Determining Mean Annual Energy Production

This robust book presents all the information required for numerical modelling of a wave energy converter, together with a comparative review of the different available techniques.

The calculation of the mean annual energy production (MAEP) is critical to the assessment of the levelized cost of energy for a wave energy converter or wave farm. Fundamentally, the MAEP is equal to the sum of the product of the power capture of a set of sea-states and their average annual occurrence. In general, it is necessary in the calculation of the MAEP to achieve a balance between computational demand and accuracy. A high accuracy can be obtained using a large number of sea-states with a high fidelity power capture model; however, this is likely to result in a high computational demand. Typically, the models most suitable for calculating the MAEP are time-domain models, spectral-domain models, and models obtained through system identification. The traditional method for representing the wave climate is using a scatter table, indexed by significant wave height and energy period; however, it has been found that this can lead to high errors in the MAEP due to the necessary assumptions regarding spectral shape. Alternative representations include an extensive time series of all the sea-states or an abridged set, where the set is chosen to cover the range of sea-states as completely as possible using techniques such as the k-means algorithm or the maximum distance algorithm. Once the wave climate is defined the power capture for each representative sea-state in the wave climate can be determined using a power matrix, indexed by significant wave height and energy period, modelling all the sea-states or modelling a representative set of sea-states defined using the radial basis functions method. The use of the power matrix is most popular, but also least accurate, whilst modelling all the sea-states is the most computationally demanding, but also the most accurate.