Traditional energy utilities have coal, gas or oil burning power plants generating huge amounts of electricity, which they connect to the electric grid over long-distance wires to provide power to homes and businesses. Their goal is (roughly) to match the amount of electricity they are supplying to the grid to demand on it.
Power plants are still a fundemental part of the energy system. But more recently things like solar panels and wind turbines have been added to the mix. In addition to being greener than power plants, these tend to be much individually smaller - usually less than 10kW of energy, compared to thousands of times that for a traditional power plant. These small sources of power are called “Distributed Energy Resources”, or DERs.
This presents a new challenge for utilities: they don’t want to be managing thousands of tiny energy producing units, where previously they only had to worry about a few big plants.
The solution to this problem is to create a layer of abstraction between the utilities and the physical DERs. This model allows utilities to group several physical DERs together into a single, ‘virtual’ DER for management purposes, sort of like a virtual power plant, which the utility will deal with instead of having to worry about the details of the underlying resources.
Once you have this abstraction you can do some pretty interesting things. You can group different types of DER together into a single virtual DER, shaping its output profile. You can group geographically dispersed resources into a single resource. You can group a set of DERs owned by a single provider into a single virtual DER to act as an interface with that provider. You can group multiple virtual DERs together into a ‘second level’ of abstraction1 1 Interesting contrast/comparison with financial engineering here. .
Up to now we have considered DERs as things whose only purpose is to produce power (turbines, solar panels), and we have set up a system for being able to deal efficiently with a large volume of small DERs. This opens an interesting possibility: we can extend the definition of a DER to include anything that is connected to the grid to produce or store power. This can include those who are traditionally the grid consumers - businesses who have on-site generators or storage, individual homes which have solar panels or batteries (including batteries in EVs) installed.
Once these consumers are connected to the grid, you can take another step and consider that, if the goal of utilities is to balance demand and supply, then removing or rescheduling demand is entirely equivalent to increasing supply. You come to the conclusion that you can manage the grid by allowing those consumers you’ve connected to the grid to add back capacity by reducing or rescheduling their demand - A so called “Demand Response” DER.
For example, a factory turning off a machine it’s running reduces demand on the grid (generally called commercial and industrial/C&I demand response). Or an individual with an EV could reschedule when their car is going to charge to a time when there is excess grid capacity (a Residential DER).
So to summarize, our definition of a DER at this point is any small producer, storer or consumer of electricity that has been signed up to participate. The utility’s role is to manage the level of consumption or production from those DERs to maintain a balance of supply and demand.
What is needed is a system to manage this - a DERMS. A DERMS can be used both by the utility itself to manage the DERs it contracts with, or by the operators of the DERs themselves. For Demand Response DERs (such as an individual with a house), these can be programs which change the behaviour of energy controllers like thermostats, EV charging stations or batteries in response to the grid’s balance of supply and demand.