Buildings.Occupants.Office.Occupancy

Package with models to simulate occupancy in office buildings

Information

This package contains models to simulate occupancy in office buildings.

Extends from Modelica.Icons.VariantsPackage (Icon for package containing variants).

Package Content

Name	Description
Wang2005Occupancy	A model to predict Occupancy of a single person office
Validation	Package with examples to validate models in Occupancy package

Buildings.Occupants.Office.Occupancy.Wang2005Occupancy

A model to predict Occupancy of a single person office

Buildings.Occupants.Office.Occupancy.Wang2005Occupancy

Information

Model predicting the occupancy of a single person office.

References

The model is documented in the paper "Wang, D., Federspiel, C.C. and Rubinstein, F., 2005. Modeling occupancy in single person offices. Energy and buildings, 37(2), pp.121-126."

The model parameters are regressed from a field study in California with 35 single person offices at a large office building from 12/29/1998 to 12/20/1999.

Extends from Modelica.Blocks.Icons.DiscreteBlock (Graphical layout of discrete block component icon).

Parameters

Type	Name	Default	Description
Time	one_mu	4368	Mean occupancy duration [s]
Time	zero_mu	2556	Mean vacancy duration [s]
Integer	seed	10	Seed for the random number generator

Connectors

Type	Name	Description
output BooleanOutput	occ	The State of occupancy, true for occupied

Modelica definition

model Wang2005Occupancy "A model to predict Occupancy of a single person office" extends Modelica.Blocks.Icons.DiscreteBlock; parameter Modelica.SIunits.Time one_mu(displayUnit="min") = 4368 "Mean occupancy duration"; parameter Modelica.SIunits.Time zero_mu(displayUnit="min") = 2556 "Mean vacancy duration"; parameter Integer seed = 10 "Seed for the random number generator"; Modelica.Blocks.Interfaces.BooleanOutput occ "The State of occupancy, true for occupied"; protected discrete Real mu; discrete Real tNext(start=0); discrete Real hold_time(start = 0); Real r(min=0, max=1) "Generated random number"; Integer state[Modelica.Math.Random.Generators.Xorshift1024star.nState]; initial equation tNext = 0; hold_time = 0; occ = true; state = Modelica.Math.Random.Generators.Xorshift1024star.initialState(seed, seed); r = 0; mu = 0; equation when time > pre(tNext) then (r, state) = Modelica.Math.Random.Generators.Xorshift1024star.random(pre(state)); occ = not pre(occ); mu = if occ then one_mu else zero_mu; hold_time = -mu * Modelica.Math.log(1 - r); tNext = time + hold_time; end when; end Wang2005Occupancy;