Residential End Uses

A general purpose end use object is provided that incorporate a simple translation of a schedule to a loadshape to an end use load. The end use is linked to a circuit (which may be either line-to-line or line-to-neutral).

The residential_enduse class is defined as:

class residential_enduse {
       loadshape shape;
       complex demand[kVA]; // the peak power consumption since the last meter reading
       complex energy[kVAh]; // the total energy consumed since the last meter reading
       complex total_power[kVA]; // the total power consumption of the load
       double heatgain[Btu/h]; // the heat transferred from the end use to the parent
       double heatgain_fraction; // the fraction of the heat that goes to the parent
       double current_fraction; // the fraction of total power that is constant current
       double impedance_fraction; // the fraction of total power that is constant impedance
       double power_fraction; // the fraction of the total power that is constant power
       double power_factor; // the power factor of the load
       complex constant_power[kVA]; // the constant power portion of the total load
       complex constant_current[kVA]; // the constant current portion of the total load
       complex constant_admittance[kVA]; // the constant admittance portion of the total load
       double voltage_factor[pu]; // the voltage change factor
       set {IS220=1} configuration; // the load configuration options
       enumeration {OFF=-1, NORMAL=0, ON=1} override;
       enumeration {ON=1, OFF=0, UNKNOWN=-1} power_state;
       complex total[kVA]; // (DEPRECATED) the constant power portion of the total load
       complex power[kVA]; // (DEPRECATED) the constant power portion of the total load
       complex current[kVA]; // (DEPRECATED) the constant current portion of the total load
       complex admittance[kVA]; // (DEPRECATED) the constant admittance portion of the total load
}

The various end use appliances within the residential module have a common end use member. The four component values of this structure are published consistently by the house as the end use load name (e.g., lights , plugs) The individual properties should be used for internal reference for a given appliance and aggregated to the "enduse_load" property, which may be used for load calculations by the house or by other objects.

The central importance of the end use structure is that these four principle properties (power, demand, energy, and heatgain) must be updated by the object using a call to gl_sync_enduse so that when the end use is attached to a house circuit panel the load accumulate correctly. If the properties are not published and updated, the house will halt the simulator.

The override property is implemented on a case-by-case between objects, and is meant to provide a mechanism for other objects to force a residential end use to immediately activate or deactivate. The house, for example, will ignore its previous state and either immediately start heating or cooling, or immediately stop heating or cooling, based on if the house could be in such a state. For example, too-cold houses will not stop heating or start cooling, no matter the signal.

The power_state property is meant to indicate to other devices whether the end use is currently drawing power or not. This is primarily used by the market module.

Implicit end uses

A number of end uses can be implicitly defined by listing them in the residential module's global parameter implicit_enduses. If the parameter is not specified in the module directive, all implicit end uses are activated as shown in Table 1. Implicit end uses that may be specified are:

 module residential {
   implicit_enduses LIGHTS|CLOTHESWASHER|WATERHEATER|REFRIGERATOR|DRYER|FREEZER|DISHWASHER;
 }

but others are expected any time, so please consult the --modhelp residential output for what is currently supported.

Table 1: Implicit end uses

End use	Type	Schedule	Parameters
Lights	analog	residential-lights-default	power: 760 W
Plugs	analog	residential-plugs-default	power: 360 W
Clotheswasher	pulsed	residential-clotheswasher-default	energy: 750 Wh count: 0.25 power: 1 kW stdev: 150 W
Waterheater	frequency modulated	residential-waterheater-default	energy: 1 kWh count: 1 power: 5 kW stdev: 500 W
Refrigerator	frequency modulated	residential-refrigerator-default	energy: 1 kWh count: 25 power: 750 W stdev: 100 W
Dryer	pulsed	residential-dryer-default	energy: 2.5 kWh count: 0.25 power: 5 kW stdev: 0.5 kW
Freezer	frequency modulated	residential-freezer-default	energy: 750 Wh count: 25 power: 500 W stdev: 50 W
Dishwasher	pulsed	residential-dishwasher-default	energy: 1.0 kWh power: 1.0 kW count: 1.0 stdev: 150 W
Range	pulsed	residential-range-default	energy: 1.0 kWh power: 500 W count: 1.0 stdev: 95 W
Microwave	pulsed	residential-microwave-default	energy: 1.0 kWh power: 200 W count: 1.0 stdev: 40 W

Using the dishwasher model

Dishwashers are fairly complex to control. Many wash cycles are simply timed prescriptions for filling, washing, releasing soaps and softeners, and drying, but most washers have several cycles to choose from. Some cycles in some dishwashers include a water temperature booster, which can be fairly energy intensive.

