Coordinated Optimal Operation of Integrated Electrical and Transportation Network Considering Source-Load Uncertainties in Severe Weather Scenarios

The large-scale penetration of electric vehicles and the emerging dynamic wireless charging technology strengthen the coupling between distribution networks and transportation networks. However, the randomness of travels in the transportation network, the fluctuation of the output of clean energy such as wind power and photovoltaic, and the sudden change of weather will have a significant impact on the safe and stable operation of the two networks. In this context, based on the background of wireless charging technology, a cooperative optimal operation scheduling model of electric transportation integrated network is proposed, which considers the uncertainty of traffic demand and photovoltaic prediction error, and regards it as the uncertainty factor of load side and source side of power grid. The Information gap decision theory (IGDT) is introduced to model the bilateral uncertainty of the network, and the corresponding risk avoidance model and risk speculation model are obtained. Furthermore, considering the effect of inclement weather scenarios on the uncertain factors of road traffic and charging facilities, a modified integrated network model of electric traffic under inclement weather scenarios is proposed. Finally, a case study is carried out on a test system consisting of a 12-node transportation network and a 20-node power distribution network. The results show that the information gap decision theory can effectively deal with the changes of dual networks under multiple uncertain scenarios, form a risk decision-making model, and provide theoretical support for different decision-making methods.