Simultaneous allocation of electric vehicles' parking lots and distributed renewable resources in smart power distribution networks

Electric vehicles (EVs) and distributed renewable resources (DRRs) are introduced to achieve three of the most pivotal objectives of this century: using environmentally-friendly energy resources, reliable supply of the load demand, and sustainable development of power systems. To achieve the aforementioned goals, simultaneous utilization of DRRs and EVs should be implemented in a scheduled manner. In this paper, we propose a two-stage approach for allocation of EV parking lots and DRRs in power distribution network. Our method considers both the economical benefits of parking lot investor and the technical constraints of distribution network operator. First, the parking lot investor offers the candidate buses for installing the parking lot to the distribution network operator based on economic objectives. Then, the distribution network decision-making is obtained to reduce loss of system. The proposed framework not only improves the distribution network loss, but also ameliorates the availability of the parking lot from the economical point of view. In order to solve the formulated optimization problem, we utilize two optimization techniques. Genetic algorithm (GA) and particle swarm optimization (PSO) algorithm are used for the distribution network loss minimization purpose. Besides, we model the EV parking lot by expanding single EV probabilistic model. The performance of the proposed method is evaluated by allocating DRRs and EV parking lots simultaneously on the IEEE standard distribution test system. This system is bus 2 of Roy Billinton Test System (RBTS).