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Thermal Energy Storage Model for space heating in residential buildings

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Thermal Energy Storage Model for space heating coupled with air-source heat pumps in residential homes in U.S. Cities across different climates.

Model overview

The TES model is an optimization-based model that minimizes the total space heating electricity cost to satisfy buildings space heating load using a system of thermal energy storage coupled with air-source heat pump.

The TES model can be run for a single building of choice, a range of buildings of choice, or all 400 representative buildings in any of the 12 major US cities across different climates included in the study (details below).

image (1)

Programming language

The TES model is programmed in Pyomo/Python and solved using CPLEX.

Running model

Run model from dashboard.py. Main options to choose from:

Option Description
super_comp False if run locally, True if run on supercomputer
city Options: Atlanta, Boston, Boulder, Chicago, Detroit, Dallas, Los Angeles, Minneapolis, New York, Orlando, Phoenix, Seattle
single_building True if run only one single building, specify building number next
building_no Specify building number to run. Options: 1 to 400. The 400 buildings represent over 90% heating load for a city. Each building has different heating load profile provided in Data folder.
building_range True if run a range of individual buildings, specify building range next
first_building,last_building Specify building range to run. Options: 1 to 400
pricing Fixed to apply fixed utility rate, ToD to apply time-of-day rate
include_TES True to couple TES with ASHP, False to exclude TES (only ASHP to provide load)
tes_material Four different salt hydrates MgSO4, MgCl2, K2CO3, and SrBr2
tes_sizing How TES is size, Varied if sized based on peak load, Incremental if sized based on peak load then round up to the next 25 kg ,Fixed if assumed one size (150 kg of salt)
const_pr False if use Ragone plots, True if assumed constant power rating
power_rating (only eligible if const_pr=True) Peak if setting constant power rating at peak load, Average if setting power rating at 100 W per kg, and Low if setting power rating at 10 W per kg

Model outputs for each building

  • ASHP's capacity
  • Hourly operations of TES (charging/output to shift load, discharging, SOC).
  • Hourly charging and discharging power ratings of TES.
  • Hourly operation of ASHP (output to charge TES, output to serve load).
  • Hourly purchase of electricity from utilities to power ASHP.
  • TES sizes based on specified sizing methods and TES materials.
  • Total system cost.
  • TES break-even cost.
  • Peak load reduction.

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Thermal Energy Storage Model for space heating in residential buildings

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