Tidal range renewable power plants have the capacity to deliver predictable
energy to the electricity grid, subject to the known variability of the tides.
Tidal power plants inherently feature advantages that characterise hydro-power
more generally, including a lifetime exceeding alternative renewable energy technologies and relatively low Operation & Maintenance costs. Nevertheless, the
technology is typically inhibited by the significant upfront investment associated
with capital costs. A key aspect that makes the technology stand out relative
to other renewable options is the partial flexibility it possesses over the timing
of power generation. In this study we provide details on a design methodology
targeted at the optimisation of the temporal operation of a tidal range energy
structure, specifically the Swansea Bay tidal lagoon that has been proposed
within the Bristol Channel, UK. Apart from concentrating on the classical incentive of maximising energy, we formulate an objective functional in a manner
that promotes the maximisation of income for the scheme from the Day-Ahead
energy market. Simulation results demonstrate that there are opportunities to
exploit the predictability of the tides and flexibility over the precise timing of
power generation to incur a noticeable reduction in the subsidy costs that are often negotiated with regulators and governments. Additionally, we suggest that
this approach should enable tidal range energy to play a more active role in
ensuring security of supply in the UK. This is accentuated by the income-based
optimisation controls that deliver on average more power over periods when
demand is higher. For the Swansea Bay tidal lagoon case study a 23% increase
is observed in the income obtained following the optimisation of its operation
compared to a non-adaptive operation. Similarly, a 10% increase relative to
an energy-maximisation approach over a year’s operation suggests that simply
maximising energy generation in a setting where power prices vary may not be
an optimal strategy.