This Grant Opportunities for Academic Liaison with Industry (GOALI) award will play an important role in making the alternative energy source that harnesses the power of ocean waves economically viable. The ultimate goal is to make wave energy a reliable and cost-effective source of large-scale, grid-quality, clean power. Mathematical optimization models and techniques will be developed and used to design so-called wave farms. In addition, the wave energy conversion (WEC) devices that constitute these wave farms can be connected via sensor networks, which allows dynamic operation of the WECs, allowing for solutions that are not only cost-effective but also robust with respect to changes in the sea environment. The academic/industry partnership between Lehigh University and Ocean Power Technologies (OPT) will give the research strong potential to be applied in practice, helping the U.S. take the lead in research and implementation of wave energy conversion.
The main objective of this award is to develop novel optimization models and algorithms for designing and operating arrays of WEC devices. The investigators will advance the state of the art in modeling and optimizing strategic problems in the layout of arrays of WECs (also known as wave farms). The project will consider both deterministic sea environments (for which there are still many open questions) and stochastic wave environments (which will initiate a new body of research). Models and algorithms to optimize the locations of WECs within a wave farm array, which can have a significant impact on the total power of the farm due to the hydrodynamic interactions among the WECs, will be developed. A second goal of the project is to optimize the types and locations of sensors that collect data on waves and forecast the actual waveforms at the WECs, thus improving the control of the WECs. The research team will develop models and algorithms for maximum-likelihood estimation of wave realizations as a function of sensor system design, and then optimize the design itself with respect to the types and locations of sensors.
