All costs are fixed. All costs are variable. How is that possible? As Albert Einstein might say, it depends on the reference of time.
Transition to Dynamic Pricing
A step-by-step approach to intelligent rate design.
With the advent of the smart grid, state commissions throughout North America are showing increasing interest in dynamic pricing as a means of enhancing economic efficiency by reducing the need for expensive peaking capacity. But several barriers stand in the way of its rapid deployment.
As noted by MIT’s Paul Joskow in a recent discussion of the economics of climate change, “On the demand side there are relatively low-cost ways to reduce electricity consumption by increasing energy efficiency in building, lighting, heating, ventilating, air conditioning and other equipment. That’s why getting the retail price signals right is important and why muting them with regulation based on traditional cost- of-service models is inconsistent with promoting adoption of economical energy efficiency opportunities.” 1
While the rate-design process (in conjunction with the revenue-requirements process) in principle results in utility recovery of all prudent costs, it doesn’t provide sufficient incentives to utilities to pursue energy efficiency and demand-response programs at a level commensurate with state and federal goals. A review of default rate designs across the continent reveals that prices paid by customers do not reflect the scarcity of capacity to produce energy at various times of day.
In fact, default rates embody a hedging or risk premium that insulates customers from price volatility and eliminates any incentive they otherwise would have for moving to dynamic-pricing tariffs. Additionally, customers lack the information to become smart shoppers. Policymakers have accepted a viewpoint espoused by defenders of the status quo that customers are averse to being placed on dynamic-pricing tariffs, since not only will they face price volatility but they also might pay higher bills. This is contradicted by evidence from 15 recent pilot programs on dynamic pricing, which clearly showed that once customers experienced a dynamic tariff, not only did they understand and respond to the price signals, they also overwhelmingly preferred dynamic tariffs to their conventional hedged rate form. 2 The experiments also showed that a well-thought out customer education program is needed to sustain customer response.
In order to make a transition to dynamic pricing, a new framework is needed to develop innovative rate designs.
A New Framework
The fundamental premise is that that rate design should be driven by clearly articulated and feasible policy objectives.
For example, one rate structure might be designed to achieve simplicity in the important task of conveying the price of electricity to customers. Long, complicated bills over laden with fine print and impenetrable prose create a problem. A rate design that achieves this objective could be simply a flat volumetric charge (see Figure 1) . Under this rate, a customer with 1,000 kWh of consumption per month would have a monthly bill of $190. The customer’s bill is calculated as follows: 1,000