Dynamic Pricing: Who is the Ideal RTP Customer?

 

[Read Part One of this 2-part series: Dynamic Pricing 101]

Most of us have experienced the inconvenience of a rolling blackout during a summer heat wave when fans and air-conditioners put excessive load on the electricity grid. Utility companies use rolling blackouts to spread existing power supply over a geographic area of demand by systematically blacking out one area for a period of time before rolling the blackout to the next area of demand. The blackouts occur without much warning but take stress off the supplier’s energy load.

Fortunately rolling blackouts no longer occur much in the U.S., because growing technologies have allowed power companies to better manage supply networks and accurately forecast electrical loads. Those same technological advances surrounding the Smart Grid have created new opportunities for electricity pricing based on consumption and behavior.

Dynamic or real-time pricing (RTP) allows consumers and utility companies to match pricing to real-time electricity generation conditions. Because dynamic pricing connects prices directly with supply and demand, it offers potential for great savings.

RTP also makes it easier to incorporate renewable power into the grid, and reduced peak-time demand can lower price volatility on the wholesale market. Consumers can manage their usage to get better pricing and predictable supply. Utility companies can plan for scheduled repairs and put the appropriate equipment to work when and where it makes the most sense.

Who is the Ideal RTP Customer?

For Residential Consumers

Several electricity producers have rolled out both mandatory and voluntary pilot programs to residential consumers, but such programs are often received with mixed feelings. Residential consumers may perceive drawbacks to using dynamic pricing. Educational materials are limited, and the lack of knowledge leads to confusion

Because the price of electricity is highest at peak times, residential customers may fear price-gouging if they don’t understand that a shift to off-peak activities will lower their overall electricity bill. Conversely, utilities may shy away from offering dynamic pricing to residential consumers, because the supplier fears a loss of revenue if residential users simply cut back on peak usage but don’t shift their activities to another timeslot.

Residential users vary in their needs and practices, too. Customers with their own generating units, such as solar panels, are better equipped to understand and track their usage. Customers who don’t have smart appliances and automated control systems are poor candidates for dynamic pricing. RTP programs can be complex, and a lack of consumer awareness prevents their widespread acceptance.

For Energy-intensive Businesses

Generally speaking, business customers—especially industrial and manufacturing companies—are ideal candidates for real-time pricing. They understand the cost of electricity and how they use it. Because they may spend millions of dollars on electricity, they are motivated to find better price options.

A Real-life Comparison of Flat, TOU and RTP Pricing

The following provides an overview of a study recently published in the Applied Energy journal. The authors used case studies to compare flat, TOU and RTP in U.S. manufacturing companies. They found that choosing the program that is best for your business depends on the specifics of your operations and the offerings of your utility provider.

The study, authored by Nasim Nezamoddini and Yong Wang of Binghamton University (Binghamton, New York), is titled “Real-time electricity pricing for industrial customers: Survey and case studies in the United States.” It was published April 2, 2017.

5 RTP Program Types

Different RTP programs use different approaches to calculate costs. You should know which ones your utility offers and how it suits your business operations

1. One part: One part programs are the simplest and charge customers for the whole electricity consumption in each hour by real-time prices. The study results indicated that RTP programs had better results for customers with less flexibility—those that cannot easily adjust shift and production times. TOU programs offered more savings for more flexible customers.

2. Two part: In a two-part program, the real-time prices are applied only to the electricity usage over the customer baseline load. Depending on the customer’s use of production shifts, the study results showed that a two-part program can protect inflexible customers from significant financial losses but can increase the savings of highly flexible customers.

3. Day-type: These RTP programs use predefined rates to calculate the supply charge. The predefined rates can vary based on season, time of day or week, and the prior day’s temperature.

4. Temperature-based: Prices are set according to daily temperature and can therefore work less well for consumers who cannot shift their loads away from high temperature days. These programs do benefit customers who can substitute solar power on those days.

5. Block-based: Real-time prices are transferred to TOU block prices that are calculated by taking the average of the real-time prices of that period. The study found that any loss or savings was highly dependent on each customer’s situation.

The study concluded: “The comparison results in the case studies show that the savings by switching from flat rates to TOU and dynamic pricing such as TOU and RTP are highly program-dependent. Eighteen out of the 35 base-case scenarios resulted in positive savings, and the rest resulted in zero or negative savings by switching to TOU. Twenty-nine out of 35 base-case scenarios resulted in positive savings, and the rest resulted in negative savings by switching to RTP.”

Many companies already benefit by time-of-use (TOU) pricing programs that set the price in advance for peak, mid-peak and off-peak demand. As more and more utilities offer RTP, businesses using TOU should explore the alternatives.

All in all, dynamic pricing is still in its developmental infancy. Advancing technologies and behavioral insights will increasingly lead to best practices that will result in smart, productive and efficient use of generated electricity.