The CityLearn Challenge 2022 focuses on the opportunity brought on by home battery storage devices and photovoltaics. It leverages CityLearn, a Gym Environment, for building distributed energy resource management and demand response. The challenge utilizes 1 year of operational electricity demand and PV generation data from 17 single-family buildings in the Sierra Crest home development in Fontana, California, that were studied for Grid integration of zero net energy communities.
Use case
Smart-district energy optimizer
| Example observations | hour_of_day, day_of_week, month, outdoor_temp, outdoor_rel_humidity solar_irradiance, carbon_intensity, elec_price building-level native loads: cooling_demand, heating_demand, dhw_demand, non_shiftable_elec_demand device SOCs: battery_soc, dhw_tank_soc pv_generation, building_area, number_of_floors |
| Example actions | battery dispatch (-1 = full charge, 1 = full discharge) dhw_tank heating power fraction cooling_tank charging power fraction |
| Example reward | – ( λ₁*energy_cost + λ₂*carbon_emission + λ₃*peak_penalty) where: energy_cost = elec_price*net_grid_import carbon_emission = carbon_intensity*net_grid_import peak_penalty computed each billing period |