Stochastic Model Predictive Control of Charging Energy Hubs with Probabilistic Forecasting
Year: 2025
Type: conference-paper
Abstract: We introduce an energy management system for an energy hub in an electric vehicle charging station with photovoltaic generation and a battery energy storage system. First, we design a scenario-based stochastic model predictive control that uses probabilistic day-ahead forecasts of charging load and solar generation to achieve cost-optimal operation of the energy hub. Second, the probabilistic forecasts leverage conformal prediction providing calibrated distribution-free confidence intervals starting from machine learning models that generate no uncertainty quantification. In preliminary results, we run a 10-day evaluation in a closed-loop simulated environment to compare the observed cost of the scenario-based stochastic control (100.21%) with two deterministic alternatives: a version with point forecast (100.32%) and a version with perfect forecast (100%).
Institution: Eindhoven University of Technology
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4415179549