# US 2014/0207431 A1 · Urban mapping technique for photovoltaic potential of rooftops

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- Number: US 2014/0207431 A1
- Document ID: US20140207431A1
- Status: Published application
- Kind: A1
- Application number: 14/160,658
- Filed: 2014-01-22
- Published: 2014-07-24
- Earliest claimed: 2013-01-23
- Assignees: Massachusetts Institute of Technology
- Applicants: Massachusetts Institute of Technology
- Inventors: Christoph F. Reinhart; John Alstan Jakubiec
- Web page: https://patentgrep.com/patent/US20140207431A1

## CPC

- G06T 17/05: Geographic models
- G06F 30/20: Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30)
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)

## Abstract

A photovoltaic map generator is provided that includes a data generator that provides LiDAR data illustrating detailed information of a geographic area. A model generator receives the LiDAR data and uniformly resamples the LiDAR data over a plan grid of specified spacing to produce simplified LiDAR data. The data points of the simplified LiDAR data are triangulated using a Delaunay algorithm to produce a highly accurate and detailed 3-D model of the geographic area.

## Claims

### Claim 1

A photovoltaic map generator comprising;
a data generator that provides LiDAR data illustrating detailed information of a geographic area; and
a model generator that receives the LiDAR data and uniformly resamples the LiDAR data over a plan grid of specified spacing to produce simplified LiDAR data, the data points of the simplified LiDAR data are triangulated using a Delaunay algorithm to produce a highly accurate and detailed 3-D model of the geographic area.

### Claim 2 (depends on 1)

The photovoltaic map generator of claim 1, wherein the model generator comprises a Radiance/DAYSIM backward-ray tracing daylight simulation engine.

### Claim 3 (depends on 1)

The photovoltaic map generator of claim 1, wherein the specified spacing comprises 1 m×1 m spacing.

### Claim 4 (depends on 1)

The photovoltaic map generator of claim 1, wherein the data points of the simplified LiDAR are divided into two or more categories for triangulation.

### Claim 5 (depends on 1)

The photovoltaic map generator of claim 1, wherein the 3-D model is divided into 1450×1450 m quadrants for simulation.

### Claim 6 (depends on 1)

The photovoltaic map generator of claim 1, wherein each of the quadrants includes a 750×750 m region of a virtual rooftop to be simulated surrounded by 350 m of context in each direction.

### Claim 7 (depends on 1)

The photovoltaic map generator of claim 1, wherein the geographic area is divided into representational sections, simulation time, and memory overhead.

### Claim 8 (depends on 1)

The photovoltaic map generator of claim 1, wherein the simplified LiDAR data points are divided into two categories using publicly available building polyline GIS datasets

### Claim 9 (depends on 1)

The photovoltaic map generator of claim 1, wherein the model generator resamples the LiDAR data taking the maximum value of the first return data in the plan grid where multiple points exist.

### Claim 10

A method for generating a photovoltaic map comprising;
providing LiDAR based data illustrating detailed information of a geographic area;
receiving the LiDAR data and uniformly resamplingthe LiDAR data over a plan grid of specified spacing to produce simplified LiDAR data using a model generator using a model generator; and
triangulating the data points of the simplified LiDAR data using a Delaunay algorithm to produce a highly accurate and detailed 3-D model of the geographic area.

### Claim 11 (depends on 10)

The method of claim 10, wherein the model generator comprises a Radiance/DAYSIM backward-ray tracing daylight simulation engine.

### Claim 12 (depends on 10)

The method of claim 10, wherein the specified spacing comprises 1 m×1 m spacing.

### Claim 13 (depends on 10)

The method of claim 10, wherein the data points of the simplified LiDAR are divided into two or more categories for triangulation.

### Claim 14 (depends on 10)

The method of claim 10, wherein the 3-D model is divided into 1450×1450 m quadrants for simulation.

### Claim 15 (depends on 10)

The method of claim 10, wherein each of the quadrants includes a 750×750 m region of a virtual rooftop to be simulated surrounded by 350 m of context in each direction.

### Claim 16 (depends on 10)

The method of claim 10, wherein the geographic area is divided into representational sections, simulation time, and memory overhead.

### Claim 17 (depends on 10)

The method of claim 10, wherein the simplified LiDAR data points are divided into two categories using publicly available building polyline GIS datasets

### Claim 18 (depends on 10)

The method of claim 10, wherein the model generator resamples the LiDAR data taking the maximum value of the first return data in the plan grid where multiple points exist.