A Stochastic Dynamic Programming Approach to Balancing Wind Intermittency with Hydropower

Hydropower is a fast responding energy source and thus a perfect complement to the intermittency
of wind power. However, the eect wind energy has on conventional hydropower systems can be felt,
especially if the system is subject to several other environmental and maintenance constraints. The goal
of this paper is to develop a general method for optimizing hydropower operations of a realistic multireservoir hydropower system in a deregulated market setting when there is a stochastic wind input. The
approach used is stochastic dynamic programming (SDP). Currently, studies on hydropower operations
optimization with wind have involved linear programming or stochastic programming, which are based
on linearity. SDP, by contrast, is a stochastic optimization method that does not require assumptions
of linearity of the objective function. The true adaptive and stochastic nonlinear formulation of the
objective function can be applied to multiple time steps, and is effcient for many time steps compared
to stochastic programming. The preliminary results for the deterministic optimization demonstrates the
potential of this method to guide operation of the hydro system knowing the state of the system. The
research will continue with optimizing under uncertain inflows as well as wind.