2013 Weather Normalization Survey -...

2013 Weather Normalization Survey

Itron, Inc. 11236 El Camino Real

San Diego, CA 92130‐2650 858‐724‐2620

March 2014

2013WeatherNormalizationSurvey Weather normalization is the process of reconstructing historical energy consumption assuming that normal weather occurred instead of actual weather. The process contains two key assumptions. First, a model is used to identify the weather response and calculate the difference between energy consumption under normal and actual weather conditions. Second, normal weather is defined and constructed to represent typical weather conditions. In November 2013, Itron conducted a survey of North American energy forecasters to understand and document the current practices in weather normalization. The survey asked three types of questions. The first set of questions was used to identify the respondents and the application of their weather normalization process. The second set of questions was asked to gain insights into their modeling assumptions. The final set of questions was asked to understand their definition of normal weather.

IdentificationQuestionsQuestions 1 through 8 The Survey includes responses from 135 companies across North America. These companies are separated into categories based on a self‐reporting question and company identification. Figure 1 and

Figure 2 s Figure 1:

how the relat

Survey Resp

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tive size of ea

ondents

013 Weather

ach category.

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tion Survey


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Figure 2: Survey Respondents by Size and Classification

CategoryDefinitionsThe categories used are defined as follows. Distribution. Distribution companies include both gas and electric companies that deliver

service to an end‐use customer. While these companies may include transmission and generation components, these components are not necessary for including a company into this category. Within this category, seven (7) respondents are gas only companies.

Combined Gas & Electric. These companies include both natural gas and electric distribution systems.

Retail. Retail companies are non‐regulated electric or gas companies serving either retail or wholesale customers.

ISO. Independent System Operators (ISOs) are regional organizations responsible for dispatching the electric grid and moving electricity throughout a region.

G&T. Generation and Transmission (G&T) companies maintain generation and transmission functions, but do not deliver energy to the end‐use customer. Instead, these companies deliver energy at the wholesale level.

Generation. Generation companies own power plants and do not deliver energy to end‐use customers.

Transmission. The primary business of a transmission company is to transmit energy from generators to wholesale customers.

Other. The Other category includes companies that do not fit the definitions provided in the previous categories, but still perform a weather normalization function.

The Distribution and Combined Gas & Electric categories represent final deliveries to end‐use customers. These companies account for approximately 55% of all electricity sold in the United States and Canada.

WeatherNormalizationPurposesThe 135 companies reported multiple uses for weather normalization as shown in Figure 3. While forecasting is the most common application, variance analysis, financial reporting, and rate cases are also extremely common.

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Page 7

Figure 8. The remainder of this section describes the models used for the system, residential, commercial, and industrial classes. Figure 7: Heating Variable Category Definitions

Heating Variable Category

Description

HDD Model includes heating degree day (HDD) and/or HDD spline variables. No other weather variables are used.

Interactions Model interacts HDD or HDD splines with another variable. Model may include HDD or HDD spline variables separately.

Other Model includes additional weather variables beyond HDD or HDD splines. However, no interactions with HDD or HDD splines are included.

HDD/Int/Oth Model includes HDD or HDD splines, interactions, and additional weather variables.

None Model is not used to normalize for cold weather.


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Figure 8: Cooling Variable Category Definitions

Cooling Variable Category

Description

CDD Model includes cooling degree day (CDD) and/or CDD spline variables. No other weather variables are used.

Interactions Model interacts CDD or CDD splines with another variable. Model may include CDD or CDD spline variables separately.

Other Model includes additional weather variables beyond CDD or CDD splines. However, no interactions with CDD or CDD splines are included.

CDD/Int/Oth Model includes CDD or CDD splines, interactions, and additional weather variables.

THI Model uses THI (temperature‐humidity index) instead of CDD and may include interactions and additional weather variables.

None Model is not used to normalize for hot weather.

SystemModelDescriptionThe weather variables used to capture the heating and cooling effects in a system model are shown in Figure 9. These responses are based on the definitions from Figure 7 and

Figure 8. and CDD f Figure 9:

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Page 10

Figure 10 with the number of responses shown in parenthesis.


