Title:
Optimal management of pumped hydroelectric production with state constrained optimal control
Abstract:
We present a novel technique to solve the problem of managing optimally a pumped hydroelectric storage system. This technique relies on representing the system as a stochastic optimal control problem with state constraints, these latter corresponding to the finite volume of the reservoirs. Following the recent level-set approach presented in O. Bokanowski, A. Picarelli, H. Zidani, State-constrained stochastic optimal control problems via reachability approach, SIAM J. Control and Optim. 54 (5) (2016), we transform the original constrained problem in an auxiliary unconstrained one in augmented state and control spaces, obtained by introducing an exact penalization of the original state constraints. The latter problem is fully treatable by classical dynamic programming arguments.
Biography:
Athena Picarelli is Assistant Professor at the Department of Economics, University of Verona. Previously, she has been CFM Research Fellow at Imperial and Nomura Research Fellow at the Mathematical and Computational Finance Group in Oxford. Her research spans optimal control, dynamic programming, numerical methods for Hamilton-Jacobi PDEs and computational finance.
Zoom Meeting Details
- Link: https://imperial-ac-uk.zoom.us/j/97484981961?pwd=cUFnNE1pL3BQUXd6WnZjMUoyMWhVZz09
- Meeting ID: 974 8498 1961
- Passcode: 6qRB=&