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An improved definition of heating and cooling degree-days for power markets.
Anyone who owns an air conditioner and pays an electric bill knows that weather drives demand for electricity, but quantifying the relationship between weather and electricity demand isn't easy. Was last winter severely cold? Winters are always cold. If it really was cold, exactly how cold was it?
One of the underlying problems is that different regions of the country have drastically different weather, technologies for generation, and local habits for keeping cool in the summer and warm in the winter. Traditionally, people have looked at weather through heating degree-days (HDD) and cooling degree-days (CDD). A common assumption with these metrics is that 65 o F is the universal thermometer setting. When the average daily temperature drops below this point, heating increases as measured by positive HDD. Alternatively, as temperatures warm above 65 o F, cooling increases leading to a higher CDD score. These are reasonable assumptions and are widely used as the basis for many weather risk-management applications and standardized weather commodity trading platforms.
But assumptions can be misleading. There is a better way.
Effective Heating and Cooling Degree Days by Load Region
In reality, there is no universal thermometer setting. In Arizona, with its hot, dry climate, people still are reaching for their Ascot sweaters at temperatures that have the residents of Eastern cities planted in front of their air conditioners. Humidity is certainly a culprit, which just highlights the fact that daily temperatures alone often don't give a complete picture. Additional complexity and variables are needed in an analysis to support any decision-making process. This leaves one with two options: gain access to a multiple, variable, non-linear regression package, or regionalize one's neutral temperature.
At Global Energy Decisions, we have adjusted the standard definition of heating- and cooling degree-days to better fit the needs of power-market participants. The result is a new term: effective degree-days (EDD) by load region. Instead of the standard universal thermometer setting of 65 o F as the basis for heating and cooling degree-days, we calculate the appropriate basis for each load-serving entity separately. We refer to this temperature as the neutral heating temperature and calculate it using a two-step process. First, we find which single weather station has the highest correlation with a given load region for daily maximum temperatures and load. Then, after we identify which weather station best represents the observed load variability, we estimate a temperature-demand response curve by fitting a polynomial to the observations. Table 1 provides a small cross- section of different load regions, the associated weather station with the highest correlation, and the neutral heating temperature we have calculated for each region.
This table shows that there can be a significant range in neutral temperature values. As one might expect, warmer climates such as Arizona and Florida seem to be slower to turn on the air (and quicker to turn up the heat) than their more northerly peers. But there are some surprises. Houston's neutral point is most similar to Pittsburgh or Kansas City.