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• A two-stage robust planning model for the coupled system is proposed. • The uncertainty of renewable energy, load and traffic demand are jointly considered. • The interactions between transportation and active distribution system are explored. • A two-level method is used to solve the proposed robust optimization model. Widespread utilization of electric vehicles has incurred more uncertainties and led to profound interdependencies across the power grid and transportation network. This creates an urgent demand for uncertainty modelling tools. Under this context, this paper proposes a two-stage robust optimization model for expansion planning of coupled active distribution and transportation. This model identifies the best type, location and capacity for roads, distribution lines, distributed generations, static VAR compensators, on-load tap changers, energy storage systems and charging facilities. From a system-level perspective, the steady-state pattern of the traffic flow in a transportation network is characterized by the Wardrop user equilibrium. In the active distribution system, the conic relaxation-based branch flow equations are employed, and the operating status of related devices are formulated by the linearized convex constraints. Considering the interdependency between two coupled systems, a deterministic expansion planning model is first established. Furthermore, with multiple uncertainties considered, a two-stage robust optimization model is proposed to optimize the investment and operation strategies coordinately, and thus a robust optimal solution is achieved. A two-level algorithm based on a combination of the column-and-constraint generation and outer approximation technique is developed for solving the two-stage model. The results demonstrate that the robust approach can effectively reduce the operation cost of coupled systems under the worst-case scenarios. Moreover, a comparative analysis indicates that operation costs in both systems increase linearly as the uncertainty level of traffic demand increases, while increasing that of the power load does not show an obvious change in the traffic operation cost. [ABSTRACT FROM AUTHOR]

• A planning model of coupled transportation and active distribution system is proposed. • Scenario generation technique is extended to incorporate traffic demand. • Scenario-based user equilibrium constraint is derived and embedded into the model. • A three dimensional piecewise method is designed to relax the bivariate expressions. • The importance of considering interdependencies of the coupled system is verified. The widespread utilization of electric vehicles has inspired the emerging trend of coupled transportation and distribution system, which entails the systematic methodologies to model the new planning problems. This paper proposes a scenario-based comprehensive expansion planning model for a coupled transportation and active distribution system. With the aim of minimizing the investment and operation costs, this model determines the best alternatives, locations and sizes for candidate assets, including traffic roads, distribution lines, distribution generators, capacitor banks, static var compensators, voltage regulators, energy storage systems and charging facilities, as well as their operation strategies. First, a generated scenario method is extended to incorporate the uncertainty of the traffic flow demand. Based on multiple scenarios, the steady-state distribution of traffic flow is characterized by the Wardrop user equilibrium principle, and the corresponding equivalent constraints are derived and incorporated into the model. For active distribution system, we formulate the operation constraints for related infrastructures. Considering the interdependency between the two systems, an expansion planning model is proposed, which simultaneously optimizes the investment and operation strategies. Due to the nonlinear nature of the model, we have developed a three-dimensional piecewise linear approximation and applied second order cone relaxation to reformulate the model as a mixed-integer second order conic program; thus, the global optimal solution can be found in a reasonable time frame. Results on a test system reveal that the variations of both systems have some influences on each other, indicating the significance of considering the interdependencies between transportation and active distribution system. [ABSTRACT FROM AUTHOR]

• A novel expansion planning model for active distribution system with multiple active network managements is proposed. • Optimal load shedding is originally proposed and shows an obvious better stability performance in case study. • A SOCP approach and some linearization means are applied to solve the MINLP model. • A two-stage optimization algorithm is developed and proved to have great ability to solve this problem. • Simulation results based on a modified 37-bus system indicate the technical and economic superiority of the proposed model. In this paper, a new expansion planning model for an active distribution system considering multiple active network management schemes is proposed, where demand management considering the optimal load-shedding direction is innovatively introduced into the planning model. This model optimizes the investment decisions of all the infrastructures as well as the corresponding operational strategies in a coordinated manner. Therefore, the final solution is identified by the optimal type, location and size of the feeders, distributed generators, capacitor banks, static var compensators, voltage regulators, energy storage systems, and transformer substations. To incorporate the optimal load reduction into active network management, the optimal load-shedding direction is first introduced, and an iterative method is developed to compute it. On this basis, the coordination planning model of an active distribution system is established, and the operational strategy of all the active management devices is integrated into the expansion planning problem of an active distribution system. By applying the second-order cone relaxation method, the original mixed-integer nonlinear model is converted into a mixed-integer second-order cone programming model that be efficiently solved. Finally, a two-stage optimization algorithm is proposed to obtain the final solutions. Simulation results based on a 37-bus system and a 122-bus system corroborate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]