Enumeration Feature

ConstraintBasedAdjustment (CON)

ESAs which support the Constraint-Based Adjustment feature allow an EMS to inform the ESA of periods during which power usage should be modified (for example when the EMS has been made aware that the grid supplier has requested reduced energy usage due to overall peak grid demand) and may cause the ESA to modify the intended power profile has previously suggested it would use.

EVSE example: An EVSE scheduling system may have determined that the vehicle would be charged starting at a moderate rate at 1am, so that it has enough charge by the time it is needed later that morning.

However, the DSR service provider has informed the EMS that due to high forecast winds it is now forecast that there will be very cheap energy available from wind generation between 2am and 3am.

The EMS first requests the Forecast data from each of its registered ESAs. It determines that the

EVSE has a power profile suggesting it plans to start charging the vehicle at 1am.

The EMS can then try to reduce the cost of charging the EV by informing the EVSE of the desire to increase the charging between scheduled times.

It does this by sending a RequestConstraintBasedForecast to the EVSE and asks it to run at a higher NominalPower consumption during the constraint period, which may require it to decrease its charge rate outside the constraint period to achieve its required energy demand.

ForecastAdjustment (FA)

ESAs which support the Forecast adjustment feature, allow an EMS to recommend a change to the start, duration and/or power level limits of the steps of the power profile that the ESA has previously suggested it would use.

Heat pump and Solar PV example: A heat pump may have the ability to heat hot water as well as heating the home. The heat pump scheduling system may have determined that the home will be unoccupied during the day, or that the indoor temperature is above the set-point and so it knows that it will not need to heat the home.

However, the hot water tank is likely to need to be reheated before the homeowner comes home in the evening. The heat pump is not aware that the property also has a solar PV inverter which is also an ESA that is communicating with the EMS.

The EMS first requests the Forecast data from each of its registered ESAs. It determines that the heat pump has a power profile suggesting it needs to heat hot water around 6pm. The solar PV inverter has forecast that it will generate 3.6kW of power during the middle of the day and into the afternoon before the sun goes down.

The EMS can then optimize the home considering other non-ESA loads and can ask the heat pump to heat the hot water around 3pm when it has forecast that excess solar power will be available.

It does this by sending a ModifyForecastRequest to the heat pump and asks the heat pump to expect to run at a lower power consumption (within the solar excess power) which requires the heat pump to run for a longer duration to achieve its required energy demand.

Pausable (PAU)

ESAs which support the Pausable feature, allow an EMS to recommend a pause in the middle of a forecast power profile that the ESA is currently using.

Washing machine example: A Washing Machine is in operation, and starting its water heating step.

However, the EMS becomes aware from the smart meter that the total home load on the grid is close to exceeding its allowed total grid load.

The EMS first requests the Forecast data from each of its registered ESAs. It determines that the washing machine has a power profile suggesting its current step in the wash cycle is using power to heat the water, but that this step can be paused.

The EMS can then reduce the grid load by asking the washing machine to pause the wash cycle for a short duration.

It does this by sending a PauseRequest to the washing machine to request pausing the current step of the forecast power usage for a period to allow other home loads to finish before resuming the washing cycle.

PowerAdjustment (PA)

For Energy Smart Appliances (ESA) the definition of being 'smart' mandates that they can report their current power adjustment capability and have an EMS request a temporary adjustment. This may typically be to curtail power requirements during peak periods, but can also be used to turn on an ESA if there is excess renewable or local generation (Solar PV).

For example, a home may have solar PV which often produces more power than the home requires,

resulting in the excess power flowing into the grid. This excess power naturally fluctuates when clouds pass overhead and other loads in the home are switched on and off.

EVSE Example: An EMS may therefore be able to turn on the EVSE (if the vehicle is plugged in) and can start charging the vehicle, and periodically modify the charging power depending on PV generation and other home loads, so as to minimize import and export to the grid.

PowerForecastReporting (PFR)

For Energy Smart Appliances (ESA) the definition of being 'smart' implies that they can report their indicative forecast power demands or generation, to a greater or lesser extent. For some ESAs this is highly predictable (in terms of both power and time), in other appliances this is more challenging and only a basic level of forecast is possible.

Forecasts are defined from a current time, using a slot format, where the slot is akin to a relatively constant operating mode.

Washing machine example: a washing machine may have stages of a washing cycle: heating, tumbling, rinse and spin stages. At each stage, the approximate minimum and maximum power consumption may be known, as well as the duration of that stage.

In some circumstances the ESA may allow the stage to be delayed or paused (subject to safety and manufacturer’s discretion and user preferences).

Typically, appliances with a heating element cannot have their power consumption adjusted and can only be paused or delayed.

Some ESAs may not be flexible other than a delayed cycle start (for example, once the washing cycle has been started then they run continuously until the cycle completes).

Appliances that only support the PowerForecastReporting and not any of the adjustment features may indicate that they are not flexible in the forecast slot format.

The PowerForecastReporting and the adjustment features aim to align to the [SAREF4ENER] ontology.

Inverter driven ESAs: some inverter driven ESAs can consume or generate a variable amount of power.

For example, a single phase EVSE can be adjusted in the range of 6-32Amps in 0.6 Amp steps in EU or on a hardwired 120V supply in the range of 6-15 Amps in US.

For example, a home battery may be adjusted to charge or discharge in steps of 1W.

For example, a heat pump may be able to modulate its compressor inverter between 20-100% of its rated power.

The ESA indicates its power adjustment range and its nominal power consumption as part of its Forecast.

StartTimeAdjustment (STA)

ESAs which support the Start Time Adjustment feature, allow an EMS to recommend a change to the start time of the energy transfer that the ESA has previously suggested it would use.

Washing machine example: A Washing Machine may have been set to start a wash cycle at 9pm when the variable tariff normally reduces.

However, the EMS is aware that a grid event has occurred, making it cheaper to run the cycle at a later time, but the washing machine is not aware of this.

The EMS first requests the Forecast data from each of its registered ESAs. It determines that the washing machine has a power profile suggesting it will start the wash cycle at 9pm, but the EMS now knows that the grid event means it will be cheaper to delay the start until 11pm.

The EMS can then optimize the cost by asking the washing machine to delay starting the wash cycle until 11pm.

It does this by sending a StartTimeAdjustRequest to the washing machine to request delaying the start of the washing cycle.

StateForecastReporting (SFR)

Some ESAs do not know their actual power consumption, but do know the state of operation. Like the PowerForecastingReporting feature, this uses the same slot structure mechanism to indicate a change in state vs time.

An external observing EMS may have access to real-time meter readings, and could learn the typical power consumption based on the advertised internal state of the ESA.

To enable this capability, the ESA shall report its internal operational state using an manufacturer specific value.

Once the EMS has built a model of the state vs observed power consumption, it may request a forecast adjustment for particular times of the day, encouraging the ESA to use power at alternative times.