joint work with Asgeir Tomasgard, Hossein Farahmand
Flexibility is an important concept to cope with uncertainty in energy systems. In this paper, we consider the problem of an actor that manages a portfolio of flexible assets. We present a Stochastic Programming model for the dynamic scheduling of a portfolio for which energy and flexibility products can be delivered into multiple markets like day-ahead, intraday, and flexibility markets. Some of these products are locations specific, while others are system-wide or even cross-border. The purpose in the short-term is to remove bottlenecks and ensure security of supply at the minimum cost.
joint work with Gislaine Periçaro, Elizabeth Karas
The long-term operation of hydro-thermal power systems is modeled by a large-scale stochastic optimization problem with non-linear constraints due to the head computation in hydroelectric plants. We state the problem as a non-anticipative scenario analysis, leading to a large-scale non-linear programming problem. This is solved by a Filter-SQP algorithm whose iterations minimize quadratic Lagrangian approximations using exact Hessians in L-infinity trust regions. The method is applied to the long-term planning of the Brazilian system, with over 100 hydroelectric and 50 thermoelectric plants.
joint work with Luis Zuluaga
We consider an electricity market in which uncertainty arises from the presence of renewable energy sources. We consider a robust model for the market using chance constraints together with a proportional control law for power generation. We prove that in this framework, market clearing prices yielding a robust competitive market equilibrium, as well as revenue adequate prices, can be computed and used for uncertain market settlements by risk-aware system operators. We contrast our results to methods using a sample average stochastic program from desired prices can be obtained in each scenario.