Wave-to-wire Modelling of Wave Energy Converters: Critical Assessment, Developments and Applicability for Economical Optimisation

The wild development of the world from the 1769, years in which James Watt patented his steam engine, brought utterly to the actual, real or assumed, economical, political, environmental and energetic crisis. The answer to the question “how to solve these problems?" is a tangled unsolved discussion, but talking about renewable energy partially ravels the problem out. Wave energy is a large, mostly untapped, renewable energy resource. It has the potential to contribute significantly to the future energy mix, but the sector has not yet rolled off into the market in consequence of a number of technical and non-technical issues. These can be efficiently summarised in the cost of the energy produced by the various wave energy converters: If compared with other renewable energy technologies the cost of energy from the ocean waves is still significantly higher. Holding the comparison it also important to noticed that there is not a clear front runner in the wave energy sector, which fades effort and funding over a too broad frame.

In order to assist efficient development and analysis of wave energy converters and therefore to accelerate the sector progression towards commercialisation, a generally applicable, efficient and reliable wave-to-wire model tool is needed. A wave-to-wire model identifies the relation from the source of energy of a particular location to the expected device productivity. The latter being expressed in terms of electricity fed into the grid. The model needs to output a coarse picture of the actual status of the different devices and their power productivity, which is used afterwards to sieve promising concepts out.

In a macro-scale the work can be divided into two main contributions

First, highlight the complementarity between numerical simulation and laboratory experience, in what can be efficiently summarised as: reliable model. Numerical models are per se meaningless, but easy to manipulate, fast and relatively cheap. Physical models are complex, slow and expensive but realistic if adequately implemented. Since there is no real need of “new", but more of “how can we get the best of what we have", the numerical model used is entirely based on well established methods. The experimental data is used as a check point to verify the direction of the numerical path.

Second, shed light on what should be the objective of the sector: minimisation of the cost of energy. Two different techniques to reduce the cost of energy are compared: the former maximises the system revenue (income) by acting on the control logic, while the second extends the first methods adding a penalty term due to the effect of the control logic on the structural design. Both methods are once more based on well established or standard techniques.