Abstract
This paper presents a framework for long-term
price forecasting in hydro-thermal power systems comprising two
modeling layers. A long-term hydro-thermal model expresses the
expected future cost as a function of hydro reservoir levels to a
short-term operational model. The short-term model re-optimizes
the weekly decision problem with more details and a finer time
resolution. To cope with the high computation times, we
decompose the weekly decision problem into daily sub-problems
by interpolating in the weekly cost functions from the long-term
model. The short-term model is refined by adding detailed
constraints on the operation of thermal power plants. We assess
the importance of detailed modeling of thermal power plants in a
case study of the Nordic power system.
price forecasting in hydro-thermal power systems comprising two
modeling layers. A long-term hydro-thermal model expresses the
expected future cost as a function of hydro reservoir levels to a
short-term operational model. The short-term model re-optimizes
the weekly decision problem with more details and a finer time
resolution. To cope with the high computation times, we
decompose the weekly decision problem into daily sub-problems
by interpolating in the weekly cost functions from the long-term
model. The short-term model is refined by adding detailed
constraints on the operation of thermal power plants. We assess
the importance of detailed modeling of thermal power plants in a
case study of the Nordic power system.
