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README.md
dataViz_AtlanFlex.ipynb
README.md

Welcome to the AtlanFlex, a synthetic dataset for smart-thermostat demand-response !

To help researchers evaluating flexiblity at district scale, we provide various synthetic datasets. These data was generated by an urban building energy model coupled to an occupant behaviour model. These data can be used to test forecasting methods, to evaluate the influence of diversity, or any other use!

Short description of the case-study:

  • type of demand-reponse: activation via a "smart" thermostat (set-point decrease during a few hours)
    • 1/ daily activations (-2°C during 3 hours)
    • 2/ activations over the year depending on a price signal (peak hours of red days & peak hours of white days)
  • costal climate (La Rochelle, FR), winter period 2017
  • 337 dwellings in 97 buildings, 2 typologies simulated:
    • 1/ BR 2012
    • 2/ BR 1980
  • 2.22 occupants/dwellings

Data available: time series for each dwelling, one year data at a 10-min time-step

  • Characteristics of each dwelling: "infosThZone.csv"
  • Space heating need [W_th]: "conso.csv"
  • Space heating consumption (electrical) [W_el]: "heatPump.csv"
  • Equipement consumption [W_el]: "consoEquip.csv"
  • Operative temperature [°C]: "operativeTemp.csv"
  • External conditions (temperature, direct & diffuse solar radiation) [°C, W/m2]: "outdoorTemp.csv"
  • SP change [°C]: "setPointChange.csv"

Overview of the model

  • bottom-up model
  • stochastic behaviour model
  • agent-based flexibility, 3 models tested:
    • 1/ high probability of set-point adjustment (3.5%)
    • 2/ medium probability of set-point adjustment (1.75%)
    • 3/ no adjustment

Preview

As an example, the model is here used to evaluate the influence of occupant behviour (opt-out option) on flexiblity:

  • Figure 1: occupants cannot interract with the thermostat during DR event

  • Figure 2: occupants can interract with the thermostat during DR event

Figure 1:

Figure 2:

Release history

  • v0 : 27/07/2022

License

Licensed by La Rochelle University/LaSIE under a BSD 3 license (https://opensource.org/licenses/BSD-3-Clause).

References

Martinez, S., Vellei, M., & Le Dréau, J. (2021). Demand-side flexibility in a residential district: what are the main sources of uncertainty? Energy and Buildings, 111595. https://doi.org/10.1016/j.enbuild.2021.111595

... if you want to go further into the occupant model: Vellei, M., Martinez, S., & Le Dréau, J. (2021). Agent-based stochastic model of thermostat adjustments: A demand response application. Energy and Buildings, 238, 110846. https://doi.org/10.1016/j.enbuild.2021.110846