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Continuous-time optimization models have successfully been used to capture the impact of ramping limitations in power systems. In this paper, the continuous-time framework is adapted to model flexible hydropower resources interacting with slow-ramping thermal generators to minimize the hydrothermal system cost of operation. To accurately represent the non-linear hydropower production function with forbidden production zones, binary variables must be used when linearizing the discharge variables and the continuity constraints on individual hydropower units must be relaxed. To demonstrate the performance of the proposed continuous-time hydrothermal model, a small-scale case study of a hydropower area connected to a thermal area through a controllable high-voltage direct current (HVDC) cable is presented. Results show how the flexibility of the hydropower can reduce the need for ramping by thermal units triggered by intermittent renewable power generation. A reduction of 34% of the structural imbalances in the system is achieved by using the continuous-time model., Comment: Accepted for publication through the Power Systems Computation Conference 2020

As the penetration of variable renewable powergeneration increases in power systems around the world, systemsecurity is challenged. Ensuring that enough reserve capacity isavailable to balance the increased forecast errors introduced bywind and solar power are and will be an important challengeto solve for system operators. This is also true in systems thatalready have flexible balancing resources, such as hydropower.The main challenge in this case will be the coordination ofthe reserve procurement between connected hydropower plants,as the water flow is changed when the reserve capacity isactivated. However, the activation step is often ignored orsimplified in hydropower scheduling models that include reservecapacity procurement. In this paper, a two-stage model forscheduling power and procuring symmetric spinning reserves in ahydropower system with uncertain net load is proposed to capturethe effect of geographic reserve capacity coordination. To modelthe uncertainty in the net load, a new mixed stochastic-robustoptimization model is proposed to achieve cost efficiency andsystem security. We show that this proposed model outperformsits natural contenders in the given case study, and so does notsuffer from the typical overly conservative nature of pure robustmodels.