Time-based or dynamic pricing is a form of pricing where consumers are charged different rates for a service depending on the time of day, month, or even season. In some cases, customers can be given price information in real time. In the case of the smart grid, utilities can monitor the load on the grid as well as the cost of generation of electricity and can transmit this information to customers. This can lead to a more stable and efficient grid.

However, a recent analysis by researchers at MIT indicates that providing customers with real time price information may not make the smart grid more efficient and could possibly lead to its crash. Their findings were presented in a paper and at an IEEE meeting [1]. These findings run counter to those of some real-world pilot tests, most notable the PowerCentsDC Pilot Programme in Washington, DC [2] and the ComEd Pilot Project in Chicago [3]. So the question is, does the MIT paper have merit and will dynamic pricing lead to a collapse of the smart grid? To answer this question, we gave the paper and the two real-world case studies mentioned above a close reading, carefully examining the authors’ methodologies as well as their conclusions.

Time-based Pricing

Time-based pricing can be divided into—but not limited to—several categories. They include:

1. Time-of-use (TOU) pricing: Prices are set in advance—typically one day—and do not change frequently. Thus, the rates paid by consumers during these periods are known by consumers in advance. This allows them to respond to these price signals and manage energy usage.
2. Critical Peak Pricing: This pricing scheme only comes into play during certain peak days when demand is at its greatest; otherwise, customers pay TOU pricing. The prices represent the actual cost of electricity generation.
3. Real time pricing/Dynamic pricing: Prices changes hourly or, in some exceptional cases, every few minutes. In some regions of the US (parts of New England and California), the real time market operates in five minute intervals [1].
4. Peak Load Reduction Credits: Customers with large loads can enter into pre-established peak load reduction agreements. If they meet these requirements, they receive credits towards their next bill.

The LIDS Technical Report (MIT Paper)

The LIDS Technical Report by MIT authors Roozbehani et al., published in June 2011, considered the possibility of dynamic pricing bringing down the smart grid. The authors noted that for the smart grid to operate effectively, supply and demand must be carefully matched at each instant in time. Customers receiving real time, minute-by-minute pricing information could cause rapid fluctuations in usage as people jump on downward falling rates to take advantage of potential savings. This rise or fall in demand might occur at a rate that is too rapid for utilities to adequately handle and lead to grid instabilities.

A utility's ability to react to changes in demand is known as a ramp constraint as there are limits to how quickly a utility can ramp production up or down to meet demand. While utilities may be able to meet demand as such, they may not be able to adequately respond to a strong and sudden surge in demand.

One way to prevent this potential collapse of the grid, as outlined in the paper, is to limit the information consumers receive. Instead of receiving price signals every five minutes, information can be sent every hour. Another possibility is to give customers the information in advance, say a full day, as seen in TOU pricing. Limiting information serves to dampen oscillations and stabilize demand as it gives consumers time to respond and utilities time to plan ahead.

Another solution is to determine exactly how customers consume electricity and determine the best possible times to perform various tasks. An electric vehicle, for example, can communicate with the smart grid and modulate its charge cycle—and thus electricity demand—depending on grid conditions. Trickle charging and charging while rates are low can still ensure that the car is fully charged when needed. This is different from, for example, using a dishwasher or refrigerator that must maintain certain temperature settings and thus, is not as flexible.

The PowerCentsDC Pilot Project

The PowerCentsDC Pilot Project was initiated in 2007 by the Smart Meter Pilot Programme, Inc. (SMPPI). The intent was to test consumer reaction and behaviour regarding smart prices, smart meters, and smart thermostats in the Washington, DC area. In July 2008, approximately 900 residential consumers began receiving electricity under one of four plans:

1. Control Group: This group consisted of randomly selected customers within the residential population. This group was unaware of their participation and enrolment in the programme or of the programme's existence other than previous advertisements in the media. Participants in this group paid Standard Offer Service (SOS) prices.
2. Critical Peak Pricing (CPP): Customers pay two prices i) critical peak prices that are in effect during critical peak days, of which there are typically 15 for the year and ii) other prices that are in effect for the other days in the year. Critical peak prices are higher than SOS prices, but the other prices are lower than SOS prices. Customers are notified the day before, either by a phone call, text message, email, or smart thermostat notification, when critical days are to occur.
3. Critical Peak Rebate (CPR): Customers in this plan pay SOS prices but are offered rebates for reductions in their baseline usage during critical peak periods.
4. Hourly Pricing (HP): Prices vary hourly and are set one day ahead and based on the day-ahead wholesale market. Based on market trends, prices are expected to be higher than SOS prices in effect for one-third of the year and lower for the remainder. Participants were notified when rates would be high so that they could focus on rescheduling activities to other times in the day.

