DYNAMIC DEMAND ALLOCATION
Istvan Lippai, Senior Project Engineer, Colorado Springs Utilities
Lisa Barbato, Managing Engineer, Colorado Springs Utilities
ABSTRACT: An efficient method for dynamic demand allocation is presented.
A program was designed to read water customer account billing data, convert the
customer billing data and allocate water demand for each customer to the nearest
demand node. The program is used to maintain the Colorado Springs Utilities
water model and to forecast system demand for what-if planning and design
scenarios. The paper discusses the development of the program and presents
examples of water demand allocation.
INTRODUCTION
Three primary steps in creating a computerized hydraulic model for water distribution planning
are: constructing the physical model, allocating demands to the network junctions, and validating
the network to obtain flows and pressures that match actual operating conditions. Of primary
importance in validating a hydraulic model is defining the correct magnitude and location of
water demands. If demands are not distributed and located properly in a hydraulic model, flow
and pressure outputs will not match actual operating conditions.
There are several methods for allocating water demands in a hydraulic model. For master
planning purposes, water demands can be estimated based on projected population growth.
Methods used to assign demands for existing customers can be determined based on Census tract
population estimates, traffic studies and actual customer water account billing records.
In 2001, Colorado Springs Utilities (Utilities) developed a computer program to read water
customer account billing records and allocate customer water demand spatially to the nearest
demand node in a hydraulic model. The program and procedure is used to maintain the Utilities
master water model and to forecast system demand for what-if planning and design scenarios.
This paper discusses the development of the program and presents examples of water demand
allocation.
Colorado Springs Utilities Water Distribution System
Utilities, currently serves a population of about 370,000 persons with the population projected to
increase to about 616,000 persons by year 2020.
Ground elevations within the Utilities service area range from about 5,900 feet (USGS datum)
along the southern edge of Colorado Springs to 7,800 feet in the western regions of the city along
the foothills. Water is supplied to the primary service levels (pressure zones) mainly by gravity
through a complex system of large mains, pressure reducing valves (PRV's), and storage
reservoirs.
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The Utilities service area is divided into five major service levels including Briargate,
Templeton, Northfield, Highline, and Lowline (Figure 1). Ten secondary service levels are
served within each primary service level. Four water treatment plants provide a total delivery
capacity of 230 million gallons per day (MGD). Water treatment plants are McCullough (75
MGD), Pine Valley (92 MGD), Mesa (50 MGD), and Fountain Valley Authority (FVA, 13
MGD).
McCullough (75)
Pine Valley (92)
BRIARGATE
NORTHFIELD
TEMPLETON
Mesa (50)
HIGHLINE
LOWLINE
FVA (13)
Figure 1- Colorado Springs Utilities Water Distribution System Major Pressure Zones and
Water Treatment Plants
WATER DISTRIBUTION SYSTEM MASTER PLAN AND MODEL
Black & Veatch developed a Water Distribution System Master Plan (Master Plan) for Utilities
in 1999. The Master Plan describes the existing system components as well as identifies major
short and long-term infrastructure improvements. Infrastructure improvements were identified
using the hydraulic software, H2Onet (MW Soft, 2002). The Utilities H2Onet model included all
pipes 12-inch and larger and 8-inch pipes to complete loops and simulate secondary service
levels (pressure zones). The Model included 1,434 pipes, 87 valves (PRV's and control valves),
and 62 pumps (Figure 2).
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Figure 2- Colorado Springs Utilities 1999 H2Onet Model
DYNAMIC DEMAND ALLOCATION PROGRAM
At the present time, Utilities relies on water distribution modeling for long and short term
planning, new development planning, fire flow determinations and operational predictions. An
important requirement for realistic water distribution system modeling is an accurate
determination of system demand. The addition of new developments and the modeling of hydrant
discharge capacities are increasing the links and junctions in the Model. Currently the Model has
over 13,000 links and over 10,000 junctions (Figure 3) and growing rapidly. The original
demand allocation was no longer acceptable for the changed and greatly expanded Model. A
water demand allocation program was developed to link the Model with the Utilities customer
account records of annual water billing data.
