Cleantech Market Intelligence
Dynamic Pricing Moves From Theory to Practice
Dynamic pricing is one of the key elements of the smart grid proposition. Efficient market signals provided through dynamic pricing allow consumers to adapt their behavior to grid conditions and utilities to balance the grid while integrating a growing amount intermittent renewable energy. Consumers are also promised lower electricity costs as they optimize their usage, and energy companies avoid having to pass on the costs of new infrastructure investments. Completing this virtuous circle, dynamic rates incentivize consumers to adopt sophisticated energy management systems and smart appliances that can automatically control household loads in response to energy prices and grid conditions.
Dynamic rates can be seen as part of a continuum of rate structures that have time-based components. These include time-of-use (TOU) rates, demand response (DR) programs, and other event-based incentive structures. However, true dynamic rates that vary according to grid or market conditions introduce another level of flexibility in terms of matching energy supply to demand.
Thus it’s important to assess the progress being made toward the provision and adoption of dynamic tariffs for electricity. While the theoretical arguments for dynamic pricing may be strong, their actual implementation is progressing slowly. According to Navigant Research’s Dynamic Pricing report, despite considerable pilot activity, less than 1% of U.S. consumers currently have access to dynamic rates. Moreover, that number is not expected to rise significantly over next 2 or 3 years. According to the report, without a change in approach, less than 1% of U.S. consumers are likely to be on dynamic pricing programs by 2020.
Progress in this market is impeded by strong counter-forces, including consumer advocacy groups concerned about the impact of lower-income customers, utilities worried about disruption to existing business models, and regulators wary of taking a lead on the introduction of new rates.
This caution has wider implications. Many of the DR programs currently being trialed in Europe, for example, depend on sophisticated dynamic pricing models that can help balance an energy supply heavily dependent on distributed renewable energy. Regulatory drivers in Europe may be different, but there is still uncertainty about consumer response and the ability to deliver programs that meet the needs of all stakeholders.
Dynamic pricing’s role in energy demand management is also mirrored in other parts of the cleantech market. One of the principal motivations for many cleantech innovations is to account for the true cost of the resources we use and to design pricing models appropriately. The transport sector, for example, is seeing a growing interest in pay-as-you-go models for road use charging as well as more flexible tariffs for parking. The lesson from the energy market is that dynamic pricing may be theoretically attractive, but it is also highly disruptive of established businesses models and consumption patterns: moving from interesting pilots to large-scale availability will not be automatic.