Automated demand response key to intermittent renewables


By 2020, many countries, states and regions expect to generate a certain percentage of their electricity from renewables, like wind and solar. In the European Union, this target is 20%, for example, while in the U.S. state of California, it is 33%.

While these goals are positive, if not exactly over-ambitious, storage solutions are currently costly and technology is still being developed, meaning intermittency issues are a very present challenge for the energy industry.

However, according to scientists at California’s Environmental Energy Technologies Division (EETD) of Lawrence Berkeley National Laboratory (Berkeley Lab), AutoDR – the infrastructure of which already exists – is an important element of the smart grid, since it can efficiently and economically reduce the chances of grid failure and help ease intermittency problems.

They say that automatically reducing the power demand of large commerical and industrial buildings to more closely match the demands of the grid is currently "more cost-effective" than grid-scale battery storage. "Deployed costs for fast automated demand response including installation, materials, labor and program management are about 10% of the deployed costs of grid scale battery storage," write the report’s authors.

Average demand response costs compared to various average grid scale

battery costs:

Grid scale battery technology

Demand response costs compared to various grid scale battery costs

DR cost* (US$/kW)

Battery cost** ($/kW)

DR/battery (% cost)

Lithium-ion – High power




Advanced lead acid




Lithium ion – high energy




Popular content

Vanadium redox battery




Zinc bromine




Sodium sulfur (NaS)




Zinc-air battery




Source: Fast Automated Demand Response to Enable the Integration of Renewable Resources

* Deployed cost, average (Wikler et al., 2009)

* Deployed costs, average(Seto 2010)

Furthermore, the scientists say their research – supported by the California Energy Commission’s Public Interest Energy Research program, California utilities, the Bonneville Power Administration, and the New York State Energy Research and Development Authority – has proven that AutoDR reduces peak power use during periods of high demand.

"In response, the California Public Utilities Commission mandated the use of AutoDR by California’s investor-owned electric utilities as a tool for managing the grid. Currently, there is more than 250 MW of AutoDR in California. Electric power authorities globally are also beginning to add AutoDR to their grid management toolkits," writes the Berkley Lab in an article summarizing the report.

Specifically, the EETD scientists have developed an internet based communications specification, OpenADR, which is said to be "one of the early Smart Grid standards" and which is already being used to implement AutoDR in practice.

However, while AutoDR presents a possible solution to intermittency, it is still not at the stage where it can completely resolve the issue. According to a study carried out in 2010, it was found that between 3 and 5 GW of load shedding would be would be required to meet California’s 2020 goals.

Based on the EETD scientists’ latest research, AutoDR deployed on a large-scale in California, and utilizing existing commercial and industrial facilities, could provide between 0.18 and 0.90 GW of load shedding. If the system was upgraded and expanded, they believe this could increase to 0.42 to 2.07 GW.

"Automated demand response has the potential to balance renewable intermittency in a cost-effective way," says EETD scientist and principal investigator of the research, Sila Kiliccote. "Combined with grid-scale energy storage and other methods, it could be an important element of a suite of tools to help operators manage the grid."

She adds, however, "We need to better understand what percentage of each of these types of load sheds is available to address intermittency throughout the year. Also needed is a quantitative economic analysis of the scale up of AutoDR as a grid resource integrated with renewable and energy storage."

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