1 Knowing Your Customers Better Through Load Research Presented By: Lawrence M. Strawn Senior Retail Pricing Coordinator Orlando Utilities Commission September

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Knowing Your Customers Better Through Load Research

Presented By:

Lawrence M. Strawn

Senior Retail Pricing Coordinator

Orlando Utilities Commission

September 21, 2004

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Agenda

• Background

• Define load research

• Getting started

• Meter sample selection

• Uses of data

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• Located in Orlando, Florida• OUC provides electric, water and chilled water to

Orlando, St Cloud and parts of unincorporated Orange and Osceola Counties.

• OUC net generating capability is 1,285 MW.• The peak demand for FY2003 was 1,019 MW

Winter and 969 MW Summer

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• The State of Florida is regulated• OUC provides fully bundled service

(generation, transmission and distribution)• OUC electric customers:

– Residential 158,000 (86%)– Commercial 25,000 (14%)– Total 183,000

• OUC does not have a large industrial load

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Load Research

• The process of gathering, verifying, and aggregating interval meter data to determine the behavior and timing of consumer demand.

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Getting Started

• Determine your objective

• Metering equipment

• Hardware required

• Software required

• Required resources

• Determine meter sample selection

• Capital and ongoing costs

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OUC’s Load Research Objective

• Gain a better understanding of customer and customer class usage characteristics.

• Understand the costs associated with servicing varying usage characteristics.

• Develop rate strategies that send the appropriate rate signals to customers.

• Have necessary information available to develop innovative rates.• Seasonal time of use rates.• Curtailable rates.• Photovoltaic rates.

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Sample Residential Shape

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kW Residential

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Sample Commercial Shape

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Sample Load Shapes

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ResidentialCommercial

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Metering Equipment

Alpha solid state meter with load

profile capability on circuit board. An internal modem is preferred.

OUC’s meter alliance

provider is Elster

Electricity, LLC.

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Hardware Required

Handheld Itron

Laptop Computer

Phone Line to Meter

Server

And / or

And / or

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Hardware Required

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Software Required

• OUC is using:– Premier Plus 4

– MV90

– Pervasive for MV90

• Other products available– Stark

– Datamatic

Software is required to:– Download

– Verify

– Store

– Organize

– Display

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Required Resources

M e te r R e a d ing

M e te r O pe ra tio ns

R e ve n u e P ro te ctio n a n d S e rv ice

D ire c to rE le c tric M e te r S h op

A cco u n t R e ps

R e ta il P ric in g C o o r.

R e s /C o m m E n e rgy A u d ito rs

D ire c to rC o m m e rica l M a rke ts

C o m m e rc ia l S e rv ic esC h ille d W a te r S e rv ic es

R e s id e n tia l C us to m e r S e rv ice

V .P . C u s to m er C o nn e c tion

Information Technology

Billing

Forecasting

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Required Resources





A cco u n t R e ps








Billing

Forecasting

Meter Readers collect the interval

load data using handheld Itrons. It

takes approximately 3 - 5 minutes per meter to download the

data

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Required Resources





A cco u n t R e ps








Billing

Forecasting

Meter Operations collects the raw

data, verifies it, and ensures it is stored correctly in MV90.

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Required Resources





A cco u n t R e ps








Billing

Forecasting


provides hardware and software

support

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Required Resources





A cco u n t R e ps








Billing

Forecasting

Commercial Account Reps use

the data when working with

customers to 1) ensure they are on the correct rate or 2) help them better

understand their operations.

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Required Resources





A cco u n t R e ps








Billing

Forecasting

Retail Pricing Coordinators use the data for the

Cost of Service and Rate Design.

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Required Resources





A cco u n t R e ps








Billing

Forecasting

Commercial Energy Auditors use the

data to help customers

understand how their usage affects their monthly bill

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Required Resources





A cco u n t R e ps








Billing

Forecasting

Forecasting uses the data to prepare the sales forecast

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Meter Sample Selection

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Meter Sample Selection

• Review your load research objective.

• Assess what data you already have.

