Ahmad Faruqui

The impact of informational feedback on energy consumption—A survey of the experimental evidence

In theory, In-Home Displays (IHDs) can revolutionize the way utilities communicate information to customers because they can induce changes in customer behavior even when they are not accompanied by a change in electric prices or rebates for purchasing efficient equipment. IHDs provide consumers with direct feedback—real-time information on energy consumption and costs—and turn a once opaque and static electric bill into a transparent, dynamic, and controllable process. However, to what extent do consumers actually respond to the direct feedback provided by IHDs?

Unlocking the €53 Billion Savings from Smart Meters in the EU - How Increasing the Adoption of Dynamic Tariffs Could Make or Break the EU’s Smart Grid Investment

We estimate the cost of installing smart meters in the EU to be [euro]51 billion, and that operational savings will be worth between [euro]26 and 41 billion, leaving a gap of [euro]10-25 billion between benefits and costs. Smart meters can fill this gap because they enable the provision of dynamic pricing, which reduces peak demand and lowers the need for building and running expensive peaking power plants. The present value of savings in peaking infrastructure could be as high as [euro]67 billion for the EU if policy-makers can overcome barriers to consumers adopting dynamic tariffs, but only [euro]14 billion otherwise. We outline a number of ways to increase the adoption of dynamic tariffs.

Household Response to Dynamic Pricing of Electricity - A Survey of the Empirical Evidence

Since the energy crisis of 2000-2001 in the western United States, much attention has been given to boosting demand response in electricity markets. One of the best ways to let that happen is to pass through wholesale energy costs to retail customers. This can be accomplished by letting retail prices vary dynamically, either entirely or partly. For the overwhelming majority of customers, that requires a changeout of the metering infrastructure, which may cost as much as

The Value of Dynamic Pricing in Mass Markets

40 billion for the US as a whole. While a good portion of this investment can be covered by savings in distribution system costs, about 40 percent may remain uncovered. This investment gap could be covered by reductions in power generation costs that could be brought about through demand response. Thus, state regulators in many states are investigating whether customers will respond to the higher prices by lowering demand and if so, by how much. To help inform this assessment, we survey the evidence from the 15 most recent pilots, experiments and full-scale implementations of dynamic pricing of electricity. We find conclusive evidence that households (residential customers) respond to higher prices by lowering usage. The magnitude of price response depends on several factors, such as the magnitude of the price increase, the presence of central air conditioning and the availability of enabling technologies such as two-way programmable communicating thermostats and always-on gateway systems that allow multiple end-uses to be controlled remotely. They also vary with the design of the studies, the tools used to analyze the data and the geography of the assessment. Across the range of experiments studied, time-of-use rates induce a drop in peak demand that ranges between three to six percent and critical-peak pricing tariffs induce a drop in peak demand that ranges between 13 to 20 percent. When accompanied with enabling technologies, the latter set of tariffs lead to a drop in peak demand in the 27 to 44 percent range.

The Power of Dynamic Pricing

Abstract The simpler forms of dynamic pricing, in which prices vary only during extreme supply conditions, may capture many of the economic benefits of real-time pricing, and may be suitable for wide-scale deployment to mass-market consumers, for whom dynamic pricing options have largely been ignored.

Mitigating Price Spikes in Wholesale Markets through Market-Based Pricing in Retail Markets