Modeling Assumptions

• Energy consumption in dishwashers is split between motors and resistance heaters. Thus the power factor changes depending on whether the wash cycle includes water temperature boost and changes from one part of the cycle to another. At this point, however, power factor modeling is simplified to be a constant value, fixed by default at 0.95.
• The fraction of washer consumption that becomes heat in the space is arbitrarily estimated to be 50%. This presumes that half the heat generated by the motors and/or resistance heater is transferred to the water and flushed down the drain.
• Installed capacity (installed_power) is randomly selected between 1000W and 3000W .

Modeling Approach

Dishwashers are modeled as a simple stream of energy demand signals taken from a tape. That is,

The heat gains to the space are simply

Default dishwasher

Default here.

Dishwasher Properties

Properties here.

Dishwasher State of Development

Dishwasher is considered an experimental model, and may not function correctly at this time.

Using the evcharger model

Description here.

Default evcharger

Default here.

evcharger Properties

Properties here.

evcharger State of Development

evcharger is considered an experimental model, and while functionality exists, it is very limited.

Using the Freezer

The freezer is modeled by determining the thermal capacity of the hypothetical contents of the freezer and estimating the thermal gains of the freezer cavity through its insulation. Heat gain through intermittent door opening is not factored in at this point.

From a simulation view, the freezer gradually absorbs heat from the house, and will activate its cooling system motor when the temperature exceeds a certain point.

Default Freezer

A default freezer will be defined with

object freezer {
}

will be initialized with the values of

object freezer {
   size random.uniform(20,40);
   thermostat_deadband random.uniform(2,3);
   setpoint random.uniform(10,20);
   UA 6.5;
   power_factor 0.95;
   rated_capacity (size * 34.0);
}

Table 2: Freezer Properties

Property Name	Type	Unit	Default Value	Description
size	double	cu ft	20 - 40 cu ft	Storage volume of the freezer
rated_capacity	double	BTU / hr	10 BTU/h per cu ft	Cooling capacity of the freezer under optimum conditions.
power_factor	double	ratio	0.95	...
temperature	double	degF	10.0 - setpoint	Read-only. Air temperature inside the freezer.
setpoint	double	degF	10.0 - 20.0	The temperature the thermostat is set at to stay colder than
deadband	double	degF	2.0 - 3.0	The 'slack' in the thermostat, and the temperature to cool the freezer by when the thermostat starts the cooling cycle.
next_time	timestamp	sec	-	The next time that the internal state of the freezer will change due to thermal conditions.
output	double	???	-	Read-only. Heat rate from the cooling system.
UA	double	BTU*hr/degF	6.5	The relative heat loss of the freezer across the surface of its housing. Smaller values indicate better insulation.
state	enumeration	OFF, ON	OFF	Read-only. Current state of the freezer cooling motor.
enduse_load	complex	kW	-	Read-only. Current power consumption by the freezer.
constant_power	complex	kW	-	Read-only. Constant power part of the current power draw.
constant_current	complex	A	-	Read-only. Constant current part of the current power draw.
constant_admittance	complex	1/Ohm	-	Read-only. Constant resistance part of the current power draw.
internal_gains	double	kW	-	Read-only. The heat created and released into the air by this appliance.
energy_meter	double	kWh	-	The energy consumed during the running life of the appliance.

Freezer State of Development

Freezer is considered an experimental model, and may not function correctly at this time.

Using the lights model

Description here.

Default lights

Default here.

lights Properties

Properties here.

Lights State of Development

Lights is considered a simple, stable model.

