Dataset

CityLearn makes use of datasets that are a collection of data files. The data files are used to define the simulation environment as well as provide some observation values. See Data Files for more information.

Data Files

The data files refer to flat files containing time series data that are used to set observations that are agent action agnostic (i.e. observations that are not a function of the control actions). These files are referenced in the environment schema.json and read when citylearn.citylearn.CityLearnEnv is initialized. The data files are desrcribes as follows:

Building Data File

The building file is a csv file that contains a building’s temporal (calendar), end-use loads, occupancy, solar generation and indoor environment variables time series data. There are as many building files as buildings in the environment. The end-use loads, occupancy, solar generation and indoor environment data may come from simulation in energy modeling software e.g., EnergyPlus or from smart meter or from a Building Automation System (BAS). The file structure is shown in the snippet below:

Weather Data File

The weather file is a .csv file that contains outdoor weather variables time series for the desired simulation geographical location. It is used as the source for citylearn.building.Building.weather, which is the source for weather related observations. Typical Meteorological Year (TMY) or Actual Meteorological Year (AMY) data can be used. The file structure is shown in the snippet below:

Carbon Intensity Data File

The carbon intensity file is a .csv file that contains CO:sub:2 emission rate time series. It is used as the source for citylearn.building.Building.carbon_intensity, which is the source for the carbon_intensity observation. The data can be sourced from grid operators e.g. ERCOT, NYISO or third-party sources WattTime. The file structure is shown in the snippet below:

Pricing Data File

The carbon intensity file is a .csv file that contains current time-step and forecasted electricity price time series. It is used as the source for citylearn.building.Building.pricing, which is the source for pricing related observations. The data can be sourced from specific utility providers for a desired location e.g. Edison. The file structure is shown in the snippet below:

LSTM Model File

The LSTM model file is an optional PyTorch state dictionary used to initialize the cooling_dynamics and heating_dynamics temperature dynamics model attributes in citylearn.building.DynamicsBuilding and its descendant classes.

Schema Data File

The schema file is a .json file that references all other data files and is used to define the simulation environment. Refer to Schema for more information.

Warning

Do not change the order of columns in any of the .csv data files!