2016/09/30 by Yübo Wang, Wang, Yubo, Wenbo Shi +7
Engineering · #Advanced Battery Technologies Research #Electric Vehicles and Infrastructure #FOS: Electrical engineering #Smart Grid Energy Management #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1609.09610
openalex publication_date 2016/09/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
The trending integrations of Battery Energy Storage System (BESS, stationary battery) and Electric Vehicles (EV, mobile battery) to distribution grids call for advanced Demand Side Management (DSM) technique that addresses the scalability concerns of the system and stochastic availabilities of EVs. Towards this goal, a stochastic DSM is proposed to capture the uncertainties in EVs. Numerical approximation is then used to make the problem tractable. To accelerate the computational speed, the proposed DSM is tightly relaxed to a convex form using second-order cone programming. Furthermore, in light of the continuous increasing problem size, a distributed method with a guaranteed convergence is applied to shift the centralized computational burden to distributed controllers. To verify the proposed DSM, real-life EV data collected on UCLA campus is used to test the proposed DSM in an IEEE benchmark test system. Numerical results demonstrate the correctness and merits of the proposed approach.