Download Proposed Weather Normalization of MISO Historical Peak Demand

Proposed Weather Normalization of MISO Historical Peak
Demand and Energy Data
Problem: MISO does not have an established method to weather normalize historical MISO
and Local Resource Zone demand and energy metered data. Weather normalized historical
demand and energy values would be useful in order to compare forecasted values with
historical values.
Data Needed:
Energy Normalization
Hourly temperature data
Hourly historical energy data
Population or energy data
Regional economic variable
Cooling Degree Days (CDD) and
Heating Degree Days (HDD)
Comments
At selected weather stations
For each LRZ
Used to weight weather stations
To account for economic trends
By LRZ and MISO; Based on specified
base temperature
Demand Normalization
Hourly temperature data
Seasonal peak demand dates and times
Population or energy data
Historical peak demand data
Comments
At selected weather stations
At each LRZ and MISO coincident
Used to weight weather stations
At each LRZ and MISO coincident
Proposed Mathematical Specifications:
Demand
 Average peak conditions across weather stations (possibly use weather station weights).
Assumes multiple weather stations in each LRZ.
 Possibly use hourly temperature data to calculate daily average temperatures of days before
to account for heat buildup or cold buildup
Energy
 Determine daily average temperature from hourly temperature data (multiple weather
stations)
 Determine HDD and CDD using base temperatures (use regional differences)
 Average HDD and CDD values across weather stations (possibly using weather station
weights). Assumes multiple weather stations in each LRZ.
Approach to Normal Weather for Energy and Demand
 Average HDD and CDD values for across years for normal weather conditions
 Average weather conditions at seasonal peaks across years for normal weather conditions
Statistical Approach:
Create a linear econometric model for energy using HDD, CDD, and an economic variable.
Create linear econometric models for summer demand and winter demand using peak demand
weather conditions. All models will be created with a monthly timescale from the data described
above. All 3 models will be created for each LRZ and MISO for a total of 30 models.
Weather Normalization:
The proposal is to weather normalize historical data from 2010-2014. Both actual weather
values and predicted normal weather values will be run through each of the models and the
historical data will be normalized with the equation below:
Normalized value = Actual value – (Actual weather model prediction – Normal weather model prediction)
FAQ: Weather Normalization of MISO Historical Peak
Demand and Energy Data
What is weather normalization?
Weather normalization attempts to adjust historical energy or demand values to normal weather
conditions.
Does MISO currently weather normalize historical data?
No, MISO does not currently weather normalize historical data on a regular basis. MISO has
previously done weather normalization on an ad hoc basis. Establishing a standard process for
weather normalization of historical data would also be helpful for MISO’s future historical data
needs.
How is MISO weather normalizing data?
MISO will determine normal weather conditions for each Local Resource Zone. MISO proposes
to develop a separate model for annual energy and each seasonal (Summer/Winter) peak
demand for each Local Resource Zone (LRZ) and MISO (for a total of 30 models). Each model
will be used to generate values based on actual weather conditions and normal weather
conditions. Those values will then be used to adjust the historical energy and demand values.
Why is weather normalization of historical data needed?
Weather normalizing historical data provides an adjustment for unusual or extreme weather
conditions in previous years. Weather normalized historical data would provide a comparison to
forecast data and show trends without the impacts of weather.
What data will be weather normalized?
MISO will be weather normalizing historical seasonal demand (Summer and Winter) and annual
energy data from 2010-2014.
How will the weather normalized data be used?
The weather normalized data will be used to develop a baseline of historical data. Both the
Independent Load Forecast and Aggregated Load Serving Entities’ Forecast will be compared
with the weather normalized historical data to see how they are related to historical trends and
values.
Which variables are being included in the weather normalization models?
For energy, the independent variables are heating degree days, cooling degree days, and a
regional economic variable (to be determined). For demand, the independent variables are
temperature and temperature for a certain number of days (to be determined) beforehand. More
details on the variables are included above and will also be determined as the models are being
constructed.
How is this weather normalization process related to the Independent Load Forecast
work?
Weather normalizing MISO historical data will provide a perspective of historical data without
the impacts of abnormal weather, which can be compared with both the Independent Load
Forecast and Aggregated LSEs Forecast.