Ryan Hledik

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.

The Power of Dynamic Pricing

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.

Will Smart Prices Induce Smart Charging of Electric Vehicles

The societal and environmental benefits of plug-in electric vehicles (PEVs) have been well documented. However, the near-term impact of PEVs on the distribution grid has yet to be fully explored. Whether PEVs will help or hinder electricity provision will depend on how customers charge their vehicles, which will be driven in part by the rate structures that are offered by utilities and the associated customer response. In this discussion paper, we explore the relationship between PEV charging behavior and varying time-of-use rates, and offer suggestions for conducting a well-designed pricing experiment that will determine whether varying rates will help reduce future grid reliability problems as PEVs penetrate the vehicle market.

The Emergence of Organic Conservation

Recent improvements in electric efficiency have been driven in part by demand-side management programs and state and federal codes and standards for electric efficiency. However, some of these improvements have happened naturally, a process we call ‘organic conservation.’ This article surveys expert opinion on organic conservation and estimates the likely impact that organic conservation has had on energy consumption for three specific end uses.