Researchers from Stanford University have published a paper based on a programme that explores how to model DER deployment in the most cost-effective manner.
The paper orginally published in Nature Magazine, describes the programme, "ReMatch" which leverages smart grid data to match groups of consumers with different kinds of distributed resources based on the customers' energy use and the ability to construct resources in that area eg. solar panels, batteries.
In a release, Ars Technica UK explains that, "if a business district uses a lot of power around mid-day, for example, it might be worthwhile to offer incentives for that area to install solar panels. If a row of restaurants is open until 9pm, perhaps offering those businesses a solar-plus-battery option would be more cost-effective."
It adds: "The modeling programme can also break down customer energy use by the hour. The software can, for example, pick out customers who use a lot of solar in the morning and customers who use a lot of solar in the afternoon. The utility can then use that information to balance the enrollment of each kind of customer, thereby evening out the demands on the grid."
The Stanford researchers applied ReMatch to a 10,000-customer sample in California, using real hourly data gleaned from smart meters. They found that
constructing DER infrastructure in a targeted way reduced the Levelized Cost of Electricity (in other words, the present value of the resource over its lifetime costs) by nearly 50%.
The paper concluded that through offering detailed data on intermittency, customer demand, and operating costs, utilities can take a targeted approach to
incentivising DER infrastructure, which will help them meet renewables goals and reduce costs associated with indiscriminate buildout.
“[O]ur results suggest that in order for DER infrastructure to become a reality we must design smart and targeted policies, programmes, and incentives that facilitate the balancing of consumer type enrollment in DER plans and programmes with the existing grid,” the researchers concluded.
“Under such smart policies, the optimal mix of consumers could be selected to become part of emerging utility models of organized ‘prosumer’ community groups to preserve the cost effectiveness of model-derived DER infrastructure plans.”