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Figure 10: System Other Variables

Other Heating Variables Other Cooling Variables

Wind (6) Cloud Cover (5) Lag Weather (3) Dew Point/Humidity (2) Effective Temperature (1) High/Low Temperature Spread(1) Precipitation (1)

Dew Point/Humidity (8) Wind (5) Cloud Cover (4) High Temperature (3) Precipitation (3) High/Low Temperature Spread (1) Lag Weather (1)

Interactive variables allow for the heating and cooling response to change under specific conditions. 16% of the responses use interactions in the heating effect, and 18% of the responses use interactions for the cooing effect. The interacted variables listed by respondents are shown in Figure 11 with the number of responses shown in parenthesis. The primary interaction is daytypes, which includes daily, monthly, and seasonal binary variables. Figure 11: System Interactive Variables

Heating Interactions Cooling Interactions

Daytypes (9) End Use Trend (2) Economic Trend (1) Lag Temperatures (1) Deviations from Normal (1) Peak Temperature (1)

Daytypes (11) End Use Trend (3) Economic Trend (1) Hours of Light (1) Peak Temperature (1)

ResidentialModelDescriptionThe weather variables used to capture the heating and cooling effects in a residential model are shown in Figure 12. These responses are based on the definitions from Figure 7 and

Figure 8. heating (5 Figure 12

Other varvariables parenthescommon. Figure 13

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: Residential

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: Residential

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TemperatureHumidityIndexCalculationA Temperature Humidity Index (THI) is used to combine temperature and humidity into a single numerical value that captures the effects of moisture in the air. Recently, utilities have reported a wide variety of mathematical calculations to capture this effect. This survey allowed for respondents to define their index calculations. Of the 13 responses to this question, four distinct equations were provided. These four equations capture the interaction between dry bulb temperatures (T) and moisture in the form of dew point (DP) or relative humidity (RH). The equations are shown below.

Index = 0.55 * T + 0.20 * DP + 17.50 Index = T ‐ (0.55 ‐ 0.55*RH/100) * (T ‐ 58) Index = ‐42.379 + ((2.04901523*T) + (10.14333127*RH)) ‐ (0.22475541*T*RH) ‐ (0.00683783 * (T2)) ‐ (0.05481717 * (RH2)) + (0.00122874 * (T2) * RH) + (0.00085282 * T * (RH2)) ‐ (0.00000199 * (T2) * (RH2)) Index = 16.923 + ((1.85212 * 10‐1) * T) + (5.37941 * RH) ‐ ((1.00254 * 10‐1) * T * RH)

+ ((9.41695 * 10‐3) * T2) + ((7.28898 * 10‐3) * RH2) + ((3.45372 x 10‐4) * T2 * RH) ‐ ((8.14971 * 10‐4) * T * RH2) + ((1.02102 * 10‐5) * T2 * RH2) ‐ ((3.8646 * 10‐5) * T3) + ((2.91583 * 10‐5) * RH3) + ((1.42721 * 10‐6) * T3 * RH) + ((1.97483 * 10‐7) * T * RH3) ‐ ((2.18429 * 10‐8) * T3 * RH2) + ((8.43296 * 10‐10) * T2 * RH3) ‐ ((4.81975 * 10‐11) * T3 * RH3)

NormaQuestionsThe seconrepresentcan impacof questioa similar wsurvey.

NumbeFigure 22 responsesdata. Thissurvey. Tincrease i Figure 22

ChanginChanging handling cnumber oThese res Figure 23

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Figure 26 displays the last year of data included in the normal calculation. In this figure, 83% of the respondents include data from 2011, 2012, and 2013 in their calculation. Figure 25: Update Normal Weather Annually

Update Frequency 2013 Survey 2006 Survey

Responses 124 114

Update Annually 81% 69%

Do Not Update Annually 19% 31%

Figure 26

OversigBecause ninvolved iwhose noresponses Figure 27

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Page 21

Figure 28 shows that 9% of respondents use a method for climate change beyond controlling the number of years


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Figure 28: Account for Climate Change

Update Frequency 2013 Survey

Responses 124

Account for Climate Change 9%

Do Not Account for Climate Change 91%

NormalPeakWeatherNormal peak weather is used to normalize peak weather events. Two types of normal calculations are typically used in the normal peak weather calculation. These calculations are defined below.

Peak Day Weather. Peak day weather is defined as the weather conditions on the peak day only. After identifying these days, the temperatures (or HDD and CDD values) are averaged across these historical events.

High or Low. High or low weather is defined by identifying the highest and lowest historic temperatures in a month and averaging across these events regardless of when the monthly peak event occurred. The High and Low weather may have occurred on a weekend and did not cause the highest load event in the month.


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Figure 29 shows the results from 96 responses to this question. In this figure, 61% of respondents use the peak day weather approach. The other responses include different methods reported by respondents. These methods are listed below with the number of respondents include in parenthesis.

Temperature on Peak Hour (4) High Temperature Variations such as THI or a heat index (3) Rank and Average (3) Load Factor Method (2) Current and Preceding Day (1) Probability Distribution (1) Cold Snap Duration (1) Other (6)

Figure 29

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Page 24

of North Amepractices. Thather. This suused by 135 c

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Page 25

Normal Weather Updates. Most companies update the normal weather calculation each year to remain current with the latest weather information

Weather normalization continues to be a major task for companies as seen by the strong response to the well‐defined applications in forecasting, variance analysis, financial reporting, and rate cases.

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