Skip to content


As a university-wide, multi-disciplinary team of faculty and students, the Resilient, Intelligent and Sustainable Energy Systems (RISES) cluster commits itself to transformative and collaborative research in resilient, intelligent and sustainable energy systems. Through partnerships among university, utility and government stakeholders, we aim to facilitate deployment and integration of renewable energy resources, as well as provide innovative solutions that make electricity grids self-organizing, efficient and resilient. The cluster focuses upon holistic analysis, design, development and deployment of distributed renewable energy resources (PV systems in particular), advanced information, communication, control and optimization technologies, along with supporting economic and management policies. Through meeting these technical goals, we can reliably integrate renewable resources, achieve better power quality and best use markets to enable customers to make intelligent and environmentally conscientious decisions.

Overview of Program in Power & Energy Systems

  • Academic programs (BSc, MSc and PhD) in power system continuously offered since 1980s:
    • Westinghouse (and its T&D Division)
    • Duke Energy, OUC, and FPL
    • Siemens power generation
  • Enhancements achieved in 2016:
    • Undergraduate track in power/energy systems was established, students are required to take courses in power systems, machines & drives, and power electronics.
    • Undergraduate electives in renewable energy and smart grid are created.
    • Siemens’ digital grid lab is operational
  • UCF institutional investments in power/energy systems
    • Cluster on Resilient, Intelligent and Sustainable Energy Systems
    • Solar farm on the main campus
    • UCF Downtown Campus
  • Current Research Programs and Center
    • FEEDER Center, Department of Energy (Project website)
    • SolarExpert, Department of Energy (Project website)
    • Self-organizing Control and Scalable Game-theoretical Dispatch of Distributed Generations for High-Penetration Smart Grids, National Science Foundation (Project website)