100

1200

1300

0 6 12 18 24

Demand/Generation (kW)

Hour

Series1

diurnal peaking

Demand

Generation

0

50

100

150

200

250

300

350

0 6 12 18 24

Grid Supply (kW)

Hour

4 x DFC300 = 1,200 kW, 4:3 turndown ratio, 10%/hour slew

Grid Load

Motivation

Increased stack life (~equal kWh spread over longer time)

Higher-value generation during on-peak hours

Larger FC installation
14

Weekend Dip

700

750

800

850

900

950

1000

1050

1100

1150

1200

024487296120144168192216

Demand/Generation (kW)

Hour

Series1

weekend dip

Demand

Generation

0

50

100

150

200

250

300

350

024487296120144168192216

Grid Supply (kW)

Hour

Grid Load

Motivation

Same as daily dispatch, but with fewer fuel cell transients
15

Control Strategy

Comparison of dispatch for our LA Clinic example

20 Year NPV Percent reduction in NPV relative to baseline

Takeaway: With storage, proper dispatch of the FC can reduce 

NPV even further. Diurnal peaking increases %NPV saved from 

13% to 15% (relative to no FC system). 

2.83 

MM$

3.03 

MM$

2.77 

MM$

2.97 

MM$
16

Optimal Size $/kW for 20 Year Lifespan

Payback Period (years)

» Optimal Size: 91 kW

» NPV: Savings 15% over baseline

20 Year NPV Percent reduction in NPV relative to baseline

DG-BEAT can find the optimal (lowest lifecycle cost) 

system for an application (again, the LA Clinic example)

If the system is too large, it will 

actually cost more than the baseline. 

Negative % reduction
17

Viable Market

Viable: Any building where 20-year NPV w/ FC is less than 20-year NPV w/o FC

DG-BEAT can estimate the viable market for a particular size of 

fuel cell system, using commercial building inventory data

Takeaway: For this case, the most viable markets are the NE and 

California 
18

Viable Regions for DG

Avg. Net Present Value: Weighted average of each building type (weighted by size and 

# buildings in state)

Includes buildings which lose money by converting to FC

Users can calculate state-by-state values for a system 

type under consideration (may be useful for OEMs)
19

Future Work Topics

• Cost optimization instead of area under demand curve (brute force for energy charges 

only)

• Scale installation to demand with fixed FC size multiples of baseline system 

(e.g., 4 x 300 kW)

• Advanced controls (e.g., predictive control) with physical DG system models and 

comparison to ideal dispatch

• Additional building energy demand profiles

o PNNL building profiles

o ASHRAE 90.1-2007 standard

o Easier upload of different formats by users

• CBECS

o Update building inventories based on output from CBECS 2012

• Refinement of economics for scenario analyses

o State incentives database (DSIRE)

o Projections for changes in utility prices

o Regional NG prices

o Regional variation in energy vs. demand charges

o Variation in utility costs and energy vs. demand costs with scale of installation

o Variation in building sizes of same class (e.g., not all hospitals = 1,200kW)
20

Summary of Functionality

1) Build a DG system out of any number of subcomponents 

(FC, chiller, batteries...)

2) Apply to 768 building types or build campus of multiple 

buildings

3) Choose from four dispatch strategies

4) Evaluate lifetime costs with 30+ real world utility rates, 

or build your own

5) Perform sensitivity analysis

6) Describe national market with detailed applicationspecific evaluation