FLEX-Behavior

What It Does

FLEX-Behavior generates stochastic, behavior-derived energy demand profiles for residential households. Instead of using fixed load profiles, it simulates how occupants spend their time throughout the day and translates those activities into appliance electricity demand, hot water demand, and occupancy patterns.

The model runs in two stages:

Person-level simulation (gen_person_profiles): For each person type (defined by household role and teleworking status), the model generates multiple sample activity trajectories at 10-minute resolution using a Markov chain. Each trajectory encodes: what activity the person is doing, which technology/appliance they are using, their location (home/away), and the resulting electricity and hot water demand.
Household-level aggregation (gen_household_profiles): For each household type, persons are assembled into a household, their profiles are aggregated, and base loads (lighting, always-on appliances) are added. The result is an hourly time series of appliance electricity demand, hot water demand, and occupancy — ready for use by FLEX-Operation.

The Markov Chain Approach

Activity transitions are modeled as a first-order Markov chain: the probability of switching from one activity to another at each 10-minute step is derived from a Time Use Survey (TUS) — a large-scale diary dataset in which respondents record their activities throughout the day. FLEX preprocesses TUS data (see src/models/behavior/tus_process/) to extract transition probabilities stratified by person type, day type (weekday/weekend), and time of day.

This means the output profiles are stochastic: each model run (with a different random seed) produces a different but statistically consistent trajectory. The default configuration generates 5 sample trajectories per person type and 1 sample household per household type.

Inputs

Table	Content
`BehaviorScenario_Household`	Household type definitions (which person types compose each household)
`BehaviorScenario_Person`	Person type definitions (role, teleworking type)
`BehaviorParam_Activity_*`	Markov transition probabilities, duration distributions from TUS
`BehaviorParam_Technology_*`	Appliance power and usage duration per activity
`BehaviorID_*`	Lookup tables for activity, person type, location, technology IDs

Outputs

Table	Resolution	Key columns
`BehaviorResult_PersonProfiles`	10-minute, 8 per day × 365 = 52,560 rows	`activity_{type}_{sample}`, `technology_`, `appliance_electricity_`, `hot_water_`, `location_`
`BehaviorResult_HouseholdProfiles`	Hourly, 8,760 rows	`appliance_electricity_{ht}_{sample}`, `hot_water_`, `occupancy_`

The household profiles table is the primary handoff to FLEX-Operation, linked via OperationScenario_BehaviorProfile.

Key Code Locations

File	Role
`src/models/behavior/main.py`	Entry point — `gen_person_profiles()` and `gen_household_profiles()`
`src/models/behavior/person.py`	Markov chain simulation at the individual level
`src/models/behavior/household.py`	Member aggregation, lighting and base load addition
`src/models/behavior/scenario.py`	Loads TUS parameters and person profiles into memory
`src/models/behavior/tus_process/`	Offline preprocessing of raw TUS data into transition probability tables

How to Run

python -m projects.test_behavior.main

Output is written to projects/test_behavior/output/.