Sustainable Design Lab @ MIT
Cambridge Solar Map Go To Map>> | Watch Demo Video>>

Alstan Jakubiec and Christoph Reinhart (funded by the NSF under Grant No. 1038264; 2011 - 2012)
Solar Energy Paper

In this project we developed a new simulation-based technique to reliably predict the annual electricity yield from an arbitrarily oriented and obstructed photovoltaic (PV) array located anywhere on the planet. The technique considers detailed surrounding geometry such as trees and buildings, hourly direct and diffuse solar radiation data as well as instantaneous solar cell efficiencies due to varying roof temperatures. Required simulation inputs are standard local weather station data as well as LIDAR point clouds.

As a proof of concept, the we teamed up with the City of Cambridge and Eduardo Berlin from Modern Development Studio and generated an interactive Solar Map of Cambridge. MIT created an annual electricity yield map from PV for all Cambridge rooftops. The data shows which roofs in Cambridge have excellent, good, poor and no solar potential for PV. The map has a resolution of 5' by 5'. Modern Develoment Studio devleopped the online viewer and a financial analysis module that considers federal and state incentives for residential and commercial PV installtions as well as estimated payback times for PV systems with excellent or good solar potential. The City of Cambridge provided the underlying LiDAR data and Google ortho-images. The basic steps of the simulation technique are shown below. More details can be found here.

Test image 00

1 - Arial photo of the MIT campus with the Kresge Auditorium.

Test image 00

2 - The LIDAR data from the City of Cambridge consists of 126 million data points.

Test image 00

3 - A simplification algorithm was used to reduce the data set to 9 million points.

Test image 00

4 - Using Delauny triangulation and GIS floor print data a 3D model of Cambridge with different surface properties was generated.

Photo of Backward Raytracing and Sky Model

5 - The model was combined with hourly solar radiation data via a sky model and backwards raytracing (Daysim/Radiance).

Photo of a solar cell with text: tmperature

6 - Hourly solar radation data and roof temperatures were combined into annual ectricity yield from PV.

Photo of a solar cell with text: tmperature

7 - Electriciy yields were classified and mapped on top of Google sattelite images.

Photo of a solar cell with text: tmperature

8 - The financial analysis considers public incentives to calculate the armortisation time for excellent and good roof areas.

MIT's portion of the project has been supported by the National Science Foundation under Grant No. 1038264. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.