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*Self-Dispatch* of Demand Response by an Energy User, based on Time-of-Use pricing

Thumbnail 15 - Time-of-Use

Energy Users who participate in this category trigger their Demand Response themselves in response to a form of time-sensitive pricing signal – that of time-of-use pricing.

It’s labelled “Not Dispatchable” in the NERC diagram because it is not dispatched by a 3rd party, but instead by the Energy User themselves.  That’s different than these other”Dispatchable” methods, where the curtailment is triggered (dispatched) by a 3rd party – the AEMO, or some other party.

Both categories are Demand Response – they are just different types.


Time of use pricing are broad buckets of pricing, which are static, and set in advance.  In its simplest form, this might be a combination of some “Peak” pricing along with “Off-Peak” pricing – which is intended to incentivise the Energy User to time-shift what consumption they can from Peak times (however they are defined) into Off-Peak times.

By moving their consumption to “off-peak” times (even if the overall consumption remains the same) the energy user should see a lower cost of energy as a result.

Time-of-Use tariffs are broad-brushed policies that are widely used in the electricity supply industry.  Historically they have proved to have some effectiveness.  They have also proved very durable over time, as the overall time-of-day pattern of demand has changed relatively little over decades.

One of the challenges with energy transition we’re working through is that the underlying patterns of pricing and demand we’re seeing emerge are becoming significantly different than have been the case in the past (e.g. a lower midday demand due to the solar “duck curve”).  As a result of this, it is reasonable to assume that the design of Time-of-Use tariffs will need to change.

A salient question is whether the pace of evolution of the energy transition will prove troublesome for the effectiveness of TOU tariffs (i.e. by requiring the form of the tariff to be revised too frequently for beneficial Energy User habits and patterns to evolve).  This challenge might see more Energy Users progress towards more Real-Time Pricing.



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