Changes in light levels due to weather often cause fluctuations in the output power of photovoltaic (PV) arrays. This unpredictability causes issues for the electric grid such as reverse power flow and voltage fluctuation. Supplementary power systems such as generators and batteries can smooth the output, but they cannot be activated instantaneously. We designed a cloud motion vector system (CMVS) using an array of ambient light sensors to calculate the size, speed, and direction of clouds in order to predict changes in power generation. We also began exploring the implementation of a camera and machine learning image processing to supplement the accuracy of the system. This system will enable solar farm operators to predict drops in output power so that they are able to ramp up supplementary power right when it is needed.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Rockrohr, Olivia
• Pruitt, Emma
• Hanlon, Megan
• Carter, Erin

Subject

• Energy
• Infrastructure
• Sustainability
• Innovation

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-042523-160905
• 105006

Advisor

• Zhang, Ziming
• Guo, Tian
• Noetscher, Gregory

Year

• 2023

UN Sustainable Development Goals

• 7 - Affordable and Clean Energy
• 9 - Industry, Innovation and Infrastructure

Date created

• 2023-04-25

Resource type

• Major Qualifying Project

Major

• Computer Science
• Electrical & Computer Engineering

Source

• E-project-042523-160905

Rights statement

• In Copyright

Última modificação

• 2023-06-22