9 papers
Control-Oriented Scenario Tree Construction through Reinforcement Learning
Fabio Pavirani, Bert Claessens, Pierre Pinson +1
Multistage stochastic model predictive control (MPC) handles uncertainty by optimizing over a scenario tree, a finite branching approximation of future outcomes constructed from sa…
S3TS: Stochastic Scenario-Structured Tree Search for Advanced Planning Under Uncertainty
Fabio Pavirani, Bert Claessens, Pierre Pinson +1
Effective scheduling in the energy sector is essential to ensure the reliable operation of electrical grids and their connected assets by, for instance, optimizing the dispatch of…
Decision-calibrated prediction sets for robust power system operations
Akylas Stratigakos, Honglin Wen, Elina Spyrou +1
Robust optimization offers a tractable approach to balance operating costs and reliability in power systems dominated by weather-dependent renewable uncertainty, but its performanc…
Stabilizing distribution-free probabilistic forecasts
Jente Van Belle, Honglin Wen, Wouter Verbeke +1
Multi-step-ahead forecasts are often updated as new observations become available, since shorter forecast horizons typically improve forecast quality. However, such improvements co…
Probabilistic Prediction Markets with Intermittent Contributions
Michael Vitali, Pierre Pinson
Although both data availability and the demand for accurate forecasts are increasing, collaboration between stakeholders is often constrained by data ownership and competitive inte…
Value-oriented forecast reconciliation for renewables in electricity markets
Honglin Wen, Pierre Pinson
Forecast reconciliation is considered an effective method to achieve coherence (within a forecast hierarchy) and to improve forecast quality. However, the value of reconciled forec…