The optimal planning of smart multi-energy systems incorporating transportation, natural gas and active distribution networks

As the energy demand for multiple purposes increases, smart multi-energy systems have become the trend in the development of cities. In such an intelligent environment, it is possible and imperative to consider the traffic flow guidance for electric and non-electric vehicles in the urban transportation network. However, this has not yet been considered in the challenges of planning multi-energy systems. Based on these considerations, a novel optimal planning framework is proposed in the present study, that takes into account the coupling of transportation, natural gas and active distribution networks. Firstly, a novel structure of integrated energy stations is proposed, which serves as coupling components where various sources of energy can be converted, distributed, and stored. The model optimizes the investment and operational strategies of renewable energy generation, energy converters, storage devices and charging facilities in a coordinated way. To capture the impact of traffic flow, a mixed user equilibrium state was established. Thus, the route selections for non-electric vehicles and the navigations of electric vehicles to charging facilities could both be incorporated into the model. Since the proposed planning model is a mixed-integer nonlinear program problem, convex relaxation was conducted to transform the model formulations into a mixed-integer second order cone program version. Finally, four cases were designed and tested in a practical urban area. The quantitative comparison revealed that unguided traffic flow will increase the traffic costs by more than 23%. Moreover, when both charging and routing guidance are considered the energy losses will decrease by at least 5.6%.