traffic uncertainty modeling and energy management of smart distribution networks with the presence of parking lots

Energy management (em) in smart distribution networks (sdn) is to schedule the power transaction between the sdn and the existing distributed energy resources (ders) e.g., distributed generations, especially renewable resources and electrical vehicles, from an eco-technical viewpoint. due to the dual role of electric vehicles (evs) acting as a power source and load, they presented both challenges and opportunities in em. the complexity of em increases as ders become more prevalent in sdn. moreover, the uncertainties of renewable resources, price, and load besides the uncertainties related to the place, amount, and time of ev’s charging makes em a more intricate field. this supports the necessity of extensive tools and approaches to manage em in sdns. in this respect, this paper proposes an optimum scenario-based stochastic energy management scheme for intelligent distribution networks. the proposed approach is modeled as a minlp problem and solved in gams software under the dicopt solver. the test is conducted on a 33-bus sdn with and without factoring in uncertainties.