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1	Linearization-Based Strategies for Optimal Scheduling of a Hydroelectric Power Plant Under Uncertainty / Linearization-Based Scheduling of Hydropower Systems Tikk, Alexander January 2019 (has links) This thesis examines the optimal scheduling of a hydroelectric power plant with cascaded reservoirs each with multiple generating units under uncertainty after testing three linearization methods. These linearization methods are Successive Linear Programming, Piecewise Linear Approximations, and a Hybrid of the two together. There are two goals of this work. The first goal of this work aims to replace the nonconvex mixed-integer nonlinear program (MINLP) with a computationally efficient linearized mixed-integer linear program (MILP) that will be capable of finding a high quality solution, preferably the global optimum. The second goal is to implement a stochastic approach on the linearized method in a pseudo-rolling horizon method which keeps the ending time step fixed. Overall, the Hybrid method proved to be a viable replacement and performs well in the pseudo-rolling horizon tests. / Thesis / Master of Applied Science (MASc) Hydropower/Hydroelectric Uncertainty Linearization Scheduling Optimization Successive Linear Programming (SLP) Piecewise Linear Approximations (PLA) Stochastic Nervousness Rolling Horizon Cascaded Reservoirs Hybrid nonconvex Start-up costs Generators