This paper compares the NEWAVE model, a stochastic dual dynamic programming based approach used in Brazil for the long term hydropower scheduling of the interconnected Brazilian power system, to the ODIN model (Optimal Dispatch for the Interconnected Brazilian National system), a deterministic approach based on model predictive control. The former adopts a composite representation of the hydro system and piecewise linear approximations to make the application of dynamic programming solution technique possible to the Brazilian system. The latter uses a nonlinear optimization algorithm considering predicted future inflows with a detailed representation of the individual power plants. Data from official sources were used to formulate a case study on the monthly operation planning of January 2011 that considers the projected expansion plans up to December 2015. Tests were performed by simulation using 75 historical inflow scenarios. In comparison to the scheduling provided by the stochastic approach, the proposed deterministic one was found to provide a superior performance due to the more efficient use of water resources, leading to a more secure and economic operation.
A Novel Quantum-Inspired Approximate Dynamic Programming Algorithm for Unit Commitment Problems
