Integration of plug-in electric vehicles (PEVs) with distributed renewable resources will decrease PEVs' well-to-wheels greenhouse gas emissions, alleviate power congestions and defer power system investments. This paper proposes a two stage stochastic joint planning model of PEV fast-charging stations and distributed photovoltaic (PV) generation on coupled transportation and power networks, considering stochastic characteristics of base load, traffic flow and PV power. We use origin-destination (OD) traffic flow to estimate PEV charging demands and propose a second order cone programming (SOCP) model for PV power generation with reactive power control. A modified capacitated-flow refueling location model (CFRLM) is used to describe the transportation network and explicitly capture time-varying PEV charging demands under driving range constraints. AC power flow with SOCP relaxation is adopted to incorporate power network constraints. The joint planning model is a mixed-integer SOCP model and can be solved by an off-the-shelf solver.
Abstract:
Publication date:
July 1, 2017
Publication type:
Conference Paper
Citation:
Zhang, H., Moura, S., Hu, Z., Qi, W., & Song, Y. (2017). Joint PEV Charging Station and Distributed PV Generation Planning. 2017 IEEE Power & Energy Society General Meeting, 1–5. https://doi.org/10.1109/PESGM.2017.8274111