• Are there small customer classes or groups of meters you can gather 100% (census)?

• Which customer classes are too large to census and must be sampled?

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Number of Meters by Rate Class

Rate Class kW

Secondary Primary

Standard Demand

Time of UseStandard Demand

Time of Use

GSLD 6,000 + 1 2 1 3

GSD1 1,000–6,000 21 27 1 9

GSD2500–1,000 89 46 3 2

50-500 4,662 248 7 0

GSND < 50 15,915

Res n/a 57,000 Homes 75,000 Apartments

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Number of Meters by Rate Class

Secondary Primary

kWStandard Demand

Time of UseStandard Demand

Time of Use

GSLD 6,000 + 1 2 1 3

GSD1 1,000–6,000 21 27 1 9

GSD2500–1,000 89 46 3 2

50-500 4,662 248 7 0

GSND < 50 15,915

Res n/a 57,000 Homes 75,000 Apartments

Census Sample

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Determining Sample Size

n =Z2 x σ2

E2

n = Sample Size

Z = Level of Significance (1.960 for 95% confidence, 1.645 for 90%)

σ = Population Standard Deviation

E = Acceptable Amount of Sampling Error

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n =1.9602 x σ2

E2

n = Sample Size




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Population Standard Deviation

• Standard deviation (σ) of what?– Kilowatt hours.

– Load factors.

– Average market value per MWh.

• Market Price Vector– Florida Municipal Power Pool (FMPP) clearing house

price vector

• Calculated the σ of the average market value per MWh for 100 GSD2 secondary meters ($3.77).

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n =1.9602 x 3.772

E2

n = Sample Size




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n =1.9602 x 3.772

$1.002

n = Sample Size




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55 =1.9602 x 3.772

$1.002

By randomly sampling 55 meters within a customer class, OUC can be 95 percent certain that the sample’s market value per MWh will represent the population’s market value within plus or minus $1.00/MWh.

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Uses of Data

Calculating Allocation Factors to Use in the

Cost of Service and Rate Design

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Step 1: Calculate Customer Class Shapes

Hour Meter 1

Plus

Meter 2

Plus

Meter 3

Equals

Class Shape

1 5 14 8 27

2 6 17 8 31

…

8759 9 20 10 39

8760 8 21 10 39

Total kWh 61,320 157,680 78,840 297,840

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Step 2: Scale to Forecast

Hour Class Shape

Times (300,000 / 297,840) equals

Class Shape (Scaled to Forecast)

1 27 27.2

2 31 31.2

…

8759 39 39.3

8760 39 39.3

Total kWh 297,840 300,000

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Step 3: Derive Residential/GSND Class Shape

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200,000

400,000

600,000

800,000

1,000,000

1,200,00012

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SystemStreetlightsGSLDGSD1GSD2

Res/GSND

Line loss calculations must be included

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Step 4: Verify Shape of Res/GSND

Compare average market value per MWh of calculated shape to that of sample shape. The two market values should be within $1.00 per MWh.

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Step 5: Compute Allocation Factors

• Monthly coincident peak (12CP)

• Non-coincident peak (NCP)

• Average and excess demands

• Average market value per MWh– By class– By time period within class

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Sample Load Shapes

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ResidentialCommercialMarket Value *

* Florida Municipal Power Pool (FMPP) Clearing House Price Vector

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Sample Load Shapes

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ResidentialCommercialMarket Value *

$39.85/MWh

$39.00/MWh

* Florida Municipal Power Pool (FMPP) Generation Clearing House Price Vector

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Time of Use Rates(Summer)

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$60.00

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* Florida Municipal Power Pool (FMPP) Clearing House Price Vector

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Other Uses of Load Research Data

• OUConsumption Online– Enables customers to understand their cost

causation

• Totalize kW on contiguous site

• Look at cost for an individual customer

• Energy conservation programs

Documents

1 Knowing Your Customers Better Through Load Research Presented By: Lawrence M. Strawn Senior Retail Pricing Coordinator Orlando Utilities Commission September