Method for forecasting energy demands that incorporates urban heat island

Patent metadata

Field	Value
Publication number	US-2016125294-A1
Application number	US-201414530099-A
Country	US
Kind code	A1
Filing date	Oct 31, 2014
Priority date	Oct 31, 2014
Publication date	May 5, 2016
Grant date	—

Abstract

A method for forecasting energy demand for a single building, a neighborhood or a city in an urban environment is disclosed. The method treats urban heat island (UHI) calculations as being dynamically impacted by predicted weather conditions to calculate a weather-adjusted UHI. Predicted energy consumption rates for weather conditions use the weather-adjusted UHI to increase accuracy of the prediction.

First claim

What is claimed is:

1 . A method for forecasting energy demand for a building in an urban environment, the method comprising steps of:
determining a predicted weather condition of an urban environment at a predetermined time using a weather forecasting model; finding, using a building energy model, an impact of the predicted weather condition on an urban heat island (UHI) of the urban environment, the step of finding producing a weather-adjusted UHI condition; quantifying a predicted energy consumption rate for a building in the urban environment at the predetermined time based on the weather-adjusted UHI condition that incorporates the impact of the predicted weather condition on the urban heat island (UHI).

2 . The method as recited in claim 1 , wherein the method forecasts the energy consumption rate over a time frame, wherein the predetermined time is within the time frame.

3 . The method as recited in claim 1 , wherein the building energy model segments the urban environment into uniform grids.

4 . The method as recited in claim 1 , wherein the building energy model segments the urban environment into uniform grids with a grid size, the grid size selected to group buildings with a uniform horizontal distribution together.

5 . The method as recited in claim 1 , wherein the building energy model segments the urban environment into uniform grids with a grid size, the grid size selected to group buildings with a uniform mean building height together.

6 . The method as recited in claim 1 , wherein the building energy model segments the urban environment into uniform grids with a grid size, the grid size selected to group buildings with dark roofs together.

7 . The method as recited in claim 6 , wherein the building energy model segments the urban environment into uniform grids with a grid size, the grid size selected to group buildings with white roofs together.

8 . The method as recited in claim 1 , further comprising presenting results of the step of quantifying in units of energy consumption per unit time.

9 . The method as recited in claim 1 , wherein the building energy model comprises a Building Energy Parameterization (BEP) that accounts for thermal impacts from horizontal and vertical building surfaces of the building.

10 . The method as recited in claim 1 , wherein the building energy model comprises a Building Energy Model (BEM) that accounts for consumption of energy due to air conditioning (AC) systems.

11 . The method as recited in claim 10 , wherein the Building Energy Model (BEM) accounts for generation of heat due to the air conditioning (AC) systems.

12 . The method as recited in claim 11 , wherein the Building Energy Model (BEM) accounts for diffusion of heat through walls, roofs and floors.

13 . A method for forecasting energy demand for a plurality of building in an urban environment, the method comprising steps of:
determining a predicted weather condition of an urban environment at a predetermined time using a weather forecasting model; modifying the predicted weather condition using a building energy model that incorporates an impact of an urban heat island (UHI) of the urban environment on the predicted weather condition, the step of modifying producing a predicted local condition; wherein the building energy model segments the urban environment into uniform grids wherein at least 20% of buildings within at least one uniform grid have a height greater than ten meters; quantifying a predicted energy consumption rate for a plurality of buildings in the urban environment at the predetermined time based on the predicted local condition that incorporates the impact of the urban heat island (UHI) on the predicted weather condition.

14 . The method as recited in claim 13 , further comprising presenting results of the step of quantifying in units of energy consumption per unit area.

15 . A method for forecasting energy demand for a plurality of building in an urban environment, the method comprising steps of:
determining a predicted weather condition of an urban environment over a predetermined time frame using a weather forecasting model; modifying the predicted weather condition using a building energy model that incorporates an impact of an urban heat island (UHI) of the urban environment on the predicted weather condition, the step of modifying producing a predicted local condition; wherein the building energy model segments the urban environment into uniform grids wherein at least 20% of buildings within at least one uniform grid have a height greater than ten meters; quantifying a predicted energy consumption rate for a plurality of buildings in the urban environment over the predetermined time frame based on the predicted local condition that incorporates the impact of the urban heat island (UHI) on the predicted weather condition.

16 . The method as recited in claim 15 , further comprising presenting results of the step of quantifying in units of energy consumption per unit area.

17 . The method as recited in claim 15 , wherein at least 40% of buildings within the at least one uniform grid have a height greater than ten meters.

Assignees

• Univ City New York Res Found

Inventors

• Gonzalez Jorge E
• Arend Mark
• Gutierrez Estatio
• Legbandt Thomas
• Moshary Fred

Classifications

• G06N5/04 Primary

  Inference or reasoning models · CPC title

• G06Q10/04

  Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202) · CPC title

• G06Q50/06 Primary

  Energy or water supply · CPC title

• Y02A30/60

  Planning or developing urban green infrastructure · CPC title