Smart Devices That Schedule Electricity Use May Ease Blackout Risks
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- Nov 12, 2020 5:02 pm GMTNov 12, 2020 2:26 pm GMT
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A team of researchers writing in the journal Chaos say that demand side controls may be effective at stabilizing grids that use a mix of generation sources, including increasing amounts of intermittent renewable energy.
The authors say that with a growing fraction of electric energy generated from wind and solar power plants, fluctuations will increase making it necessary to consider a range of control approaches to balance the system. Devices that are smart enough to postpone certain tasks can help. (Read the article.)
To test the idea, the authors factored the effects of demand side management (DSM) into power grids using a model to simulate the rapid fluctuations involved and tested the system under different demand loads.
They also extended a model for the complex dynamics of blackouts to include three factors, which they say are key: intraday variability, power bursts caused by simultaneous switching on of many electric devices, and the effect of managing demand on the power grid.
Common DSM methods include smart devices that use two-way communication between a load serving entity (LSE) and the device. The LSE sends a price signal to the device; if the price is high, the device can postpone a task.
Devices that the authors say are well suited for this approach include heaters, boilers, dishwashers, washing machines, air conditioners, refrigerators, and chargeable devices, among other.
Another DSM methodology not requiring user intervention is Dynamic Demand Control (DDC). Here, the same kind of devices can postpone a task if grid frequency is outside of a given range. DDC does not require communications but, instead, relies on local measurements of the instantaneous frequency. The authors say that DDC can reduce small- and medium-size frequency fluctuations and improve the synchronization on the network.
One down side, however, is that the probability of large frequency fluctuations goes up as delayed tasks begin to be performed. The authors say that although this is rare, such events are linked with demand spikes that can trigger a blackout. The authors tested a modified DDC approach in which devices in a group communicated and coordinated opposite actions. This approach significantly reduced the number of pending tasks so that large frequency fluctuations could be suppressed.
The authors say plan to continue to investigate more advanced forms of demand control, such as communication between nodes. They are also exploring models that can assess the amount of solar and wind power that can be included in grids without increasing the risk of blackouts due to fluctuations.