Model predictive control of sea wave energy converters – Part II: The case of an array of devices |
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Affiliation: | 1. The School of Engineering and Materials Science, Queen Mary, University of London, Mile End Road, London E1 4NS, UK;2. College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QF, UK;1. NTNU, Trondheim, Norway;2. CorPower Ocean, Stockholm, Sweden;3. WavEC, Lisbon, Portugal;1. Michigan Technological University, Mechanical Engineering – Engineering Mechanics Department, Houghton, MI, USA;2. Sandia National Laboratories, Albuquerque, NM, USA;3. South Dakota School of Mines & Technology, Rapid City, SD, USA;1. Optimisation and Logistics Group, School of Computer Science, University of Adelaide, Australia;2. School of Mechanical Engineering, University of Adelaide, Australia |
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Abstract: | This paper addresses model predictive control (MPC) of highly-coupled clusters of sea wave energy converters (WECs). Since each WEC is not only a wave absorber but also a wave generator, the motion of each WEC can be affected by the waves generated by its adjacent WECs when they are close to each other. A distributed MPC strategy is developed to maximize the energy output of the whole array and guarantee the safe operation of all the WECs with a reasonable computational load. The system for an array is partitioned into subsystems and each subsystem is controlled by a local MPC controller. The local MPC controllers run cooperatively by transmitting information to each other. Within one sampling period, each MPC controller performs optimizations iteratively so that a global optimization for the whole array can be approximated. The computational burden for the whole array is also distributed to the local controllers. A numerical simulation demonstrates the efficacy of the proposed control strategy. For the WECs operating under constraints explored, it is found that the optimized power output is an increasing function of degree of WEC–WEC coupling. Increases in power of up to 20% were achieved using realistic ranges of parameters with respect to the uncoupled case. |
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Keywords: | Wave energy Model predictive control Distributed control |
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