Revenue maximisation and storage utilisation for the Ocean Grazer wave energy converter: A sensitivity analysis

Jose de Jesus Barradas Berglind, H.T. Dijkstra, Yanji Wei, Marijn van Rooij, Harmen Meijer, Wouter Prins, Antonis I. Vakis, Bayu Jayawardhana

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This paper presents a revenue maximisation strategy for market integration of a novel wave energy converter (WEC), part of the Ocean Grazer platform. In particular, we evaluate and validate the aforementioned revenue maximisation model predictive control (MPC) strategy through extensive simulations and by checking the underlying assumptions of the strategy imple- mentation. Accordingly, an annual simulation of the MPC strategy is shown, which illustrates seasonality effects; furthermore, a benchmark against a heuristic strategy is presented, followed by analyses of the parameter sensitivity and the assumptions on the control loop information that the MPC receives. These efforts shed some light on the impact of variations of the considered parameters and variables on the total revenue and provide insights to optimally scale the WEC. Lastly, the challenges associated with the deployment of such a strategy are addressed, followed by concluding remarks.
Original languageEnglish
Pages (from-to)1241-1248
Number of pages8
JournalIET Renewable Power Generation
Issue number11
Early online dateJun-2018
Publication statusPublished - 20-Aug-2018


  • Wave power
  • Predictive control
  • Sensitivity analysis
  • PUMP

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