Using the microwave model

In their simplest mode of operation (full power), microwave ovens consume an essentially constant power. Other modes, such as defrost or partial-power, typically consume the same power in cycled on-off bursts. Microwaves are typically rated at 750 to 1100 Watts and operate at an efficiency in the neighborhood of 65%, meaning that 65% of the energy consumed goes toward heating food and the rest is released as heat to the surroundings. However the heat released to the surroundings is complicated. Although roughly 35% of consumed energy goes immediately to the house as heat, the 65% that warms the food is arguably released eventually as heat, either as the food cools on the table or as it is released as body heat from the humans who ate it.

Modeling Assumptions

• Power factor is assumed to be fixed at 0.95.
• Because microwaves have efficiencies in the range of 65%, approximately 35% of their consumption goes immediately to the space as heat. Because body heat from occupants is theoretically accounted for separately, the microwave model assumes none of the remaining energy consumption becomes heat in the space .
• Installed capacity (installed_power) is randomly selected between 700 W and 2000 W.

Modeling Approach

The microwave model retrieves its demand from a tape as a simple stream of values between 0 and 1 (representing the fraction of time the power is on). Ordinarily, the values will be either 0 or 1 since most microwaves control cooking by cycling. The demand is adjusted (scaled) by an “installed_power” value associated with each microwave (W). That is,

The heat gains to the space are simply

Default microwave

Default here.

microwave Properties

Properties here.

Microwave State of Development

Microwave is considered an experimental model, and may not function correctly at this time.

Using the occupantload model

Description here.

Default occupantload

Default here.

occupantload Properties

Properties here.

occupantload State of Development

occupantload is considered an experimental model, and while most of the functionality should exist, it has not been thoroughly tested.

Using the plugload model

Description here.

Default plugload

Default here.

plugload Properties

Properties here.

Plugload State of Development

Plugload is considered a simple, stable model.

Using the range model

Electric ranges are essentially perfectly resistive loads. Each “burner” on a range top may be controlled by cycling the power on and off or by a “triac” device that regulates the on time at very high frequency. The user may reset the knob setting multiple times during a cooking event. Thus, range loads vary with the number of active burners, the user-controlled knob settings, and possibly the cycling behavior.

The GridLAB-D™ range model greatly simplified. It works in a manner essentially identical to the way plug loads are modeled—a demand (0 to 1) is read from a tape and multiplied by a range object-specific capacity (installed_power).

Modeling Assumptions

• Power factor is assumed to be fixed at 0.95.
• 100% of the range’s energy consumption is assumed to enter the house as heat (ignoring the heat that goes into the food).
• Installed capacity (installed_power) is randomly selected between 2500 W and 4500 W.

Modeling Approach

The range model retrieves its demand from a tape as a simple stream of values between 0 and 1 (representing the fraction of time the power is on). The demand is adjusted (scaled) by an “installed_power” value associated with each microwave (W). That is,

The heat gains to the space are simply

Default range

Default here.

range Properties

Properties here.

Range State of Development

Range is considered an experimental model, and may not function correctly at this time.

Using the Refrigerator

The thermal and the electric loads on a refrigerator can be estimated using simplified first principles models. In this approach, the thermal load (primarily heat gain from ambient) is modeled as function of few lumped parameters (effective shell conductance, effective thermal mass, and compressor efficiency), ambient condition, internal gains adding and removing food material, and thermostat setting. Once the thermal load is estimated the power consumption of the compressor and the fan can be calculated. Although this approach is not as detailed and accurate as the detailed physical model, it does provide reasonably accurate estimates of the energy consumption.

Load Calculation

The major heat gains that contribute to the refrigerator thermal load are:

1. Conduction through refrigerator/freezer walls.
2. Heat gain from infiltration of ambient air when the refrigerator/freezer door is opened.
3. Heat gains from additions of food to the refrigerator/freezer.

In general, the amount of heat that must be removed (cooling load) is not always equal to the amount of heat received at a given time. The difference is a result of the heat storage and time lag effects. Only a portion of the heat entering refrigerator actually cools the air inside the refrigerator immediately; the rest cools the mass – the food material. The heat that is stored in the mass will result in thermal load at a later time. So, the modeling approach will have to account for the storage effect.

