Portrait of Feng Li

Feng Li

PhD - Polytechnique Montréal
Research Topics
Optimization
Probabilistic Models
Reinforcement Learning

Publications

Inferring electric vehicle charging patterns from smart meter data for impact studies
Élodie Campeau
Ilhan Kocar
Inferring electric vehicle charging patterns from smart meter data for impact studies
Élodie Campeau
Ilhan Kocar
Inferring electric vehicle charging patterns from smart meter data for impact studies
Élodie Campeau
Ilhan Kocar
A Rapid Method for Impact Analysis of Grid-Edge Technologies on Power Distribution Networks
This paper presents a novel rapid estimation method (REM) to perform stochastic impact analysis of grid-edge technologies (GETs) to the powe… (see more)r distribution networks. The evolution of network states' probability density functions (PDFs) in terms of GET penetration levels are characterized by the Fokker-Planck equation (FPE). The FPE is numerically solved to compute the PDFs of network states, and a calibration process is also proposed such that the accuracy of the REM is maintained for large-scale distribution networks. The approach is illustrated on a large-scale realistic distribution network using a modified version of the IEEE 8500 feeder, where electric vehicles (EVs) or photovoltaic systems (PVs) are installed at various penetration rates. It is demonstrated from quantitative analyses that the results from our proposed approach have negligible errors comparing with those obtained from Monte Carlo simulations.
Mitigating Equipment Overloads due to Electric Vehicle Charging Using Customer Incentives
This paper first presents a time-series impact analysis of charging electric vehicles (EVs) to loading levels of power network equipment con… (see more)sidering stochasticity in charging habits of EV owners. A novel incentive-based mitigation strategy is then designed to shift the EV charging from the peak hours when the equipment is overloaded to the off-peak hours and maintain equipment service lifetime. The incentive level and corresponding contributions from customers to alter their EV charging habits are determined by a search algorithm and a constrained optimization problem. The strategy is illustrated on a modified version of the IEEE 8500 feeder with a high EV penetration to mitigate overloads on the substation transformer.