For each account, the customer number, total annual water use in cubic feet, latitude and
longitude was saved to a text file (Figure 4). In 2000, 110,765 customers used an average of
69.32 MGD. In 2001, 113,953 customers used an average of 69.99 MGD. In 2002, 117,622
customers used an average of 64.94 MGD. The 2002 average customer demand of 64.94 MGD
was adjusted to a design demand of 84 MGD to account for system losses. The text file of
customer use records is updated annually.
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Figure 3- Colorado Springs Utilities 2003 H2Onet Model
Description of Dynamic Demand Allocation Program
H2ONet organizes input data in spreadsheet format. The H2ONet Junction Demand table is
copied and pasted into the Junction Demand worksheet (Figure 5). The H2ONet Junction
Information table is copied and pasted into the Junction Information worksheet (Figure 6). The
H2ONet Node Geometry table is copied and pasted into the Node Geometry worksheet (Figure
7).
The program, WinCSU.EXE, developed with Windows C++, organizes the information from the
worksheets into arrays. Worksheet of Junction Demands is for arrays ID, DEMAND1 and
PATTERN1 , worksheet of Junction Information is for array DESCRIPT, and worksheet of Node
Geometry is for arrays for X and Y. The array for DESCRIPT serves to identify junctions with
no demand or junctions with special demand.
The Demand Solver worksheet (Figure 8) defines the user options. The most significant user
option is the targeted demand (Cell B5). The targeted demand allows the mapping of actual
demand to the target design demand. The year 2002 water billing records based average daily
demand of 64.94 MGD is be mapped into the system as 84.00 MGD design average daily
demand for 2002.
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Figure 4– Text File of Customer Water Use Records
Figure 5 – Junction Demand from H2ONet Data Base
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Figure 6 – Junction Information from H2ONet Data Base
Figure 7 – Node Geometry from H2ONet Data Base
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Figure 8 – Demand Allocation Setup Screen
The demand allocation program is activated by clicking on Cell B4 and pressing Enter, activating
the link_WinPipes function. link_WinPipes sets up the arrays and calls WinCSU.EXE.
WinCSU.EXE reads each line of customer records, converts the longitude and latitude of each
account to user X and Y coordinates, finds the junction closest to the customer and allocates the
customer use to the closest junction. It takes about two minutes to process 115,589 accounts. If
the run is successful, the total system demand is returned to Cell B4.
If no trace files are requested (trace files were used to help program development) the run will
produce three text files, SUMMARY.ZN1, SUMMARY.ZN2 and REPLACE.ALL. The
summary files show the distribution of demand by zones before and after adjusting for target
demand. The REPLACE.ALL file contains each demand junction with new demand and pattern
(Figure 9). Transfer the contents of this file to H2ONet Junction Demand data base completes
the demand allocation. The complete process takes less than 15 minutes.
DEMAND ALLOCATION PROGRAM APPLICATION
Mapping customer account records to the closest junction in H2ONet provides for quick and
accurate update of system demands. Utilities provide fire flow reports for existing hydrants.
Getting a realistic estimate of fire flow requires adding a large number of existing pipes and
junctions to the Model. Redistributing system demands after the addition of 200-300 junction
nodes maintains a realistic demand distribution in the Model and improves model convergence.
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Figure 9 – New Demands Based on Customer Use Records
Most of the growth is predicted to occur in the Briargate and Templeton zones (Figure 1).
Assigning the predicted demand increase to these pressure zones and allocating the demand was
used for exploring what-if scenarios for system expansion and operation.
ACKNOWLEDGEMENT
The authors thank Colorado Springs Utilities for supporting this project. Special thanks to Pat
Hamburger, Applications Senior and Lu Ann Maddy, Applications Specialist with Colorado
Springs Utilities for producing customer water use records.
REFERENCES
Black and Veatch Corporation, 1999. Colorado Springs Utilities, Water Distribution System
Master Plan.
MW Soft, Inc., 2002. H2Onet, Graphical Water Distribution Modeling and Management
Package.
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