Modeling Assumptions

• Power factor is assumed to be fixed at 0.95.
• The thermal conductance of refrigerator and freezer compartments are assumed to be random normal in the range of 0.9 to 1.1 Btu/h.f 2.°F
• The refrigerator compartment set point is assumed to be between 35 and 39°F.

Modeling Approach

The refrigerator model is currently implemented in its simplest form to calculate the time to change of state based on the current indoor temperature, refrigerator interior temperature, thermal properties of the casing, and food content and water content of the refrigerator compartment. The original ODE relating these properties is

where

• \(T_{air}\) is the temperature of the air
• \(T_{out}\) is the ambient airtemperature around the refrigerator
• \(UA_r\) is the UA of the refrigerator itself
• \(UA_f\) is the UA of the food-air
• \(C_f\) is the heat capacity of the food
• \(Q_r\) is the heat rate from the cooling system

The general solution is:

where

• \(t\) is the elapsed time
• \(T_0\) is the initial temperature
• \(T_t\) is the temperature at time \(t\)
• \(C_1 = C_f / ( UA_r + UA_f )\)
• \(C_2 = T_{out} + Q_r / UA_f\)

The time solution is:

During each synchronization cycle, the refrigerator model calculates the internal gain based on the rated capacity of the refrigerator and returns the time solution for determining the next synchronization time.

Default Refrigerator

Refrigerator Properties

See Freezer Properties

Refrigerator State of Development

Refrigerator is considered an experimental model, and may not function correctly at this time.

Using the washer model

Description here.

Default washer

Default here.

washer Properties

Properties here.

Washer State of Development

Washer is considered an experimental model, and may not function correctly at this time.

Internal Gains

Each house modeled in GridLAB-D™ has two primary sources of internally generated heat. First, is the “waste” heat given off by other devices in the house that are modeled by GridLAB-D™. For example, a refrigerator located inside the house is modeled primarily for its thermal behavior regarding cooling and freezing food, with its primary output being the impact (energy and peak) on the grid. However, the refrigerator also gives off heat that must be accounted for in the simulation of the house itself. Second, there are devices in the home that are not explicitly modeled by GridLAB-D™, but that have sufficient aggregate impact that their heat contribution to the house and their aggregate impact on the home’s electricity must be accounted for. Examples are TV sets, vacuum cleaners, hand-held hair dryers, and other miscellaneous equipment generally plugged into wall outlets.

Modeling Assumptions

• All “plug loads” are assumed to be consolidated into a single load. Thus, they are all either on one side of the home’s circuit split or evenly distributed between the two sides; this is determined randomly at object creation.
• The installed capacity of plug loads is randomly selected at a value between 700 and 2000 Watts.
• The fraction of plug load consumption that ends up as heat in the house is fixed at 90%.
• The power factor of the aggregate plug loads is fixed at 0.95.

Modeling Approach

The internal gains reported by modeled devices are simply collected and summed at the house level, the house object being unaware of any details other than the consumption, circuit, and power factor reported by each device.

Other internal gains (aka plug loads) are modeled as a simple, fixed capacity (installed_power) that is multiplied at each time step by a demand fraction (p.u.) read from a tape.

References

Pita, G. Eward. 2002. Air-Conditioning Principles and Systems. Prentice Hall, Upper Saddle River, New Jersey, 07458.

Pratt, R.G. and Z.T. Taylor, 1994. "Development and Testing of an Equivalent Thermal Parameter Model of Commercial Buildings from Time-Series end use Data," Pacific Northwest Laboratory, Richland, Washington.

Pratt, R.G., et al., 1990. "Significant ELCAP Analysis Results: Summary Report," PNL-6659, Pacific Northwest National Laboratory, Richland, Washington.

Sonderegger, R., 1978, "Dynamic Models of House Heating Based on Equivalent Thermal Parameters," Report PU/CES 57, Doctoral dissertation, Princeton University, Princeton, New Jersey.

Subbarao, K., 1981, "Thermal Parameters for Single and Multizone Buildings and Their Determination from Performance Data," Solar Energy Research Institute, Golden, Colorado.

Wilson, N.W., B.S. Wagner and W.G. Colborne, 1985, "Equivalent Thermal Parameters for an Occupied Gas-Heated House," ASHRAE Transactions, vol. 91, part 2.