Optimising the control of a fixed pitch tidalturbine using a python based tool

The tides are unique among renewable energy resources. It is both highly predictable and energy dense, which presents many opportunities for designing a Tidal Energy Converter (TEC). One of the principal advantages is that the design of the turbine can be closely tailored to the site in question by performing a cost-based optimisation. This requires knowledge of how both the generator and the blades perform to produce a mapping from flow speed to generated power, typically called a power curve. Tocardo technologies are developing a turbine to be deployed at the Morlais tidal energy site using QED Naval’s seabed mounted Subhub platform. The seabed-mounted design aims to maximise the blades’ frontal area thereby maximising the energy generation potential. However maintenance requirements should be minimal given the challenges of accessing the device. Accordingly, turbine consisting of passively pitched blades and a Permanent Magnet Synchronous Machine (PMSM) has been chosen due to their proven simplicity, reliability, and efficiency. To ensure that a future utility scale device is well suited to its environment, this paper presents a python-based tool that has been developed to integrate the behaviour of the blades with the electrical performance of the generator to produce a predicted power curve. In doing so this tool illustrates why operating a non-actively pitched device must be treated differently to an actively pitched device. The tool’s principal function is the generate surface plots that describe the behaviour of the turbine at all flow and turbine speed combinations within the desired range. It achieves this by representing the blades using a tip-speed-ratio to torque-coefficient mapping to produce surfaces describing the mechanical torque and power generated by the blades. An equivalent circuit model of the PMSM is then optimised for the most efficient operational state for each torque-speed pair. While this typically equates to Maximum Torque Per Ampere (MPTA), the model can also simulate field weakening at higher turbine speed. This tool has allowed for a power curve to be produced that does not use the concept of a single rated point or pre-defined operational strategy. Instead by looking at the whole landscape of operational points, it is possible to find the best way of operating the device for any given flow speed. Therefore, the surface plots produced highlight how fixed pitch devices when operated to their maximum cannot be described effectively by a single rated point. This has implications for how such turbines are classified within funding schemes such as the UK government’s Contracts for Difference (CfD) mechanism. In future, this tool is used to link generator and blade analysis with an analysis of the resource at the Morlais site allowing for a cost-revenue analysis to be performed. It will therefore be invaluable for the development of an optimal tidal turbine.