The PowerCentsDC Programme was particularly noteworthy in that it was the first to compare and contrast consumer behaviour and reaction across several dynamic pricing schemes at the same time. Previous studies only looked at a single approach. In addition, the study was also able to observe and monitor consumer response across different socio-economic backgrounds.

The Commonwealth Edison Pilot Programme

The Commonwealth Edison (ComEd) Pilot Programme was initiated in the summer of 2010 by the Electric Power Research Institute (EPRI) to evaluate how customers in Chicago might modify usage levels and patterns in response to price structures, enabling technologies, and other educational and promotional strategies that may be facilitated by an Advanced Metering Infrastructure (AMI). Customers were placed into one of five payment plans:

1. Day Ahead—Real Time Pricing (DA-RTP): This pricing plan is similar to the HP pricing of the PowerCentsDC Programme.
2. Critical Peak Pricing/Peak Time Rebates: Customers pay DA-RTP prices except during days when critical periods are in effect. During critical periods, customers pay higher Critical Peak Prices (CPP) or are given rebates (Peak Time Rebates (PTR)) for reducing their consumption below a base load.
3. Time of Use (TOU): Under this schedule, customers pay prices that differ between peak and off-peak times.
4. Inclining Block Rates (IBR): Under this schedule, a customer's electricity bill and the rate paid ($/kWh) varies according to the cumulative level of consumption for the month.
5. Control Group: The control group pays standard tariff rates and exists to compare and contrast usage behaviour with the above mentioned groups.

Phase I of the study was published in April 2011 and looked at overall consumer satisfaction and savings. Phase II will look more closely at the data and examine customer demographics and usage patterns in greater depth. This is expected to be completed and published sometime next year.

The Smart Grid and Dynamic Pricing

The PowerCentsDC and the ComEd programmes are important in that they highlighted that, among other things, consumers are interested in what the smart grid has to offer. This can be attributed to the educational aspect of the programmes. While some participants were initially sceptical of what smart meters, smart appliances and smart thermostats could do for them, the cost and energy saving benefits were soon realized and they viewed the technology favourably. The PowerCentsDC Programme also highlighted differences in how people of different socioeconomic backgrounds consumed electricity. For example, higher income homeowners often chose to reduce thermostat settings and usage of energy intensive appliances while lower income homeowners and renters preferred other ways, such as turning off lights when not in use.

The LIDS Technical Report is also significant and interesting for many reasons. First, it highlights what the aforementioned studies have demonstrated: for a programme to be effective, understanding how consumers utilize energy and technology is important [4]. Second, if customers are unaware of how they can benefit from the various technologies of the smart grid, they will be unlikely to want to take advantage of them. Third, it is important to have a model in which dynamic pricing can be simulated, which in turn will allow utilities to determine how their electrical grids will react to consumer behaviour.

The model used in this pilot programme only considered the response of power generating plants, and not the presence of distributed storage facilities. An array of V2G stations with a much faster ramp constraint, for example, will have a significant impact on grid stability. A deeper understanding of consumer behaviour as well as the impact of other technologies on the smart grid is needed before any major predictions can be made by this type of model.

Dynamic pricing, along with demand response, can lead to a more stable and efficient electrical grid provided it is implemented properly.

References Used

1. Roozbehani, M., et al., "Volatility of Power Grids under Real-Time Pricing (20)," ArXiv e-prints, June 2011. 
2. "PowerCentsDC Program Final Report (0)," ESC 10-09-08, 2010.
3. M. W. G. Horst, B. Neenan, E. Marion, "The Effect on Electricity Consumption of the Commonwealth Edison Customer Application Program Pilot: Phase 1," 2011.
4. A. Faruqui and S. Sergici, "Household response to dynamic pricing of electricity: a survey of 15 experiments," Journal of Regulatory Economics, vol. 38, pp. 193-225, 2010.

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