Om
Prodrisk allows scheduling within a geographical area assuming no internal transmission grid bottlenecks, and can in principle be run in two modes; a market mode and an isolated mode. In the market mode, the system under consideration is connected to a market, and the market prices are exogenously given. In the isolated mode, all relevant parts of the power system are modelled, and Prodrisk performs the "market clearing" to obtain power prices.
ProdRisk is in operational use by many of the largest hydropower producers in the Nordic power market.
Solution approach
Prodrisk is based on SDDP which enables stochastic optimization with a large number of reservoirs. The solution approach combines system simulation and strategy computation to find an optimal hydro release strategy. In brief, this separation is achieved by dividing the overall problem in to smaller optimization problems, which are solved by using linear programming and coordinated by using on the principle of Benders decomposition. System constraints can be treated equally in both the system simulation and strategy computation. Prodrisk allows treating the power price as an exogenously given stochastic variable by integrating the principle of stochastic dynamic programming (SDP) in the SDDP scheme.
Modelling features
- solves the same scheduling problem as is solved by the EOPS model. That is, the market description and detailed hydro module description is similar for the two models;
- has a stochastic time-resolution of one week, but allows dividing the week in to load blocks with down to hourly time resolution;
- generates coupled water values (or cuts) which can serve as input to the short-term operational planning, providing a consistent coupling between the two;
- is designed for parallel processing;
- has functionality for risk management and dynamic hedging.
Transmission grid and wind power
In a research prototype named ProdNett, Prodrisk was extended to analyse transmission system bottlenecks by adding linearized power flow constraints, and model wind power as a stochastic variable.