As the Smart Grid takes shape, it opens new vistas for change. One of those salient opportunities for change that is enabled by the Smart Grid is the pricing of electricity. By and large, existing rate designs hide the temporal variation in the cost of electricity and thereby promote over-consumption of electricity during peak times and under-consumption during off-peak times. In much of North America, the problem is especially pronounced during the top 60-100 hours of the year which may account for as much as 10-18 percent of system peak load. In order to meet this critical peak load, expensive combustion turbines are purchased and installed, raising rates for all customers. Dynamic pricing rate designs can remedy this problem and enhance economic efficiency. For that reason, they are receiving increased attention by state commissions throughout the country. California has made a major commitment to it, by approving the deploying of advanced metering infrastructure (AMI) and by establishing critical-peak pricing (CPP) rates as the default tariff for all non-residential customer classes with AMI. Other smart rate designs, such as real-time pricing, may be provided as options. To show the power of dynamic pricing, we develop a set of illustrative rates using data from a generic California utility and compute the benefits that would accrue to the states economy from widespread deployment of these rates. While the numbers are specific to California, the process and methodology are perfectly general and should be of interest to utilities and regulatory bodies throughout North America. We develop dynamic pricing rates for four customer classes: Residential, Medium Commercial and Industrial (C&I), Large Commercial, and Large Industrial. In order to show the development of these rates, we begin with a discussion of existing rates. All the dynamic pricing rates are developed to be revenue neutral to these existing rates.

The residential demand for electricity by time-of-use: A survey of twelve experiments with peak load pricing☆

Abstract Introducing a modest number of spot-based products into the retail portfolio would provide significant price relief and stability by connecting the retail and wholesale markets in a cost-effective and market-based manner.

The Discovery of Price Responsiveness – A Survey of Experiments Involving Dynamic Pricing of Electricity

Information on customer response to time-of-use (TOU) rates plays a major part in utility resource planning, particularly in the design of cost-based rate structures and cost-effective load management programs. Several elasticity concepts have been used by economists to analyze customer response to TOU rates. We discuss the interrelationships between various concepts and show that total uncompensated price elasticities are the appropriate measure of customer response.

Arcturus: International Evidence on Dynamic Pricing

This paper surveys the results from 126 pricing experiments with dynamic pricing and time-of-use pricing of electricity. These experiments have been carried out across three continents at various times during the past decade. Data from 74 of these experiments are sufficiently complete to allow us to identify the relationship between the strength of the peak to off-peak price ratio and the associated reduction in peak demand or demand response. An “arc of price responsiveness” emerges from our analysis, showing that the amount of demand response rises with the price ratio but at a decreasing rate. We also find that about half of the variation in demand response can be explained by variations in the price ratio. This is a remarkable result, since the experiments vary in many other respects – climate, time period, the length of the peak period, the history of pricing innovation in each area, and the manner in which the dynamic pricing designs were marketed to customers. We also find that enabling technologies such as in-home displays, energy orbs and programmable and communicating thermostats boost the amount of demand response. The results of the paper support the case for widespread rollout of dynamic pricing and time-of-use pricing.

Dynamic Pricing of Electricity for Residential Customers: The Evidence from Michigan

This paper introduces Arcturus, an international database of dynamic pricing and time-of-use pricing studies. It contains the demand response impacts of 163 pricing treatments that were offered on an experimental or full-scale basis in 34 projects in seven countries located in four continents. The treatments included various types of dynamic pricing rates and simple time-of-use rates, some of which were offered with enabling technologies such as smart thermostats. The demand response impacts of these treatments vary widely, from 0% to more than 50%, and this discrepancy has led some observers to conclude that we still don’t know whether customers respond to dynamic pricing. We find that much of the discrepancy in the results goes away when demand response is expressed as a function of the peak to off-peak price ratio. We then observe that customers respond to rising prices by lowering their peak demand in a fairly consistency fashion across the studies. The response curve is nonlinear and is shaped in the form of an arc: as the price incentive to reduce peak use is raised, customers respond by lowering peak use, but at a decreasing rate. We also find that the use of enabling technologies boosts the amount of demand response. Overall, we find a significant amount of consistency in the experimental results, especially when the results are disaggregated into two categories of rates: time-of-use rates and dynamic pricing rates. This consistency evokes the consistency that was found in earlier analysis of time-of-use pricing studies that was carried out by EPRI in the early 1980s. Our analysis supports the case for the rollout of dynamic pricing wherever advanced metering infrastructure is in place.