01:30 PM - 01:55 PM
Challenges in Real-Time Optimal Dispatch of Hydropower Units
Rio Tinto owns and operates the Kemano powerhouse in B.C. Canada where eight generators supply power to the Kitimat aluminium smelter. This talk will present the system implemented for real-time optimal dispatch which is a challenging task that required statistical analysis, data filtering and optimization of nonlinear mixed integer problems.
01:55 PM - 02:20 PM
Interior Point Methods Applied to the Predispatch Problem of a Hydroelectric System with Scheduled Line Manipulations and Security Constraints
The interior point methods are developed for minimizing the pre-dispatch generation and transmission loss of a hydroelectric DC power system where programmed maneuvers and security constraints occur. The resulting matrix structure is exploited aiming an efficient implementation. Considering that the energy demand varies along the day, the power generation should follow the (electric charge) variation. With the change in demand, it is necessary to perform some programmed maneuvers to efficiently adapt the transmission network to this load enabling it to keep the system stable. Security constraints, in turn, seek to prevent the most important contingencies related to line transmission loss, generators shut down, and violation of bounds on previously known bottlenecks. According to the National Operating System the consideration of such maneuvers and additional constraints approaches this model to the problem of the Brazilian pre-dispatch system. The developed implementation is compared with an existing one that does not consider neither additional topology change or security constraints in matters regarding computational efficiency and solution quality.
02:20 PM - 02:45 PM
Generation and Transmission Expansion Planning: A Stochastic Adaptive Robust Optimization Approach
We consider a central planner, e.g., the transmission system operator, that aims at determining the generation and transmission expansion plans in a power system that minimize both the expansion and operation costs. Uncertainties in the future peak demand and the future generation costs are modeled using confidence bounds, while uncertainties in the demand variability and the production of stochastic units such as wind- and solar-power units are modeled using scenarios. This uncertainty modeling allows us to formulate the generation and transmission expansion problem as a stochastic adaptive robust optimization model.
02:45 PM - 03:10 PM
Application of a simulation-and-regression approach for control problems
We present a simulation-and-regression, dynamic programming approach to solve control problems. The method is flexible and efficient. We will go into some detail over two applications areas, portfolio optimization problems and hydropower management, in the second case reporting results obtained with our industrial partner.