A tactical transactive energy scheduling for the electric vehicle-integrated networked microgrids

Abstract

A bi-level hybrid robust-stochastic framework is proposed in this study to scrutinize the tactical market behaviour of networked microgrids (NM) integrated with high penetration of electric vehicle fleets (EVF). At the first level, the NMs’ aggregator self-schedules the distributed generation (DG) units, transactive energy exchange between micro grids, as well as the residential EVFs parked at smart parking lots, then submits its energy purchase/sell offers/bids in wholesale electricity market (WEM) as a tactical price-maker. At this point, the WEM operator, as a second level follower, is given the offers/bids from all market players, generation companies (GENCO), and NMs’ aggregator. Afterward, it clears the market to achieve the optimal value for maximum social satisfaction, and announces the locational marginal price (LMP). The electric vehicles are congregated into fleets of similar behavioural patterns by k-means clustering method considering the stochastic behavioural distributions. Moreover, the uncertain production of the renewable energy sources (RES) are confronted by the robust optimization approach. The NMs are modelled through 12 real 14-bus microgrid systems, while the WEM was embodied through IEEE 24-bus transmission network (TN). The results of different case studies show that smart EVF scheduling does not only diminish the operational costs, but also helps the NMs’aggregator in reducing market price as a tactical price-setter.