  The energy transition is expected to significantly increase the share of
renewable energy sources whose production is intermittent in the electricity
mix. Apart from key benefits, this development has the major drawback of
generating a mismatch between power supply and demand. The innovative dynamic
pricing approach may significantly contribute to mitigating that critical
problem by taking advantage of the flexibility offered by the demand side. At
its core, this idea consists in providing the consumer with a price signal
which is evolving over time, in order to influence its consumption. This novel
approach involves a challenging decision-making problem that can be summarised
as follows: how to determine a price signal maximising the synchronisation
between power supply and demand under the constraints of maintaining the
producer/retailer's profitability and benefiting the final consumer at the same
time? As a contribution, this research work presents a detailed formalisation
of this particular decision-making problem. Moreover, the paper discusses the
diverse algorithmic components required to efficiently design a dynamic pricing
policy: different forecasting models together with an accurate statistical
modelling of the demand response to dynamic prices.
