Smart Campus Energy Lab (SCEL)

2017 ~ Present | National Science Foundation

Smart Campus Energy Lab (SCEL)


The overarching goal of the SCEL is to gather, process, analyze and make decisions about energy and environmental data on the UH Manoa campus. This involves building sensor networks to get environmental, building energy, and electric grid data. We are also analyzing and modeling the data and then making decisions by performing demand response algorithms to control loads using optimization and control theory.

The main current project is to build an environmental sensor network that monitors and relays reliable weather data that is durable and long lasting. This includes designing a low power consumption sensor module that communicates in a mesh-network configuration and is self powered using a solar panel and rechargeable battery; deploying the sensor modules on building roofs in the UH Manoa campus; collecting data in real time and storing it in a data base; analyzing and visualizing the data in real time; and distributing the data to the public for educational and research purposes.

Issues Involved or Addressed

The Smart Campus Energy Lab (SCEL), a subdivision of the Renewable Energy and Island Sustainability (REIS) program, is developing sensor modules that collect weather data (solar irradiance, wind speed and direction, moisture, humidity, etc). Our lab aims to design and develop low-cost, low power, accurate, and reliable environmental sensor modules that can easily be reproduced for mass development on rooftops across the University of Hawaii at Manoa campus. The data collected is used to analyze spatial and temporal impacts on the renewable energy sources. The results can be used to help integrate renewable energy sources and use demand response algorithms to provide for a more stable and efficient electrical grid as well as providing risk mitigation for electricity generation through the development of renewable resource prediction and forecasting algorithms.

Methods and Technologies

  • renewable energy
  • weather data
  • sensor nodes
  • wireless sensor network
  • microgrids

Academic Majors of Interest

  • Electrical Engineering
  • Computer Engineering
  • Mechanical Engineering

Preferred Interests and Preparation

EE/CEng: Background/interest in programming, networking, circuit analysis and design, digital and analog hardware design, signal processing, filter design, prediction and forecasting
ME: Background/interest in CAD

Team Advisors

Anthony Kuh


National Science Foundation

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