  Peak/off-peak spreads on European electricity forward and spot markets are
eroding due to the ongoing nuclear phaseout in Germany and the steady growth in
photovoltaic capacity. The reduced profitability of peak/off-peak arbitrage
forces hydropower producers to recover part of their original profitability on
the reserve markets. We propose a bi-layer stochastic programming framework for
the optimal operation of a fleet of interconnected hydropower plants that sells
energy on both the spot and the reserve markets. The outer layer (the planner's
problem) optimizes end-of-day reservoir filling levels over one year, whereas
the inner layer (the trader's problem) selects optimal hourly market bids
within each day. Using an information restriction whereby the planner
prescribes the end-of-day reservoir targets one day in advance, we prove that
the trader's problem simplifies from an infinite-dimensional stochastic program
with 25 stages to a finite two-stage stochastic program with only two
scenarios. Substituting this reformulation back into the outer layer and
approximating the reservoir targets by affine decision rules allows us to
simplify the planner's problem from an infinite-dimensional stochastic program
with 365 stages to a two-stage stochastic program that can conveniently be
solved via the sample average approximation. Numerical experiments based on a
cascade in the Salzburg region of Austria demonstrate the effectiveness of the
suggested framework.
