With the penetration of electric vehicles in local markets, vehicle-induced electricity demand can cause power grid instability. Collaborative smart charging can help stabilize grid demand and mitigate those issues. This paper formulates charge scheduling when connected vehicles constitute a large portion of instantaneous demand. Allowing coordinated charging to sway electricity price, we formulate a multi-objective stochastic optimization problem to minimize cost while maximizing charge in each car. We model stochastic base electricity demand using a Gaussian Mixture Model (GMM) and solve the certainty-equivalent stochastic optimization problem. We then implement a stochastic model predictive control (SMPC) algorithm and compare performance between a naive policy, a certainty-equivalent optimized policy, and SMPC on a dataset derived from California ISO-serviced demand.
Stochastic Model Predictive Control for Scheduling Charging of Electric Vehicle Fleets with Market Power
01.11.2019
247429 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
ELECTRIC VEHICLE BATTERY TEMPERATURE CONTROL FOR CHARGING VEHICLE FLEETS
Europäisches Patentamt | 2024
|Inductive fast-charging electric vehicle fleets
Kraftfahrwesen | 1999
|Electric Vehicle Charging Optimization Through Charging Perturbation Across On-Road EV Fleets
Europäisches Patentamt | 2024
|