With the transformation of the energy system a generation portfolio has to be adapted constantly to new conditions. The more generation units are involved and the more commodities and markets have to be observed, the more difficult the management gets.
An optimisation solution helps to monitor all aspects of cross-function planning and to utilise the resulting market opportunities in optimal fashion.
NEW POSSIBILITIES IN LONG-TERM PLANNING
The planning processes of production portfolios require the optimisation of very long periods in many places. From investment/divestment planning to economic planning and (remaining) annual planning all users are struggling with the balancing act between model accuracy and solution time for optimisation. The market rules generally force hourly modeling. To limit the model size, methods are often used that subdivide the whole problem into sub-problems
(e.g. optimisation in monthly slices).
Since BoFiT Optimisation 7.1 an optimisation problem can now be optimized completely or partially relaxed. This means that the actual binary variables of the problem are no longer considered binary and solutions are also allowed where these values deviate from 0 and 1.
First application examples show that the solution times decrease dramatically, while at the same time the considered fuel quantities etc. only deviate by a few percent from the non-relaxed solution. Since the model error due to unknown long-term stock exchange prices or heat demand is considerably higher, considerable advantages for long-term planning can be tapped here.
For the remaining year planning, it is also possible to calculate the exact model at the beginning of the optimisation horizon and, for example, from the second month of the optimisation to relax the binary variables. In addition, the start-up ramp can now be switched off for parts of the horizon, since these modelling details typically are only relevant for the short-term results.
The feature is included in the standard since BoFiT Optimisation 7.1. Are you interested in a study to redesign your planning processes with a view to these new possibilities?