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Simulation of sizeable hydro-thermal power systems, such as Northern Europe or larger, requires several extensive simplifications and model reductions to decrease simulation time. Such reductions for hydrosystems are often called Equivalent models. Their purpose is to mimic a more detailed hydropower model while decreasing computation time. Both aspects are vital for accurate and useable simulation results. Here, different Equivalent models for hydropower have been developed together with a new function for adaptive Equivalent inflow based on local inflows to the detailed system. The models were computed via a bilevel optimization problem factoring in the novel adaptive inflow. Based on this, the new function for adaptive inflow was calculated using regression. The Equivalents have then been evaluated in a case study of hydropower systems in Northern Sweden regarding accuracy in hourly and total power generation, revenue estimation, and relative computation time. For all Equivalents, the computation time is decreased by ¿96%. Further, the Equivalents demonstrate improved performances in hourly and total power production and revenue estimations. The best hourly power difference was 9.2%, and the best revenue estimation was 5.9%. Especially notable is the low total power production difference of ¡0.5% compared to the more detailed model. [ABSTRACT FROM AUTHOR]

For inclusion in large-scale power system models, various aggregations and simplifications in the modeling of relevant actors are needed. This paper focuses on reduced models of hydropower, so called area Equivalent models. They use a simplified topology but are not a direct aggregation of the real hydropower system. Instead, the area Equivalent is constructed to mimic the simulated power production of a more detailed hydropower reference model. Here, this goal is fulfilled by formulating a bilevel problem minimizing the difference in simulated power production between the area Equivalent and its reference. Solving this can be computationally heavy. Thus, for a fast solution of this bilevel problem, a single-level reduction is done, which is then solved using two methods. The first method includes McCormick envelopes to form a linear single-level problem. Second is a modified Benders with a relaxed sub-problem to handle the non-convex single-level. These are then also compared to Particle Swarm Optimization. Moreover, six new upper-level objective functions are investigated for a case study of hydropower in northern Sweden. The method using McCormick envelopes is fast (2–5 min), but the area Equivalent shows lower average performance. The modified Benders finds a solution in 5–31 min with good performance. [ABSTRACT FROM AUTHOR]