Stochastic energy management of responsive plug-in electric vehicles characterizing parking lot aggregators

摘要: Abstract Rapid advances in Plug-in Electrical Vehicle (PEV) technologies are expanding charging infrastructures especially large shopping centers. Flexibility potential of PEVs can compensate for volatility and intermittency electricity generation power systems with high penetration renewable energy sources. This paper proposes a novel multi-stage stochastic-based structure Parking Lot Aggregators (PLA) to integrate flexibility potentials into systems. The proposed approach uses three trading floors short-term market, including day-ahead, adjustment, balancing markets, trade the PEVs’ flexibility, from 24 h before delivery time until near real-time, market. In order extract behavior Shopping Center Lots (SCPL), data-driven is formulated. suggested makes it possible optimize charging/discharging operation huge number low computational burdens, which clear need real-time optimization. Instead subsidizing responsive PEVs, PLA maximizes profit market participants, i.e. PEV owners, through integrated not only income owners but also provides functional future intermittent power. Numerical studies real data on an SCPL Danish sector Nordic Electricity Market assures competence guarantee system against