Forecasting

I Have the Power

August 05, 2021

In econometrics generally and energy modeling specifically, variables in equations often include an exponent. In particular, this is often seen in price variables. That is, the price is raised to an exponent to impose a magnitude and direction for the responsiveness (of energy or sales) to changes in its price. In the case of electricity, the price is typically negative and fractional (e.g., -0.2. -0.1), which suggests that increases in price result in decreased consumption. If the absolute value of the exponent is greater than one (1.0), the variable is said to be elastic. If the absolute value of the exponent is less than one (1.0), the variable is said to be inelastic.

The meaning of the exponent is clear when the number is an integer greater than 1.

The following figure depicts x raised to the powers of 1, 2, 3, and 4. As the magnitude of the exponent increases, the steepness of the curve increases. That is, x4 is much steeper than x1. In fact, x1 is barely visible below, as the magnitude of x4 swamps it.

Power

That seems simple enough. Now let’s extend the idea. What is the mathematical interpretation of a decimal exponent? The best way to think about this is in terms of fractions, rather than decimals. Since any terminating decimal can be written as the quotient of two integers, this is easily represented by the following example:

Once the decimal is converted into a fraction, we can express the exponent more generally as follows:

The denominator (b) of the fraction is the root of the base (x) and the numerator (a) is the exponent to which the root is raised, which can also be written more intuitively as follows:

The following is a numerical example:

The following figure depicts x raised to the powers of 1/4, 2/4, 3/4, and 4/4 (respectively equal to 0.25, 0.5, 0.75, and 1). As in the case of the integer exponents above, the steepness of the curve increases as the magnitude of the exponent increases. Viewed alternatively, the curve flattens (i.e., gets closer to 0) as the decimal gets smaller. Thus, x1/4 is closer to 0 on the y-axis than x4/4 (which is equivalent to x1).

Power

As alluded to above, we often use negative exponents in energy forecasting.

The rule for evaluating this expression is to take the multiplicative inverse of the number and raise it to the positive power. Thus, the above expression becomes:

We can extend this idea to negative fractional exponents:

This can also be expressed as:

Let’s return to our original numerical example, except this time with a negative exponent:

After all of the intermediate steps, you should note that the result (1/125) is simply the inverse of the original result (125).

With this knowledge, you can now interpret exponents with a deeper level of understanding for your modeling with MetrixND. More importantly, you are now well-equipped to speak intelligently to the next 10th grader you meet.

There’s more great information on a variety of load forecasting topics available in the forecasting section of the Itron website and we invite you to also register for our regular free webinars. Let us help you improve your forecasts! Contact us at forecasting@itron.com.

By Rich Simons


Principal Forecast Consultant


Since joining Itron in 2000, Mr. Simons has developed, implemented and supported numerous day-ahead and real-time forecasting systems for Independent System Operators (ISOs), retailers, distribution companies, cooperatives and wholesale generators, including NYISO, IESO, TVA, Consolidated Edison, NRG Energy, PSEG and Vectren. Mr. Simons has implemented systems to support budget & long-term forecasting, weather-normalization, and unbilled-energy estimation for municipal utilities, electric cooperatives and investor-owned utilities, including Ameren, Entergy and FirstEnergy. Mr. Simons has developed forecasting and analysis solutions for municipal water utilities and has developed several customized applications and models for forecasting revenues, managing bills, weather-normalizing sales and estimating unbilled energy. Mr. Simons has reconfigured, streamlined and deployed load research systems at multiple utilities including United Illuminating, Indianapolis Power & Light, TECO Energy, NVEnergy, Colorado Springs Utilities and Lincoln Electric. Mr. Simons has implemented real-time natural gas forecasting systems to support operations at Vectren Energy and Consolidated Edison. In 2019 and 2020, Mr. Simons was a key team-member on a well-publicized report for NYISO to analyze long-term weather trends across the New York state.


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